Curious about which online advertising platforms exist beyond your current advertising strategy?
I’m sure you’re already familiar with Facebook and Google as online advertising platforms. These behemoths are the best-known online advertising platforms out there, boasting the biggest online user bases and powerful self-service ad managers. Together with Amazon, they absolutely dominate the online advertising market.
Top 3 ad platforms by 2021 advertising revenue:
- Google: $209.49 billion
- Facebook: $115 billion
- Amazon: $32 billion
Given Facebook and Google’s popularity as online advertising platforms, you’ll face high competition with millions of other advertisers to get your ads shown and capture users' saturated attention. It’s a challenge. It also means ad prices can be comparatively high.
However, there’s a whole advertising ecosystem out there that could offer your business more reach amongst niche demographics for less cost or greater ROAS. Especially if audience targeting is more effective, regardless of the cost-per-mille (CPM) or cost-per-click (CPC) prices.
We’re not saying you shouldn’t use Google or Facebook as leading platforms within your online advertising strategy. You definitely should be using Google for paid search results. But there’s a whole ad ecosystem out there just waiting to be tested, ready to open up more opportunities for your business. As always, some testing is the best way to find out what works and what doesn’t.
The team at Half Past Nine live to help our clients develop ad strategies that maximize the reach and return against budget. To help you, we’ve pulled together this comprehensive guide to where you can advertise online, selecting the best online advertising platforms we’ve come across so far.
This guide is exclusively for brands that want to expand the impact of their paid advertising strategy; we’re not listing out free sites and directories to list your business on. It’s applicable for both B2B and B2C brands.
Keep in mind that ad prices and results fluctuate greatly by variables such as country, industry, target audience, demand and seasonality, placement, ad format, ad quality, landing page quality and audience engagement with your ads. Platform-specific benchmark data by industry and country is a valuable tool where you can get it, alongside running your own test campaigns on platforms of interest.
It’s an easier task to consider which search engines should be included among your online advertising platforms given the limited choices! As of September 2022, global desktop search engine market share is almost monopolized by Google at around 92%, trailed by Bing 3%, and Yahoo at approximately 1%.
Note, DuckDuckGo is powered by Bing and ads are managed through Microsoft Advertising, so isn’t covered separately here.
In the US in 2022, around 50% of search traffic comes from mobile, 45% from desktop, and 3% from tablets.
Google Ads offers a powerful self-service ad management and reporting platform covering a wide spectrum of advertising functionality across search engine, display, in-app and video ads.
- Reaches around 75% of the US population
- Google Chrome App accounts for 49% market share in the US
- Google Maps, another search-related product, has over 5 billion downloads
Search ad pricing can vary widely and you’ll get to select the pricing models you want to use based on your search campaign objectives and the ad formats. You can set campaign and daily budgets, and there’s no minimum spend required.
If you're an eCommerce brand, leverage Google shopping results ads within your search strategy.
Bing is a Microsoft company, and Bing ads are managed through the Microsoft Advertising platform. In 2009, Microsoft was in partnership with Verizon Media, which has since been acquired by Apollo Global Management and rebranded itself as Yahoo (combining AOL and Yahoo Gemini).
That means your Bing search ads are also shown on:
Joining forces has provided more incentive for advertisers to use Bing and Yahoo companies in competition with Google. In comparison to Google, there is also less competition for ad placements within Microsoft-owned platforms and lower ad prices.
- Older user demographics - average user being 45 years old.
- Users have above average incomes with a third making $100k+, and almost half making $75k+.
- Microsoft Ads say they have an equal gender split.
Like Google, Bing’s adverts are auctioned by CPC for selected keywords. You can target by demographics, geographic regions, and also the time of day or week. Budgeting is flexible on Bing Ads, and there’s no minimum budget to get started.
Ecommerce works particularly well on Microsoft Ads, which has shopping partnerships with companies like Amazon.
- Bing shopping campaigns have a 45% higher ad click through rate (CTR) than on Google
- CPC on shopping ads is 30% lower than Google’s average.
Powered by Bing’s search engine, Yahoo is managed through Yahoo Native. The ad manager states that your ads may run on Yahoo, MSN, AOL, TechCrunchand Engadget -Yahoo brands. It offers search and native advertising options from one platform.
- Yahoo AdTech says 20 million daily unique visitors use Yahoo
- 180 million monthly unique visitors in the US - accounting for 45% of its global traffic
- 66% of Americans visit the Yahoo homepage with an equal gender split
- If Yahoo Mail users are an indicator of Yahoo search users demographics, Statista reports that 45-54 is the biggest age group, followed by 65+, and 54-64.
With less advertiser competition, you’re guaranteed to benefit from lower CPC costs on Yahoo than you’ll get with Google or Bing, and you’re likely to get more clicks. Targeting can be done by basic demographics, keywords and search phrases.
Globally, the most popular social platforms had the following number of monthly active users (MAU) as of January 2022:
Market share and demographics for social media continues to evolve.
In the United States in 2020, around 80% of the population used some form of social media. And in the US, YouTube just surpasses Facebook for reach.
Looking at social platform growth rates in the US, TikTok is set to overtake Instagram soon, although its exceptional growth rate is starting to plateau. Reddit is another one to note because despite having a smaller user base, it currently has above average growth in the US.
Most social media content is consumed in-app on mobile devices (around 80%), so it’s a given that most of your placements will be viewed on a mobile screen. However, we’ll look at mobile advertising networks separately.
For eCommerce marketers, social commerce allows in-app purchasing, a growing trend to leverage on aligned platforms.
See more interesting social media statistics for marketers.
Facebook Ads is ideal for creating demand in consumer-oriented FMCG marketing. However, it’s still somewhat popular with B2B users. A Hootsuite study found that 48.5% of B2B decision makers use Facebook for conducting research, and users do also go to Facebook for news to a lesser extent.
Facebook’s US user demographics tends towards Millennials as the biggest user group.
In the US (as of January 2021):
- 69% of the adult population has an account, exceeded only by YouTube usage.
- 54% of users are female.
- 49% of users visit several times per day.
The price of ads tends to be mid-range, whether you choose CPC or CPM. However, Facebook ad costs can vary widely depending on your audience, ad goals and the season.
The Average Click-Through Rate (CTR) for adverts on Facebook is 0.89%.
Powerful targeting and real-time reporting are provided plus a wide variety of ad placement options.
YouTube is the best-known video sharing platform globally. Launched in 2005 and acquired by Google in 2006, it has achieved steadfast popularity. It’s the second largest social platform in the world, but the largest in the US.
As a Google platform, YouTube videos can also rank highly in Google’s organic search results. Google Chrome features a video section on the first page of search results showcasing a selection of the most popular videos for the given keyword or search term.
YouTube has a relatively unique position in that it spans the age demographics rather evenly, also engaging those in older age brackets. In terms of gender, the global average is around 56% male and 44% female.
In the US specifically:
- 81% of adults use YouTube, out-performing Facebook for total US population reach.
- 54% of users are male.
- 77% of 15-35 year olds use YouTube, and represent the biggest demographic.
- 62% of users visit YouTube daily.
According to Google Ads, 70% of viewers bought from a brand after seeing video content on YouTube.
A range of YouTube ad placements are available and ad content doesn’t need to be in video format. Ad content can be pulled through from Google search campaigns rather than YouTube-specific campaigns.
Manage your video ads through a Google Ads account by linking your YouTube channel, which gives you access to powerful targeting and reporting tools. For the best results, create YouTube ads in video format. This does require some extra content investment.
In terms of YouTube ad costs, you’ll only pay when someone watches at least 30 seconds of a video or clicks on your TrueView ad. There’s no minimum investment required and you can start with a $10 daily budget. Learn more about YouTube pricing strategies
Read more YouTube statistics.
A Facebook company, Instagram advertising can be run from the Facebook Ad Manager or by promoting posts you’ve already shared from within the app. The third biggest social platform globally, it has just over 1 billion monthly active users.
- Read Half Past Nine's guide to Instagram Reels Advertising.
FMCG and B2C brand content performs well here, as does influencer content. Instagram isn’t typically used by users as a news source and generally performs better for brands using inspirational content opposed to factual content.
It attracts users with higher than average household incomes and higher-level education.
In the US:
- There are 159.75 million users (as of Jan 2022).
- 59% of users login daily.
- The gender balance swings in favor of females at 56%.
- The biggest age group is 25-34 year olds.
There are six types of Instagram advertising formats to choose from.
Launched in 2017, TikTok grew at a viral rate, mostly among teenagers and those in their 20s as the early adopters.
It is a harder channel for B2B brands to leverage effectively, although that’s not to say it can’t be done with a more personal and UGC approach. Bear in mind that today, 73% of people involved in the B2B buying process are Millennials, and 81% of non-C-suiters have a say in purchase decisions.
As of January 2022, it has 1 billion users globally and gender is almost evenly split with 53% male and 47% female.
In the US:
- There are 100 million active users.
- 47.4% of active users are aged between 10 and 29.
- Females notably outnumber males, with 61% of users being female.
- Most users are active multiple times daily.
On average, TikTok posts get the highest follower engagement rates out of all the social platforms. In terms of ad pricing, you can get started for as little as $20 with an ‘in-feed’ ad group daily budget. The TikTok Ad Manager user-experience and reporting capability is competitive.
LinkedIn Marketing Solutions is a B2B favorite for leveraging the world's biggest professional network. It’s a no-brainer for B2B ad strategies.
LinkedIn specializes in ad targeting by professional roles and company types right down to specific companies. This career-specific targeting is not available to anywhere near the same extent through other ad platforms.
It has around 822 million active global users as of Q1 2022, and users are more likely to have higher education and earn more than average. However, LinkedIn users are less likely to use this platform daily, with most logging in either weekly or monthly.
- Around 191 million users are in the US.
- Males outnumber female users at 57%.
- 37% of users are 46-55 years old, followed by 34% aged 36-45.
- 51% of US adults who have a bachelor’s or advanced degree say they use LinkedIn compared with 28% of those with only some college education (Pew Research Center).
For ad placements, LinkedIn requires a minimum bid of $2 for CPC and CPM campaigns. Given its niche reach into B2B audiences, it’s a more expensive platform to advertise on. Despite higher prices, B2B brands could see significantly higher ROAS here.
Pinterest Ads offer a more niche audience that’s ideal for eCommerce and female consumer audiences.
There are just over 400 million monthly active users, and the demographics are skewed towards mature females in the US:
- Up to 50% of all users are located in the US.
- Females make up around 76% of users.
- 38% of users are aged 50–64, followed by 34% of users aged 30-49 years old.
If that fits your target audience, Pinterest claims that 89% of their US audience use the platform for inspiration on their path to purchase. It boasts a higher conversion rate than most, with 50% of users having purchased an advertised product on the platform, and even more having purchased a product based on what they’ve seen from brands here.
However, it can prove a more time consuming platform to get results from given the hours needed to create ‘boards’.
Here are some more helpful Pinterest marketing insights.
Reddit Ads are available on this community platform where users share links, text posts, images, or videos, which other users can vote up or down. Posts are organized by subject into user-created boards called "communities" or “subreddits” and cover a wide variety of topics.
Reddit says they’re particularly popular with gamers, tech enthusiasts, TV & film buffs, sports enthusiasts and health-conscious visitors. You’ll be able to target users based on interests, location, by communities in ‘subreddits’ and devices.
Fresh user data for 2022 is elusive, but Reddit said they had 430 million active users as of 2020, and 222 million of those were in the US. This was a 30% increase on the year before. Views and the number of monthly comments had been growing too, with 52 million daily active users.
In the US (as of December 2020):
- 49% of all traffic came from the US, followed by the UK and Canada at 8% each.
- Users are estimated to be around 56%+ male.
- 58% of users are 18-34 years old.
Reddit requires a minimum ad budget of $5/day using their self-service ad platform, which isn’t particularly advanced. You’ll pay around $0.75 for CPM and can choose display ads, Sponsored Q&As, Link post, Text Post, or Video Post.
Twitter advertising gives you access to a male majority audience representing a whopping 70% of Twitter users. The use of hashtags is king here and makes it easy to find followers highly engaged with a topic.
Unlike other social platforms, getting current news is the top reason to use Twitter. A preference for factual content makes Twitter a better fit for B2B brands, not to say B2C brands shouldn’t use it.
There are around 396 million monthly active users globally:
- Most users are from the US at around 73 million, followed by Japan and then the UK.
- 61% are male.
- Popular with Gen Z users, 42% are aged 18-29, followed by 27% at 30-49 years.
Twitter users are more open to trying new products and engaging with brands. Ads tend to receive higher engagement, and it’s popular with B2B marketers also. It works particularly well for video content. Video-based ads represent good value at around 50% less cost per user engagement.
In terms of pricing, there’s no minimum required budget to get started. Promoted tweets are charged per user ‘action’ that you’ve chosen, such as when a user clicks your link. As always, ad costs can fluctuate greatly.
If you haven’t encountered Tumblr yet, this Automattic-owned company is a pop-culture micro blogging site where people follow topics of interest suited well to B2C or DTC brands. It also uses hashtags like Twitter, but offers far more freedom on content length and format. There are 7 different post types available; text, photo, quote, link, chat, audio and video.
As of February 2021, it had around 518 million registered users. Tumblr says that around 12.8 million blog posts are published daily.
- The US accounts for the vast majority of traffic at around 46% (followed by the UK at 5-6%).
- It has the most reach with Gen Z and Millennials (15-35 years).
- Gender is reported to be a 50/50 split in the US.
Tumblr ads are shown to users based on other content they view, created as sponsored posts, video posts, or ‘Sponsored Day’. You don’t get the level of targeting features or analytics that Google or Facebook’s ad manager tools provide. However, there are still basic targeting features like gender, location, and interests.
Tumblr is targeting big brands with its ad offering; the minimum investment is reportedly $25,000 and you’ll need to submit a request to get started.
Here are some more Tumblr statistics.
Quora Ads allows you to promote your brand on this popular question & answer community site. Users create both the question and answer content, they can vote on the helpfulness of answers, and follow topics that interest them. It lends itself better to B2B content, particularly if it can be posted by company thought leaders in a personal context focused on value-added knowledge sharing.
Quora attracts around 300 million monthly active users globally:
- Around 40% of traffic is from the US, followed by India at 12%.
- Quora says the gender ratio is in favor of females at 54%.
- This user base has above average education and income; 39% are in management positions and users are 45% more likely to be senior decision makers.
- The biggest age demographic is 18-24 at 45% of users.
Adverts can be targeted by topics or keywords, by audience demographics or behavior. Placements include text ads, image ads, promoted answers and Lead Gen forms. Optimize for conversions, clicks, or impressions, and see real-time reporting in the Ads Manager.
Required investment is low, with a minimum starting budget of $25.
Snapchat Ads utilizes a unique format of picture/video messaging and news. It shows photos or short videos for a limited time, which disappear after they have been viewed. However, they can also be screen-grabbed or use a replay option.
Snapchat has 238 million daily active users globally:
- Around 107 million of them are in the US.
- 48% of users are aged 15-25, followed by 30% at 26-35.
- 55% of users in the US are female.
If this is your demographic, content is low maintenance to produce and the ad platform also offers very low CPMs. It’s a cheap channel to get a large volume ‘top of the sales funnel’ views. The Ads Manager platform allows you to get started with as little as $5, and pricing can be optimized according to your goals. You’ll be able to target users by demographics, location, interests and behavior.
Houzz is a US community network specifically for home improvement, architecture and landscape design. Users can create image-based ‘ideabooks’ for inspiration, connect with suppliers and plan home renovations costs. Launched in 2009, Houzz states that it has around 40 million homeowners using its platform. Advertising is not automated/self-service on this platform, so you’ll need to get in touch with the customer support team to get started with advertising. Learn about marketing on Houzz.
Nextdoor connects people in the same neighborhoods and areas. Uses can share local news, tips, buy and sell items or promote businesses. Founded in 2010, Nextdoor claims to reach a quarter of US households and has around 10 million users. A range of ad formats and placements are available on their self-service ad center.
Display networks show display adverts - a graphic ad format featuring banner images, rich media or text. It’s usually referring to static banner ads or video ads, which appear in allocated placement areas on websites or social media.
If you’re not familiar with display networks, they’re online platforms that own and/or purchase advertising space from other ‘publishers’, which is known as ad inventory. Networks sell ad inventory to advertisers via self-service platforms.
Display networks use programmatic purchasing technology. Programmatic means that software is used to automate the process of pricing and buying ad inventory using real-time bidding (RTB). It can optimize your bid prices to get ads shown based on your chosen pricing model against other bids that are being placed at the given time. This improves cost efficiency, ROAS, and removes the time-consuming need to manage bids manually.
Display networks can have their own ad inventory to sell, they may have partnerships with third-party websites selling ad inventory, and may also buy/sell inventory from other ad exchanges too.
Ad exchanges are online platforms that facilitate the programmatic buying and selling of ad inventory from multiple publishers in larger volumes. The inventory can come directly from publishers and through connected ad networks. As an industry, it’s not exactly completely transparent how all the networks link up.
Outside the biggest display ad networks (Google AdSense and Facebook’s Audience Network), a demand-side platform (DSP) subscription is usually needed. DSPs refer to software that facilitates purchasing directly from ad exchanges, networks and publishers.
Theoretically, this removes the need to manage your ad purchasing individually on multiple publishers/networks/exchanges, saving time on campaign management. You can also better manage dynamic targeting and personalization across multiple platforms or ad networks.
Looking at the downsides of programmatic display networks, there are some issues in the form of ad-blocking software (used by 47% of internet users), third-party cookie blocking and inaccurate reporting due to bots. For example, in the first half of 2021, 64% of all internet traffic was bots, 39% of which were ‘bad’ bots. And with less control over where your ads appear, you might also receive undesirable ad placements and associations that don’t serve your brand. Nor will you have transparency on direct publisher prices if the network is purchasing inventory through an ad exchange.
As an SME business, if you only wish to advertise on a few specific platforms, it could be that managing your ads through the individual display networks makes most sense. They cater to smaller budgets and ad inventory requirements, plus they generally require less resources than DSP platforms, whether in-house or agency managed.
Here are the top ad exchanges, display networks, and then DSPs which give you access to their respective integrated ad exchanges.
OpenX is the world’s largest independent ad exchange, with 30,000 advertisers reaching nearly 1 Billion consumers globally with 100 Billion targeted ad requests each day. In the US, the unique consumers reach up to 250,000 million.
There are over 130,000 active publishing domains that OpenX works with to meet the advertisers’ ideal audience and they claim to have the highest quality standards in the industry. They offer first party data activation, PMP tools and premium omnichannel inventory.
OpenX works with Basis Technologies and theTradeDesk to name a few DSPs, but according to their website they are compatible with whatever DSP the advertisers are currently using. For pricing information you need to contact the website directly, no public information is available.
Read OpenX user reviews.
Applovin Exchange or ALX is a powerful platform with a focus on mobile and connected TV channels. With the acquisition and integration of MoPub (currently Applovin MAX) as their in-app bidding medium, ALX connects buyers to over 2 billion mobile devices globally.
As an advertiser you will have access to ALX’s omnichannel premium inventory through any of the 100+ DSPs they are compatible with.
Pricing information is not publicly available, however the RTB tool MAX buys the inventory programmatically on a per-impression basis.
Read ALX user reviews.
As touched upon in the search engine section, Yahoo operates a search and native ad network using its owned brands called Yahoo Native, but also has a group of display ad publishing partners.
Their owned publishing platforms are Yahoo, AOL, and TechCrunch. Their publishing partners include ESPN, ABC News, Apple News (in select locations), and MSN, among others. They say they serve 2 billion ad impressions a day to 1 billion monthly active users.
In addition to the Yahoo Native platform, Yahoo AdTech offers a DSP platform, giving more advanced access to Yahoo & Microsoft properties, plus their premium native marketplace of partners. Pricing information for this platform is not publicly available, and is suited to larger advertisers. However, you can get started on the Yahoo AdTech network with as little as $5.
Read Yahoo AdTech DSP.
Index Exchange is a programmatic advertising platform that connects every involved party in its systems. It has solutions designed for publishers, advertisers and DSPs. According to the website, Index offers premium omnichannel inventory through its partnerships with the world’s most trusted media owners.
The platform proudly offers placements for “any ad format, on any screen”; including display, CTV, native, video and mobile apps.
Index Exchange partners with over 150 DSPs, meaning you can most likely use the ad exchange with your preferred DSP with no compatibility issues. Pricing information is not publicly available.
Display Ad Networks
Google's ad exchange allows the advertiser to manage ad campaigns across multiple channels from Google Ads to YouTube and Google’s Display Network.
As an advertiser, you have access to Google’s display network through the Ad Manager. There are over 2 million websites in the Google Display Network (GDN). They have, of course, been screened by Google before inclusion in the network. Your display ads will be shown on the most relevant sites based on the user demographics and targeting you have chosen.
You have the option to manage the bidding manually or let the platform manage the bids for you. Google provides automated bidding strategies depending on your goals. There’s no budget requirement to get started on Google Ads.
Adsterra is an ad network with self-service functionality, offering banner advertising among other formats such as pop-under, native and pre-roll video. Ecommerce is one of their main industry verticals. They have 18,000+ publishers in their network and serve 1 billion ad impressions a day.
The minimum deposit for advertisers is $100 and there’s no license fee, and there are some minimum bid prices in place to note.
Read Adsterra user reviews.
Media.net is a smaller programmatic advertising network that offers a network of ‘premium’ publishers with a particular focus on blogging websites and delivering contextually relevant ads.
You benefit from their relationships with DSPs, Agency Trading Desks, Horizontal Networks, Vertical Networks, Performance Networks, AMPs and DMPs. They’re also partnered with platforms such as Facebook Audience Network, and most network traffic is from the US, Canada and the UK.
Media.net manages ad supply on over 500,000 websites. They currently manage traffic that generates 70+ million ad clicks each month. Pricing information is not publicly available.
Read Media.net user reviews.
Adform is an independent modern marketing advertising platform that offers DSP and SSP solutions with over 2,000 global clients. In 2022, Adform’s DSP was awarded the “Best DSP” by Adweek Reader’s Choice.
Adform offers cross media activation via FLOW, which uses augmented reality to “amplify business results”. With this, advertisers can utilize programmatic and direct buying with campaign reporting and optimization for channels such as display, audio, video and CTV.
Adform provides access to inventory through its 100+ partners. Pricing information is not publicly available.
Read Adform DSP user reviews.
TheTrade Desk is the world’s leading independent demand-side platform (DSP) that enables advertisers to access and buy digital advertising inventory across “every channel and device” in real-time.
The DSP platform offers a range of sophisticated targeting and optimization features that help advertisers reach their desired audiences more effectively, including cross-device targeting and multiple buying models.
The Trade Desk has become known for its commitment to transparency. With OpenPath, TheTradeDesk’s transparency pipeline, advertisers can access premium inventory directly from the platform and have a direct representation of how the media dollars bring value with each purchase.
As a guideline keep in mind that the minimum monthly spend starts at 100K, but for specific info you would need to set up an account.
Formerly known as the Rubicon Project, Magnite was born after a 2020 merger that combined Rubicon’s experience as a programmatic exchange and Telaria’s extensive CTV capabilities. Today, it is the “world’s largest independent sell-side platform (SSP)”, working with thousands of publishers; but it also serves advertisers as an omnichannel supply partner.
To advertisers, Magnite offers a programmatic advertising marketplace where they can buy inventory for display, video, audio, and connected TV (CTV) advertising. Pricing information is not publicly available.
Beeswax DSP is a programmatic advertising platform offering real-time bidding, audience targeting and optimization tools for inventory across various channels such as display, video and CTV. The platform creates custom algorithms and data models for each ad campaign which provides transparency and control over the campaign materials
One of the unique aspects of Beeswax is that it allows you to build your own programmatic advertising platform using its infrastructure called Baas (Bidder-as-a-service) which allows for greater customization.
Since there is a personalized aspect to the service Beeswax provides, pricing varies and you would need to contact an expert on the website.
Read Beeswax user reviews.
For ecommerce advertisers, Amazon Advertising offers a range of advertising services, including display ads. A self-service option lets you advertise on a smaller scale within Amazon, however they also cater to larger budgets with a more advanced DSP. It’s an ideal place to reach shoppers who are on Amazon with a high intent to purchase.
Amazon’s DSP solution enables advertisers to programmatically buy display, video, and audio ads both on and off Amazon. And you don’t need to sell products on Amazon to use it. Amazon has publishing partners and connects to third-party ad exchanges to give you reach. However, the Amazon DSP service requires a minimum spend of $15,000 (may vary by country).
For Sponsored Display ads, there is no minimum ad investment required and you can set daily bid and budget limits.
Read Amazon DSP user reviews.
AdCritter is a DSP especially designed for small businesses, putting self-service programmatic advertising within reach of smaller budgets who want to reach audiences beyond Google and Facebook.
The platform features an ad builder with pre-designed templates or user-friendly design functionality. There’s audience-based targeting functionality with over 200,000 audience characteristics to choose from, including geo-targeting, and automated optimized targeting. You can also select website categories, or even favorite websites, where you want your ads to appear.
AdCritter can place your ads across the entire internet ecosystem, with functionality to automatically place them on the sites that generate the best results. With AdCritter’s connection to ‘all the major ad exchanges’, you’ll still get competitive pricing for your ad placements.
Start with a 30-day free trial, and progress to a Standard subscription plan for $149 per month (doesn’t include ad budget).
Read AdCritter user reviews.
Choozle lets advertisers plan, buy, execute, and measure ad campaigns from one platform. Using self-service programmatic functionality, its reach gives you access to an impressive 98% of online ad inventory and 40+ ad exchange networks. They serve ads on premium ad networks like MoPub, OpenX, Google Display Network, Yahoo, AppNexus and Yahoo.
Choozle supports multiple ad formats, including display, video, mobile and native. With cross-device and cross-channel targeting functionality, they offer the flexibility to use first-part or third-party data to create campaigns for custom audiences composed of your most valuable users. There are 60+ third-party data providers you can plug in. You can also target specific locations, or web content and page categories.
They have a starter Growth subscription plan for $99 per month and no minimum ad spend required, for “Liberated digital advertising for everyone”.
Read Choozle user reviews.
SharpSpring Ads provides cross-device retargeting ads for ecommerce across web, mobile, Facebook and Twitter. It will help you set up targeted and personalized product or shopping ads. You can integrate your Shopify store and use the self-service Dynamic Ad Builder to automatically create relevant ads from your products.
In terms of pricing, the self-service platform is free as long as you spend $100 per month, and there’s no set-up fee. A 14-day free trial is available and you’ll get $100 free credit too.
SharpSpring Ads say: “Set your own campaign budgets and spend as much or as little as you like! We charge on a CPM basis and all campaigns are prepaid for self-service customers.”
For ecommerce brands, AdRoll helps you reach customers as they browse the web, use social media, and in their email inbox. It offers a centralized platform to access ad inventory from Google, Facebook, Instagram, and another 500 suppliers.
Working with over 12,000 brands, they say they ‘predict online shopper behavior and ad and store performance better than anyone’. Their machine-learning platform uses data from billions of customers’ interactions with hundreds of thousands of brands to make better ad placement recommendations.
You can use the Starter version of the platform for ‘free’, or get advanced features on the Growth subscription plan from $19 per month. Get a 30-day free trial for the Growth plan.
Read AdRoll user reviews.
Criteo helps you accurately target and re-engage more of your customer base with dynamic paid display ads across web, mobile browsers, connected TV (CTV) and apps. Particularly well-suited to ecommerce, Criteo offers a programmatic ad platform that lets you run, manage and analyze your ad campaigns.
Criteo say that 20,000 marketers use the platform. Pricing information is not publicly available.
Part of the Shopify Plus partner program, Criteo says: “Gain access to the best ad inventory available. With thousands of the world's top publishers in our open Commerce Marketing Ecosystem, you get better placements across leading sites.”
Read Criteo user reviews.
Basis DSP solution (formerly Centro) unifies programmatic, search, social, direct, and advanced TV in a single interface. You get built in business intelligence, automation tools, search and social integrations, including Facebook, LinkedIn and AdWords.
They provide access to 50+ ad exchanges and inventory from 11,000 publishers, and there are 25,000+ audience segments to drill into. Over $1 billion of marketing activity has been activated through Basis in the last 3 years. Pricing information is not publicly available.
Basis says: “Plan, buy, and optimize your omni-channel campaign using the #1 rated DSP on G2 Crowd.”
Read Basis user reviews.
More Display Platforms:
Smaato - This ad exchange reaches 1.3 billion monthly unique users, and also offers a DSP for advertisers. “Manage and optimize campaigns for any device with the Smaato Marketer Solution. Reach quality audiences worldwide and deliver hyper-relevant experiences with contextual targeting optimization.”
AdCash - With banner, push, pop-under, interstitial, native and autotag ad formats, Adcash is a global self-serve online advertising platform for media buyers, affiliates, ad networks and publishers.
AdMaven - This digital display advertising network provides access to 2 billion daily impressions worldwide. AdMaven offers self-service, managed CPA with auto optimization, or programmatic endpoint integration. Supported ad formats are banner, push, pop-under and interstitial.
AdRecover - Use AdRecover to target ad-blocked users (mostly Millennials) with permission-enabled ads. AdRecover lets you show non-intrusive static/text ads.
Ads Compass - This ad network offers in-page, push, pop and native ad formats, with a user-friendly dashboard and customer support. “Having our own Ad Exchange and Self-Served Platform, we are able to provide all our partners multiple options to collaborate.”
Epsilon - Epsilon maintains the industry’s largest set of pseudo-anonymous consumer data, providing complete views of 200 million real people across their online and offline activity. They offer a network of 1.1 million websites, a private in-app exchange and provide access to nearly every RTB ad exchange and social media publishers.
Marin Software - “Marin has helped advertisers manage over $40 billion in search, social and eCommerce ad spend, in the process identifying three principles for growth.”
Exoclick - Access the world's largest entertainment inventory from one single platform, with a premium marketplace for top Alexa sites. Buy on their RTB platform, with multiple ad formats available beyond just display advertising, including push, native, interstitial and pop-unders.
JuicyAds - A provider of banner ads and pop-under on entertainment websites - perfect for promoting video games, gambling, mobile apps, and webcams. They ‘service a wide range of websites including Tubes/Video, Hentai/Anime/Toon, Gaming, and Social Networks’.
NativeAds - “Our demand-side platform makes it simple to launch strategic native, display, video, and retargeting ad campaigns at scale. Choose self-service or have one of our talented marketing experts handle everything for you with our managed option.”
PlugRush - “Receive high quality traffic through deep targeting and automatic optimization from thousands of websites.” Buy display ads, push notifications, pop-under or native formats.
PropellerAds - PropellerAds is a display and mobile ad network with a self-service platform and automated ad optimization, providing access to a billion users. With push, pop-under and native interstitial formats, use beginner-friendly and pro-level tools to deliver your desktop and mobile ads to your target audience.
Vibrant Media - Vibrant Media are focussed on contextual targeting and highly viewable advertising that is relevant to what people are viewing at the moment.
In-App Mobile Advertising
In-App advertising is, as the name suggests, when adverts are shown within mobile apps. The app developer gets paid per click to serve ads to its users. In-app display advertising can be effectively delivered through self-service social or Google Ads. However, you can go down the DSP route too, with some specializing in mobile app inventory.
Websites are still predominantly accessed by desktop, accounting for around 56% of their traffic. However, with low opt-in rates for website tracking cookies (which usually only work short-term) on top of online ad blockers, website display ads compare less favorably to in-app ads. In-app advertising uses device ID’s to track users, capturing far more accurate and detailed data, right down to GPS locations. Plus, a mobile device ID is generally active for 21 months on average.
Although smartphone ownership is highest in the younger age demographics (at least 93% of Millennials), 2019 research showed that smartphone usage is high across the age demographics. 68% of baby boomers (aged 53-73) owned a smartphone, and 59% were using social media. People aged 65+ actually only spend a third of their digital media time on desktops.
From the average 4 hours people spend using mobile devices daily, 88% of that time is spent within apps.
The Apple App Store has around 1.96 million apps available to download at the moment, and Google Play Store has even more at 2.87 million. See the most popular apps globally and by country, going by number of downloads in 2020 alone.
Facebook Audience Network Ads
Facebook Audience Network Ads lets you run your ads on thousands of mobile apps outside Facebook through third-party apps who’ve signed up to their ad network. Since March 2020, the Facebook Audience Network only supports in-app advertising. Big brand partners include apps like Tinder and Voodoo. It’s like they purchase from other networks too, acting as a third-party.
You can use Facebook’s powerful targeting capabilities and campaign objective tools, run retargeting campaigns, or reach more people who don’t have a Facebook account. Choose from native, rewarded video and interstitial ad formats.
Although the Audience Network reports lower click-through rates, the lower costs reflect that. CPM prices on Facebook Audience Network over 2020 were around 32% cheaper than Facebook and Instagram newsfeed ads.
Given lower click-through rates resulting in generally higher customer acquisition costs, the audience network works best as a supplement to Facebook or Instagram ads, giving you more audience reach.
Google AdMob is a mobilead network for app developers who want to earn money showing ads on their app. It supports the following ad formats: native, rewarded, banner, video, and interstitial ads. Google AdMob says that it’s used by 81% of the top 1,000 Android apps, 1 million + apps, and 1 million + Google advertisers.
As an advertiser, you can access the AdMob network by choosing to target mobile users in the standard Google Ad Manager. If you wish to advertise your own app, you can also use Google Ads to create an App campaign.
Google uses machine learning to optimize your app ad campaigns for you, including placements and bids. Google decides where your app ad will be shown in its network of properties.Your ads could appear across Google Search, Google Play, YouTube, Discover, and over 3 million third-party sites and apps.
Apple Search Ads
Apple Search Ads is currently only for businesses with an iOS app already listed in the Apple Store. Apple says that 70% of App Store visitors use the search function to find apps, 65% of app downloads occur directly after a search, and the average conversion rate of app search ads is 50%.
Apple’s App Tracking Transparency (ATT) update controversially blocked other ad platforms from collecting most Apple user data for the purposes of ad targeting. Consequently, Facebook in particular has lost a huge chunk of app ad installs to Apple Search Ads, which accounted for 58% of all iPhone app downloads from advert clicks by September 2021. As a result, Apple Search Ads was by far the fastest growing ad network of 2021, radically outstripping the growth of any other network since it implemented the ATT framework.
Use Apple Search Ads Basic with ‘intelligent automation’ functionality, for budgets up to $10,000 per app per month. Or use Apple Search Ads Advanced to manage your own campaigns. Choose your keywords and audiences, and set your own bids and budgets. You pay when a user taps your ad. Detailed reports let you track key metrics, and their APIs help you measure value and manage at scale.
Samsung Ads offers you access to their huge user base for Samsung mobile device (as well as their Smart TVs and CTV).
Samsung is the biggest marketshare holder for Android devices at approximately 34% of the global market. There were over 3 billion active Android mobile devices globally - that's double the amount of Apple mobile devices, so Samsung accounts for around 1 billion Android users. Samsung’s market share in the US was 24% as of April 2021.
You can access their audience via Direct IO, Private Marketplace, or the Samsung DSP. Unlike Apple, any advertiser can access their network, not just app developers.
You'll need to contact Samsung to set up an account and get started.
SmartyAds is an ad exchange suitable for SMEs, with a user-friendly Mobile Advertising DSP available, and a self-service option. Their network extends beyond mobile advertising, however you’ll have access to 20k+ mobile apps here in addition to 25K + premium publishers.
The SmartyAds platform lets you deliver a variety of mobile ad formats on a RTB purchasing CPM basis, with audience targeting including GEO, OS, IP, timing, device type, and more.
SmartyAds says: “The self-service ad platform doesn’t require a certain sum of money for the campaign to start, however, it is advisable to make the minimum deposit ($1000) to maintain your ability to bid and compete for the best inventory.”
Read SmartyAds user reviews.
Epom Ad Server
For programmatic purchasing, the Epom DSP is available for a flat tech fee of $2,000. Connect your DSP to Epom Ad Exchange, and you’ll be able to access ‘exclusive mobile and in-app inventory that is hard to find elsewhere’.
The Bidding Autopilot feature automates bidding optimization for you, keeping you away from underperforming traffic sources. Choose the advertising goals that you want to achieve like CTR, CPA or CR, and see real-time analytics. Varied ad formats are available and are easily customized for mobile and in-app campaigns.
Read Epom user reviews.
Use it to reach your exact targeted audience at the lowest possible cost with automated bidding powered by BidQ™ Deep Learning Technology. It includes a creative platform to help you design high impact, mobile-first ad formats, and enables ‘enterprise-grade’ API integrations with over 15 partners. Pricing information is not publicly available.
Read Inmobi user reviews.
Airnow Media (formerly Airpush) offers programmatic advertising within their mobile display network. Established in 2011, it allows you to target over 100 million monthly active users across 300,000+ apps. They state they have run over 47,500 ad campaigns to date, and TikTok is one of the major publishers they have partnered with.
Their DSP allows programmatic buyers to bid on Airnow Media inventory via real-time bidding, giving you access to more than 800,000 publishers. A managed service is available, or self-service for ‘the advanced marketer & agencies who prefer to have complete control’. The DSP also offers event analysis functionality, to help you remarket to users most likely to re-engage. Pricing information is not publicly available.
More In-App Networks & Platforms:
AdColony - “With a direct supply of almost 450 million users and a total reach of more than 1.5 billion, AdColony is the trusted source of in-app inventory for brands where direct supply and programmatic expertise combine to create true advertiser success.”
Affle - This ‘end-to-end’ platform helps you acquire new customers, and has reached over 2 billion mobile devices to date. They enable mobile advertisers to acquire users at scale, across directly integrated publishers, programmatic platforms, and relevant app recommendations.
Bidease - “Bidease is the only mobile DSP that provides advertisers with access to the entire mobile ecosystem through the world’s most popular mobile publishers and exchanges.”
Mediasmart - Use Mediasmart’s DSP, a self-serve mobile programmatic platform that provides an integrated mobile advertising solution. It has “unique capability of measuring incremental metrics in real-time for Proximity and App marketing campaigns”.
Spotify - Spotify serves audio and video ads to your audience while they’re on the app, whether they’re listening to music or podcasts.
start.io - “With the support of Start.io’s mobile data expertise and partnerships with publishers and DSPs across the global app ecosystem, you can reach your precise audience and maximize your marketing ROI.”
Tapjoy - "We make it easy for advertisers to connect with exclusive audiences in the world’s most popular mobile games and apps.”
Taptica - “We serve all mobile goals and cover every publisher source type, so that we can connect you with your ideal audience.”
myAppFree - Grow your app by finding the right users. “It’s very easy: set up your promotional campaigns in a few clicks, choose a cost per install and you are ready to go.”
Liftoff - “Engage more users with your app. Discover and engage high-quality audiences you couldn’t reach before through our extensive ad network. By working with our team of creative experts, you’ll get more eyes on your app.”
Unity - “Unity User Acquisition solutions enable you to easily run ad campaigns and be seen by millions every day on apps and games. A diverse ad supply, advanced targeting tools, insightful analytics, and self-serve dashboards help you manage your campaigns and profitably scale your app or game.”
Native advertising is when ad content matches the look and format of the organic content surrounding it, following the style of the particular website or social platform. So native ads look like an organic part of the page rather than an advert.
It typically looks like search results, newsfeed posts, content or product recommendations. Sponsored content can be purchased programmatically in some cases. Paid editorial is another example, although it is usually arranged directly with media publications rather than purchased programmatically.
Native is an increasingly popular ad format thanks to its effectiveness at engaging users. Native ad spend in the US is expected to increase 21% in 2021 to $57 billion (eMarketer). Research shows that:
- Consumers look at native ads 52% more frequently than banner ads
- Purchase intent is 53% higher for native ads
Native advertising is also increasingly purchased with programmatic buying and the use of DSPs.
Discover some more fascinating native marketing statistics!
Taboola lets you access ‘premium publishers’ at scale using native ‘sponsored’ content or video ad formats combined with programmatic buying functionality.
With a focus on high-brow editorial sites and exclusive partnerships, their network includes publisher websites like Business Insider, USA Today, Bloomberg and more. Monthly, they serve 360 billion ads to 1.4 billion people across the web. With 10,000 premium publishers, you can reach 44.5% of global internet traffic.
The Taboola platform gives you user behavior insights, and lets you create native ads with flexible creative tools for a variety of native ad formats. You also get to control where your ads are served and what surrounds them. The self-service option is available for an ad budget of just $10 per day, however they recommend starting with $50.
Taboola say: “Taboola’s Smart Bid feature takes the guesswork out of manual bid adjustments in order to ensure that advertisers are getting their most effective placements at the lowest cost.”
Read Taboola user reviews.
Microsoft Audience Network
The Microsoft Search Network show search ads on Bing and partner search sites, and also through Windows 10, Cortana and Office. Search partners include the Verizon Media brands - Yahoo, MSN and AOL.
However, Microsoft’s advertising offering also includes native ads through the Microsoft Audience Network. Cross-device ads are delivered through third-party platforms, which could include Amazon’s devices, web results for Siri, Spotlight Search on Apple devices, maps on thousands of websites, and brands like Fox Business and CBS Sports. Microsoft says: “Connect with millions across devices through high-quality native ad placements and IAS certified brand-safe properties.”
With Microsoft, there’s no minimum fee to get started and you can sign up for free. You only pay for clicks, and can manage your ad budgets on a daily basis. You’ll get better ROI than Google with Microsoft ads, with lower click costs and users more likely to click, compensating for smaller search volumes.
Voluum DSP is a platform to run native ads with a CPM price model on 20+ networks, all managed from one platform. Networks connected with the Voluum DSP include Taboola, Smaato, PubNative, and a number of other well known and high volume ad exchanges. Voluum also offers a private marketplace for the highest premium publishers and placements.
Buy programmatically and automate inventory bidding based on your pricing preference, whether it’s CPC, CPA or more. Targeting capability allows you to promote your ad on sites related to specific topics, powered by deep learning capabilities. There’s also real-time reporting to help you optimize campaign performance.
Access to the platform is free, although they have self-service or managed plan options. For self-service, you just need a $500 initial top up, and there’s no minimum monthly ad spend.
OutBrain is focussed on native ‘recommendation’ ad content for the open web. It delivers 344 billion recommendations monthly. It can help you reach ‘one-third of the world's consumers engaging with content’, and also claims to have 62% cheaper CPCs than Facebook.
Purchase inventory directly from the Outbrain Amplify platform, or programmatically via the DSP of your choice. Outbrain Amplify functionality includes auto-optimizing of bids for your campaign goals, whether conversions, CPA, or ROAS. You can target new audiences similar to your top existing customers, re-target, and use first or third-party data to reach your most relevant audience. Outbrain also offers their own programmatic DSP solution, Zemanta.
OutBrain’s minimum budget for a campaign is $10/day or $300/month, and the minimum cost per click (CPC) is $0.03.
RevContent is a native content ad network that says it’s for businesses of all sizes. They offer a self-service advertising platform to provide granular targeting & audience optimization tools, real-time reporting and access to their network of premium publishers. Choose your websites and ad placements, devices and OS, right down to audience zip codes. Pricing information is not publicly available.
Read RevContent user reviews.
Zillow is a US real estate marketplace, where people can buy and sell their homes. It’s free for users to list a home for sale or rent. Zillow for brands reaches customers across the nation’s largest real estate network, claiming two-thirds of the market share in online real estate. With native advertising solutions for brand advertisers, you can reach 201 million monthly unique users.
Zillow’s native ad network comprises Zillow, Trulia, StreetEasy and HotPads. Use their native programmatic platform to automate and optimize your ad bidding for enhanced cost effectiveness. Get started with a minimum campaign investment of $15,000.
More Native Ad Networks & Platforms:
AdBlade - Native formats and content advertising is a strong focus for this network, although display ads are also available.
AdNow - This native advertising network is connected with 160,000 publishers, serving 1 billion daily content recommendations.
Bidtellect - A DSP for native advertising that maintains an ecosystem of native inventory with over 5 billion auctions per day.
Dianomi - “The native ad platform for business and finance.” Adverts are served on premium publications, using technology to secure placements alongside contextually relevant editorial content. It is used by brands in financial services, technology and corporate sectors.
Earnify - A DSP, “Earnify is connected to all major native advertising networks”.
EngageYa - “With our native advertising platform you control and manage every aspect of your inventory to maximize ad revenue potential.”
Evadav - Evadav offers native, push, in-page and pop-under ad formats, and serves 2+ billion impressions per day. “We offer bespoke technology, a 24-7 client care service with dedicated account managers, and a wide range of ad formats and payment options to suit you.”
MGID - A native advertising and programmatic platform, their network includes 23k+ content websites with 850 million unique monthly visitors.
Nativo - Reach millions of consumers with native articles. “Nativo’s high-performing and exclusive formats tell powerful brand stories and build meaningful connections across the consumer journey. Available through our managed service, programmatic deals and self-service offerings.”
redirect.com - Redirect.com allows clients to buy or sell traffic through a real-time bid system. Purchase native, email, display, pop, domain, RON traffic and more.
Runative - This programmatic native and push ad network offers a self-serve platform where advertisers can start running campaigns with a budget as low as $100.
TrippleLift - “TripleLift has built a portfolio of modern ad products. From our roots in Native programmatic ads, we have expanded into Display, Branded Content, Video and Television. Integrated with the nearly all of world’s top DSPs to provide you with easy access to the most engaging advertising experiences across formats and platforms.”
The advertising landscape is truly extensive, and we haven’t touched on the vast selection of online media publishers and independent publications yet, from news and industry verticals to entertainment. It’s not practical to list out individual media publishers across industry niches.
However, here are some further selected examples of other ad networks, platforms and publishers you can find out there.
Connected TV (CTV) + Streaming
Google Ads - In your video campaign targeting, include TV in the devices category to access users on TVs that stream YouTube content, reaching video game consoles, smart TVs (such as Apple TV), and Chromecast.
Google Display & Video 360 - For enterprise advertisers, this campaign manager tool offers capacity to plan , buy and measure CTV campaigns.
Amazon Advertising - "Our video advertising solutions combine first-party insights, measurement capabilities, exclusive inventory and priority access to third-party content through Amazon Publisher Direct. Use Streaming TV ads and online video ads to engage audiences through an expansive supply of quality streaming content, on streaming TV and across the web."
Apple TV - Like the App Store, Apple TV advertising is restricted to developers with an Apple TV app that they want to promote. (The best way to target Apple TV users is through iOS apps most popular with Apple TV users.)
Samsung Ads - Reach global audiences at home on their Samsung Smart TVs and CTV.
Criterio - "Combine video advertising with performance capabilities to reach and convert consumers across CTV, OTT, and online video."
StackAdapt - "Plan, execute, and analyze your programmatic campaigns in all ad formats on a single platform. Our multi-channel offering allows you to integrate CTV ads into your full-funnel campaigns with confidence and ease."
SmartyAds - Appeal to larger audiences on a cross-screen programmatic platform specially tailored for multiple types of video ads. Build your own creative library with engaging desktop, mobile, in-app, and CTV ad units.
TheTradeDesk - Reach users on CTV, through video, audio, and public spaces. Access a marketplace of 225+ partners, from Fox News to Spotify.
Amobee - "We support planning, activation and optimization for omnichannel campaigns, with a deep reservoir of CTV in our marketplace."
Magnite - "We offer a flexible and scalable solution to access premium television, including live sports on CTV."
VDX TV - “Magnify the magic of your TV/Video ads from the TV to every household member's personal device screens.”
BuySellAds - BuySellAds are focussed on niche tech audiences. “We make it easy to connect with tech audiences at scale. Reach developers, designers, early adopters, crypto enthusiasts, and other tech-savvy audiences in a single platform.”
Capterra - Capterra is a search and review platform for B2B software, with 5 million business software buyers visiting Capterra every month. Advertise to highly engaged business users with a PPC model.
Slashdot Media - Slashdot Media is a global leader in professional B2B & technology communities. Their properties include SourceForge.net, slashdot.org, VoIPReview.org, wirefly.com and MyRatePlan.com - among others. These websites provide comparison tools, reviews, software, and forums where business and IT professionals evaluate and make intelligent decisions on IT solutions, and connect with technology sellers. Advertising options include display, native and email marketing.
Gourmet Ads - Gourmet Ads is the first ad network 100% committed to the food and wine verticals. With managed services and programmatic options, they use their own proprietary ad serving technology, integrated on Appnexus infrastructure and with major SSPs. Access their network of 1,700+ websites and 55 million + users.
Commission Factory - Specialized in affiliate marketing, they connect affiliates to brands and brands to customers. Their platform integrates with all of the major shopping carts and tag management software.
Performcb - “We specialize in generating consistent, quality customer acquisitions at high volumes through exclusive affiliate channels on native, mobile, social, email, contextual, SMS, and search placements."
Specialized Ad Formats - Audio, Pop Ups + Forms
TheTradeDesk - Reach users through CTV, video, audio, and public spaces. Access a marketplace of 225+ partners, from Fox News to Spotify.
SXM Media - Buy audio, video and podcast advertising, connecting you to the largest share of the US podcast audience. Podcast advertising is a digital audio platform reaching 104 million educated, affluent and mobile listeners every month.
Brave Ads - Brave Ads are supported on Brave VPN Browser. “As consumers browse, they are presented Push Notifications featuring the brand name, a call to action that drives the user to the advertiser’s desired landing page, and a click-through URL.”
Opt-Intelligence - Opt-Intelligence are specialized in serving form-fill ads to enhance your lead generation and/or grow your email subscriber list. No landing pages necessary!
RichAds - Using push, pop or native ad formats, reach new audiences and conversions with RichAds, a global self-serve ad network with 4 billion + ad impressions per day.
PopAds - “PopAds is simply the best paying advertising network specialized in pop-unders on the Internet. We guarantee you that no other pop-under ad network will pay better than us!”
Do you need support with your online advertising strategy? Half Past Nine is a Performance Media and Marketing Intelligence specialist offering a white-glove service perfectly tailored to our individual clients. We work with a select group of brands ready to invest in maximum results from an ad budget in accelerated timeframes. Get in touch with us and we’ll be delighted to discuss the possibilities.
What To Read Next:
- Audit your PPC agency with 5 important metrics.
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- For B2B brands: Optimize your content distribution strategy.
Unlock Revenue Growth With Data
Knowing where to invest marketing budget to increase contribution margin and overall revenue growth is the #1 pressing challenge for any marketing or growth leader.
As multichannel complexity and media budgets grow, attribution becomes one of those topics we really can’t ignore.
To truly understand the most valuable customer journey design, relying on default attribution reporting within ad platforms or Google Analytics just doesn’t cut it. In fact, it can even do more harm than good due to misattribution and double attribution - a big problem with these uncensored (and self-serving) tools.
The trouble with free on-platform attribution reporting (like Facebook or Google Analytics) is that they are siloed walled gardens that work in isolation with their own limited data sets. Your most powerful and valuable attribution analysis needs to cover everything, directly tied back to revenue results.
Without a proactive attribution strategy that connects all your customer journey and conversion data, optimized customer journey design will remain an elusive mystery. Highly influential channels like dark social or offline interactions are often underestimated or completely missing, while non-profitable campaigns are over-indexed.
The difference in business results can easily stack up to millions of dollars in wasted budget and lost opportunities - especially where larger paid media budgets are involved.
Let’s explore how marketers can master attribution to start hitting revenue targets with much greater confidence and certainty.
The Impact of Not Using Accurate Attribution Reporting
The impact of not using attribution reporting - or using it poorly - is worth understanding. It can have multiple negative impacts on decision-making and overall business performance.
The common consequences are:
Incomplete Customer Insights Cause Poor CX
An incomplete understanding of customer preferences, motivations, and pain points hinders the ability to tailor marketing strategies to effectively engage and convert customers.
This can result in a lack of adequate content personalization and a poorer customer experience (CX), meaning your brand gets overlooked in favor of others by potential customers.
Unprofitable Resource Allocation
Struggling to accurately identify the marketing channels, campaigns, or touchpoints that are driving conversions or desired outcomes results in less effective use of resources.
For example, over-investing in underperforming channels, and underinvesting in high-impact touchpoints, wasting budget in the process.
Poor Revenue Growth and Limited Brand Equity
Incorrect assumptions about the impact of specific touchpoints or channels results in suboptimal marketing performance and missed opportunities.
If marketing efforts fail to engage and convert customers effectively over time, the business can suffer from stunted revenue growth, also putting a cap on brand equity.
Understanding the Challenges for Accurate Attribution
Marketers can’t fully rely on free attribution solutions for the insights they need to drive significant optimizations. Results can be significantly misleading when solely using free on-platform attribution reporting.
On-platform attribution issues:
- No Cross-Channel Visibility - On-platform attribution doesn't have full visibility into the performance of other channels, or wider customer journey outside of their own ecosystem, acting as walled gardens. This limited view can make it difficult to understand the true impact of each channel on conversions and ROI (or ROAS).
- Double Attribution - When using multiple platforms, there's a risk of double attribution - where more than one platform takes credit for the same conversion. This overlapping attribution may cause businesses to overestimate the performance of certain channels or campaigns, and consequent overinvestment stunts overall marketing ROI.
- Inconsistent Attribution Methods - Different platforms apply different attribution rules, leading to inconsistencies in how they assign credit to various touchpoints. This inconsistency can make it challenging to accurately compare the performance of different marketing channels or campaigns.
- Tracking Limitations - With increasing data privacy regulations, third-party platforms may face challenges in accurately tracking user behavior across channels. A custom attribution model can help overcome some of these limitations by incorporating first-party data and other tracking methods.
- Lack of Customization - On-platform attribution reporting may not be tailored to your specific needs, goals, and marketing strategy. A custom attribution model, on the other hand, can be designed to accurately reflect a business's unique customer journey, allowing for more precise insights into the performance of each marketing channel and campaign.
There is a compelling case for marketers to invest in their own customized attribution solutions. Especially when paid media investments start becoming more significant.
However, accurate attribution modeling isn’t one of the most straightforward tasks for a marketing department to tackle.
There are several hurdles to overcome to extract and benefit from the most valuable insights:
1. Tracking Data Across Complete Journeys
A typical user journey involves multiple devices, channels, platforms, and time breaks between visits, making it difficult to track a complete customer journey path from the first touchpoint to conversion. Cross-device tracking techniques are needed, such as device matching or probabilistic modeling.
2. Data Privacy
Tracking restrictions and cookie limitations can limit the ability to track customer interactions across marketing channels, sometimes requiring workarounds. Yet it's essential to adhere to data privacy regulations, maintain transparency and obtain appropriate consent from customers when collecting and utilizing their data.
3. Offline Data Tracking
Marketers may need to implement strategies such as unique identifiers, coupon codes, QR codes, or call tracking to link offline interactions to specific customers and attribute them properly. However, implementing and managing these tracking mechanisms may require additional resources and operational adjustments, including manual data entry from both customers and staff.
4. Data Quality and Completeness
Ensuring the accuracy and completeness of the data is crucial for building reliable attribution models. Marketers must establish data quality control measures, address data gaps, and perform regular data validation to maintain the integrity of the data.
5. Data Integration
Integrating data from various sources, both online and offline, can be complex. Offline data sources such as in-store purchases, call center interactions, or direct responses may not be easily captured and linked to other digital data. Marketers need to develop data integration processes to build a unified view of complete customer journeys.
6. Attribution Modeling Complexity
Choosing the best-fit modeling approach for marketing goals, and accounting for multiple touchpoints both online and offline, adds complexity to attribution modeling. Marketers need to understand statistical models that can properly attribute credit to different touchpoints based on their real impact on conversions. This requires analytical expertise, plus the budget for necessary data tools as marketing complexity grows.
Types of Attribution Data
Data attribution models are nothing without the data that you feed into them.
There are 2 main sources of attribution data.
1. Software-based Attribution Data
This utilizes digital tracking tools, such as analytics platforms or marketing automation software, to track and record user interactions and automatically attribute conversion actions to specific marketing touchpoints.
Pros - It provides objective and granular data on user interactions and conversions, and enables real-time tracking and analysis of customer journeys. The reliance on voluntary self-reporting and subjective recall is reduced.
Cons - Aside from missing touchpoints that are not digital or easily trackable by software, it can be complex to implement and require technical expertise. You’ll need the right tracking set up for accurate data and reliable insights, and the analytics tools.
2. Self-reported Attribution Data
This is data collected directly from your customers and leads, who share information about the touchpoints that influenced their decision-making process. It’s usually collected via an online form or survey but can also be collected in direct conversation with customer-facing staff and then recorded in a CRM.
Pros - It allows for qualitative data collection, using direct insights from the individuals themselves to capture subjective factors and nuances that software-reported attribution may miss, such as offline interactions or word-of-mouth referrals.
Cons - It relies on individuals' willingness to provide information, and their memory and perception which may not always be accurate or complete. This type of data can be more time-consuming and resource-intensive to collect and analyze.
Hybrid Attribution Data
Combining both self-reported and software-based data sources into attribution modeling is what is known as hybrid modeling. It’s the ideal solution to mitigate the drawbacks of each data type, providing the most fully comprehensive understanding of your customers journeys.
Next, depending on your marketing activity and data tracking sophistication, you’re going to have some of the following types of data sets to work with.
The best way to categorize your data inputs is to split it into channel data and event data.
1. Event Data (What Happened?)
Event data typically includes:
- Conversion Data - Conversion data includes information about the desired actions taken by users, such as purchases, form submissions, or sign-ups. Conversion goals need to be set for each journey stage.
- Behavioral Data – Any data related to customers' online behavior, such as organic website visits, page views, time spent on site, clicks, search queries, and interactions with specific content or features.
- Clickstream Data – This is a record of each click a consumer makes while browsing online. Tracking all these actions can help brands form an accurate understanding of the most effective consumer journey design.
- Ad Impressions and Clicks - Ad impressions combined with click data provides information on the number of times an ad was displayed to users, and the corresponding clicks made. This data helps gauge the effectiveness of specific ads.
- CRM and First-Party Data - This data provides long-term insights into customer behavior and can include survey responses, purchase history, and any interactions with the brand. CRM data is necessary to link the direct impact on revenue generation and CLV.
Note, there are two common ways to give credit to touchpoints within a conversion sequence: post-click, or post-view.
Post-click Conversion Data - If attribution is done on a post-click (not necessarily last-click) basis, clicked touchpoints will get a part of the conversion credit as long as the action happens within the defined lookback window.
Post-view (or view-through) Conversion Data – Here, the content a user viewed (impressions) within the specified lookback window also gets part credit for a conversion. Most of the advertisers who advertise on multiple channels will have video and social media as part of the conversion journey. These channels usually are not driving clicks, but still contribute to outcomes. This data is more challenging to accurately collect.
The lookback window is how far back a conversion action is included, usually measured in days. So a 7-day lookback window would only include advert impressions or clicks 7 days before the customer converted. In low-cost eCommerce transactions where the selling cycle is short, the most relevant lookback window only might be 7 – 14 days. Whereas for more complex sales like business software, a lookback window of 60 days could be used.
2. Channel Data (Where Did It Happen?)
Channel source data typically includes:
- Referral Data - This identifies the source that referred users to your website (or app). It can attribute from the high-level referral sources, such as search engines, social media or email, right down to the specific pieces of content.
- Device and Platform Data – This gives information about the devices and platforms used by users during their customer journey. It allows marketers to track cross-device interactions and attribute conversions across different devices. Device data is also helpful for providing location information.
- Offline Data - This gives information about customer interactions outside of digital channels, such as in-store purchases, phone calls, word of mouth, events, direct mail responses, etc. Offline data is typically captured through mechanisms like unique identifiers, coupon codes, or CRM systems.
An attribution model is essentially used to link these two types of data together to show which marketing touchpoints deliver the best results.
Types of Attribution Models
There are several types of attribution models to feed your data into. Applying the right modeling for the goal or KPI is key.
A model essentially joins up your event data (what happened) to your channel data (where it happened) to show you the most profitable journey connections.
The difference between attribution models is where they place most credit for achieving a desired conversion goal (like submitting a contact form, generating an MQL or closing a sale). Conversion goals should be set up for each stage of the customer journey to feed attribution analysis.
Multi-touch models attribute results to more than one touchpoint, allowing for the influence of consecutive touchpoints to be considered as part of a process that led to the final conversion.
A model either uses:
- Rule-based methodology - Analyzes data in a completely static approach.
- Data-driven modeling - Typically uses AI and machine learning to help automatically customize multi-touch attribution based on the influence of touchpoints.
Here’s a breakdown of the most common attribution models:
Last Touch (or Last Click) Attribution
This model assigns all the credit for a conversion to the last touchpoint (or channel) that the customer interacted with before making a purchase or completing the desired action.
When to use it? - To understand which touchpoints are most influential for prompting people to take the final step in completing a conversion goal (e.g., submitting a contact form or making a purchase).
Limitations? – Although easy to use and collect data for, it’s not a great stand-alone model for longer and more complex sales cycles where conversion still heavily relies on the preceding touchpoints, particularly in B2B.
First Touch (or First Click) Attribution
The first touchpoint (or channel) the customer engaged with receives 100% of the credit for the conversion.
When to use it? - To understand which early journey touchpoints are best at first reaching new audience members who will eventually convert.
Limitations? – It ignores the influence that mid to late journey touchpoints have for final conversion. Data accuracy can also be more difficult to assure depending on your data tracking methods and lookback window
Equal credit is given to each touchpoint in the customer journey, recognizing the role of all channels in driving conversions.
When to use it? – To understand how touchpoints and journey architecture work together to nurture conversions over time, including cross-departmental touchpoints between marketing and sales for B2B.
Limitations? – The data collection process is more intensive and may require cooperation with other departments to capture all touchpoints, taking time to implement fully. This may include qualitative touchpoints through manual data entry. Distributing credit evenly doesn’t account for which touchpoints have most influence.
Time Decay Attribution
More credit goes to touchpoints that occurred closer to the conversion event, with the assumption that recent interactions have a greater impact on the decision-making process.
When to use it? – For longer, more complex customer journeys where later touchpoints are most influential. Equally, it can be useful for very short sales cycles where decisions are made quickly and you want to see which touchpoints have immediate effect for impulse conversion.
Limitations? – The influence of earlier touchpoints for creating brand awareness or intent won’t be accounted for.
U-Shaped (Position-Based) Attribution
A higher percentage of credit goes to the first and last touchpoints in the customer journey, while the remaining credit is distributed evenly among the other touchpoints. It's based on the idea that the first and last interactions play a more significant role to create new leads and drive conversions.
When to use it? – When you want to understand which channels generate most new leads, and which drive most conversions.
Limitations? – Again, the influence of in-between touchpoints will not be fully understood, and it requires data collection to cover all touchpoints within the journey.
Equal credit goes to three key touchpoints: the first interaction, the lead creation event (e.g., form submission), and the final conversion event. The remaining credit is divided among the other touchpoints.
When to use it? – To highlight the key journey milestones from early journey, mid journey and late journey.
Limitations? – The influence of intermediary touchpoints is not fully understood
Data-driven models use advanced analytics, machine learning, or artificial intelligence to analyze customer journey data and assign credit to various touchpoints based on their estimated influence on conversions. This can be done by off-the-shelf software solutions specifically designed for marketing attribution. There are two widely accepted data-driven models for attribution: Shapley value model, and Markov chain model.
When to use it? – For more accurate full-journey attribution across multiple touchpoints, providing greater flexibility for integrating multichannel data silos and more balanced weighting criteria.
Limitations? - An attribution software subscription is required, some of which can be costly. How the algorithms are coded and applied is sometimes proprietary information that is not made fully clear or adaptable. Data sources still need to be set up and connected, including offline touchpoints. It can take months of work to fully set up and implement a data-driven model covering all marketing channels.
Fully Customized Attribution Modeling
Custom-built models are also data-driven, but can include as much complexity and adaptability as you’d like. They allow for full visibility and control of the combined data sets, rules and weighting in use. It allows the layering of many rules and granular data analysis so you can deeply understand and drive growth to a level that isn’t available any other way.
When to use it? - For larger media budgets where small adjustments see the $ results impacted by millions.
Limitations? - Fully customized attribution requires a specialist to implement because of the complicated algorithms and calculations, along specialized statistical software and coding. Like off-the-shelf data-driven solutions, it can take several months to fully implement.
Choosing Data and Models to Match Goals
For multichannel marketing across the customer lifecycle, marketers will have several different goals and KPIs, so there isn’t a one-size fits all when it comes to using attribution modeling.
For example, marketing goals will vary by campaign, but also business lifecycle stage. As a business matures and can afford to allocate more budget in demand creation, longer payback periods become feasible in the name of sustainable growth.
For the most accurate results, several rules and weighting criteria may need to be layered together. This requires an understanding of how to choose the most appropriate combination for each goal or data set.
Here are examples of how different goals could affect the overall approach for assessing attribution against KPIs:
Brand Awareness - The main objective is to build familiarity rather than immediate conversions, so attribution models that consider upper-funnel touchpoints using a longer lookback window are most helpful.
Conversion Rate Optimization - Last touch attribution can provide insights into the most influential touchpoints in driving conversions for any journey stage.
Customer Acquisition – With a focus on identifying marketing efforts that drive most new customers, attribution models that emphasize first touch and last touch before sale conversion are a good fit.
Customer Retention and CLV - Attribution models that consider multiple touchpoints over the customer lifecycle are best. Time-based attribution models such as linear or time-decay attribution can help identify touchpoints that contribute to CLV over time.
Cost Efficiency - Attribution modeling using cost-per-click (CPC) or cost-per-acquisition (CPA) data provides insights into the cost of acquiring customers through different channels.
Channel Optimization - Models like time-decay attribution or position-based attribution can help evaluate the effectiveness of various channels throughout the customer journey.
Return on Ad Spend (ROAS) - Attribution that uses revenue conversion data along with position-based or data-driven models are most suitable for calculating ROAS. These models can help isolate the impact of an advertising campaign against other touchpoints.
Customer Engagement - Attribution models fed with click data are most valuable. Models like engagement-based attribution or position-based attribution can help attribute credit to touchpoints that generate higher engagement levels.
Campaign or Event Success - Campaign-based attribution or event-based attribution allow marketers to filter conversion data specifically for the corresponding campaign (or event) identifier.
Demographic Targeting - Companies that target audience segments based on demographic data, such as geography, need to be able to filter customer event data for segment-based attribution.
Social Media Influence - Models using multi-touch attribution with social media weighting can help more accurately attribute conversions or engagements specifically to social channels.
Experimentation with attribution models will help you find the most suitable approach for each reporting use case.
A Step-by-Step Guide to Building Custom Attribution Models
A customized approach to attribution modeling allows hybrid data usage to give the most complete and accurate view of your marketing effectiveness. (Reminder - a hybrid approach combines multiple online and offline data sources, reducing the risk of misleading insights).
With customized approaches, you can get journey clarity at the individual level. For example, you could isolate a new customer to see that their first website visit was 9 months ago, and they were exposed to 37 ads across 5 platforms. You can also use heat map tools to confirm how channels work together in order to predict where prospects will go next, targeting content messaging accordingly.
Here are the 6 steps to create custom attribution reporting that will truly allow you to start optimizing your marketing investments:
Step 1 - Clearly Define Your Goals
Identify the specific objectives that your marketing efforts aim to achieve, such as increasing conversions, driving brand awareness, or improving customer retention. They can be different for each channel or audience segment. As discussed, these goals will guide the rule options for your attribution model.
For each goal, decide what you consider to be a conversion for the journey stages, and whether you will need to include post-view data in addition to post-click data. The type of conversion is important, so you’ll want to identify the conversion events to look at for each specific goal, including the lookback window that will be most relevant.
Attributing marketing activity to revenue is the ultimate aim – this will give you the most powerful information to improve ROI and drive growth.
Step 2 - Identify All Your Data Sources
Start with accurately and consistently collecting all the data you possibly can for all customer interactions across all your active channels and platforms. You’ll need to UTM tag every link that matters, and have tracking pixels installed for all active marketing platforms.
Here’s a quick checklist of data sources:
- Social media (organic)
- Paid media campaigns
- Email marketing
- CRM system and revenue data
- Customer feedback
- Call tracking
- Offline touchpoints
- Third-party data providers
- Self-reported attribution is most valuable when free text only.
- B2B buying decisions usually involve multiple people, so it’s better to track the customer journey at the account level instead by combining individual user data.
Step 3 - Bring in the Necessary Data Capabilities
Marketers need to have a deep understanding of marketing concepts and principles to be able to set up effective attribution models and make data-driven decisions.
You will need access to strong data analysis skills to be able to set up, manage and interpret the data for customized attribution models. Some technical knowledge is required to select, set up and configure attribution software tools, integrating them with existing data sources and systems. Knowledge of statistics is also necessary to understand, interpret and communicate the results of attribution models.
If in-house attribution data specialists are not in budget (or available), It can be more economical to use specialized data agencies to support you.
Step 4 - Chose + Activate Your Data Tools
Available resources are a big part of your consideration here. You’ll need to consider what is within means for your company in terms of ease of use, data integration capabilities and subscription cost.
There are 2 options here:
- Off-the-shelf attribution software
There are several software tools available that can help marketers combine marketing attribution data from different sources.
Tools with in-built machine learning and AI are better suited to help you analyze and weigh the contribution of different touchpoints and channels in your custom hybrid attribution model. This will give you more accurate insights.
Google Analytics (or Campaign Manager 360) are the best known off-the-shelf providers. However, data integration from other sources can be much more of a challenge with GA. Some other off-the-shelf options which offer better data integration capabilities include Northbeam, Wisely, Adobe Analytics and Improvado.
However, the drawbacks are that you’re still handing over power to a platform that uses its own proprietary algorithms, not always allowing complete visibility or flexibility in how rules are applied or data is weighted.
- Build your own custom modeling
Depending on your resources, building custom modeling offers the greatest control and visibility of exactly how data is being weighted and analyzed for each scenario.
If you’re doing this independently, you’ll need a data connector/warehouse solution to import and store your data from across your multichannel data sources. Custom coding and statistical tools can be utilized for advanced capabilities, allowing for layered algorithms and models tailored to any specific need or data set, including fully customized weighting criteria for data sets such as self-reported attribution.
The benefits over any other solution is the most accurate attribution possible, with completely granular insights depending on any criteria you’d like, allowing complete flexibility as variables such as channels, campaigns and customer or market dynamic shifts, and fully aligned for any goal you set.
With customized approaches, you can get journey clarity at the individual level. For example, you could isolate a new customer to see that their first website visit was 9 months ago, and they were exposed to 37 ads across 5 platforms. You can also use heat map tools to confirm how channels work together in order to predict where prospects will go next, targeting content messaging accordingly.
Step 5 - Integrate Your Data Sources
Using your selected attribution tools, start collecting and integrating data from your multichannel sources.
This involves setting up data integrations between the attribution software and the data sources, whether through configuring API connections (recommended) or importing data files.
Automate the most relevant model-based analysis into dashboards, reporting on each of your specific marketing goals whether by revenue, channel, journey stage, customer segment, etc.
Step 6 - Test and Iterate
Continuously test and refine your attribution model, adjusting the weights and methodologies as necessary. Monitor the performance of your model and make data-driven adjustments to improve its accuracy and effectiveness over time.
For example, data capture often relies on UTM tags, which requires links to be clicked before they are reported. This means some early-journey channels that rely on impressions rather than clicks (mainly social media and display advertising) will be underrepresented without qualitative self-reported data and weighting adjustments. Lift tests need to be run to help assess weighting criteria.
To test the influence of unclicked impressions, which is common for early-journey touchpoints and channels, you can use lift tests. Lift tests use test and control groups, only showing adverts to the test group. The difference in conversions between the two groups is known as lift, indicating the channel's real impact, and providing a helpful weighting metric. (Audience sample size and segment characteristics are important for statistically valid comparisons.)
Incrementality is a complementary metric to lift.
The Main Takeaways
Marketing attribution is critical to understand the impact of different touchpoints on customer behavior and conversions.
While various simplistic attribution models exist, building customized data-driven models provides marketers with the greatest control and insight accuracy for their attribution analysis. This is essential to ramp up marketing spend with certainty of generating the required revenue results.
Custom data-driven attribution models offer several advantages over on-platform and Google Analytics reporting:
1. Report Against Goals - Marketers can tailor custom models to their specific business goals, customer behavior patterns, and available data sources. This level of customization enables a more accurate reflection of the complexities of the customer journey and the unique dynamics of the market.
2. Understand Touchpoint Influence Across Whole Journeys - Custom data-driven models empower marketers to attribute credit to touchpoints based on their true contribution to conversions, rather than relying on predefined rules or assumptions. And by integrating multiple (hybrid) data sources that include online and offline interactions, marketers can operate with a significant competitive advantage to drive growth forwards.
3. Allow Flexibility For Refinement - Custom models also provide the flexibility to adapt and refine the attribution process as the business evolves. You can more easily incorporate new data sources, update algorithms, and fine-tune attribution rules to ensure the model remains aligned with changing market dynamics and marketing activities.
Implementing a custom data-driven attribution model requires robust data integration and advanced analytical capabilities. However, the benefits of improved accuracy, granular insights, and informed decision-making make the investment worthwhile, potentially adding millions of dollars of additional annual growth. Particularly where larger advertising budgets are involved.
By leveraging the power of custom attribution modeling, marketers can achieve industry-leading business outcomes.
If you need any support scoping, setting up or managing your attribution analytics, the team at Half Past Nine are here to help. We live and breathe marketing data! Just reach out.
What To Read Next:
- The New Era of Personalization Explained; A Guide to Building Profitable Customer Journeys With Digital Intent Signals
- Marketing Data Visualization To Fully Leverage Your Sources of Truth
- Switching to First-Party Data: It’s Time to Stop ‘Renting’ and Start Owning Customer Data
Imagine a future where paid media actually adds real and welcomed value in people’s lives.
Where the information someone needs appears at exactly the right time to help them find what they want. Or while they’re browsing, learn about something that they weren’t aware could solve a pressing need.
And in the process, brands spend less money putting content in front of people who don’t want or need it, radically driving up the profitability of media spend to deliver maximized revenue growth.
This future is possible, even without third-party cookies. It will be built on a mindset shift, where the rigid parameters of the sales funnel are no longer paramount, and dynamic customer journeys become the north star.
Where as marketers, we can cater to real people who don’t behave in linear ways, with empathetic understanding of what their goals might be and providing real value when it’s wanted.
If your goal is to improve customer engagement and fuel new revenue growth, this article is for you. Let’s explore how to build highly profitable customer journeys using digital intent signals.
Building Personalized Customer Journey Architecture
Our job as marketers is to get the right touchpoints and messaging in the right place to progress our prospects from first introduction to converted and loyal customers.
The basics of the customer journey remain the same under the tried-and-true framework of Awareness > Interest > Consideration > Decision > Retention > Advocacy.
The 3 journey stages for customer acquisition are:
- Early Journey (creating awareness)
- Mid Journey (nurturing interest and consideration)
- Late journey (prompting action)
However, customers can move through buying stages in very different timelines. They may regularly loop back to previous stages, with pauses in-between. In our digital era, journeys can be incredibly fragmented across devices and platforms, and many journeys are completely unique.
The typical customer journey today is actually a 3-dimensional process that can shift in any direction, rather than a straight line from A to B. They can resemble pyramids, diamonds, or even hourglasses, rather than a linear funnel.
A linear sales-funnel philosophy fits with the old approach of the stereotypical sales-led company. It’s not that a sales-led approach isn’t right for any business - but an overemphasis on sales goals can cause counterproductive tactics. For example, immediately jumping to harassing prospects with unwanted phone calls or emails, or running a generic sales ad to the widest audience possible and having to pay above average CPM/CPC due to poor engagement.
That’s why the most successful approach to fueling revenue growth is a dynamic and responsive customer journey framework, rather than a funnel approach.
It allows for the individual to engage with relevant content while on their own unique path, maximizing the number of conversion routes and potentials at any one point in time.
Naturally, the simplicity (or complexity) of a typical journey will vary greatly by the value and importance of the purchase being made.
For ecommerce brands, a customer could leap from awareness to an impulse purchase in the space of 5 minutes in the right circumstances. Or a B2B sale could take many months from initial touchpoint. (Learn more about the B2B customer journey and buying process.)
Regardless of journey timeframes, marketers building any type of customer journey architecture will still need to understand:
- What are the common challenges, needs, goals, and desires of each audience segment?
- What channels and platforms have best reach for the target audience at the specific journey stages?
- What corresponding messages will work best for each journey stage and platform?
- How do cross-channel and platform touchpoints work together to facilitate complete journeys for each segment?
Learning to Read Behavioral “Tells”
How can brands really get to grip with personalization across platforms?
Firstly by recognizing that the old way of building a sales funnel - assuming everyone who enters it will behave the same way - doesn’t reflect reality. We can’t assume that all people in a target market will be relevant leads, use the same platforms, automatically be ready to consider buying after showing interest, or that their consideration process will always follow the same path.
It’s the equivalent of walking up to a colleague in the middle of a phone call and expecting them to answer your question immediately. Or approaching someone perusing the vegan section of a store to offer them a promotional ham sample, then continuing to follow them around after they’ve said “No thank you”.
The need for observation, active listening and empathy applies as much to marketing and sales activity as it does anywhere else in life.
That’s where intent data comes in. Intent data is the marketers means of observing what people are doing, before we “decide” if and how to approach them.
Using intent data to target users will outperform targeting by demographics alone. Users who show intent are typically closer to making a buying decision, making them high-quality leads. By targeting these users, businesses can increase the likelihood of conversions to generate quicker and higher ROI.
And the more digital and mobile customers have become, the more helpful intent data they generate for us. Of course, it still depends on a brand’s ability to manage and analyze the data… But with a solid data strategy, brands can tap into intent data to engineer hockey-stick moments of sustainable growth.
Introducing Digital Intent Signals
Just like in life offline, the key is to observe people’s “body language” within their digital world, building a picture of what might be happening for them in the moment.
We call these digital actions “intent signals”.
Being able to read them allows us to connect with only the most relevant people, using tailored messages that are most likely to resonate in that particular moment.
The majority of buyer journeys start with some type of intent. Although…, your ideal prospects might not always start out directly looking for your type of solution or product.
For example, a person Googles healthy meal recipes. Their goal is to improve their nutrition and lose weight. They aren’t looking for complete nutrition shakes. But if we were to reach the user with content highlighting the quick and easy benefits of complete nutrition shakes to improve health and lose weight, we’re far more likely to capture their attention and create intent to buy.
These types of people with relevant but indirect intent may represent a large portion of your serviceable/addressable market.
Demand is much easier to create with the right message that talks to a pressing goal, at the exact time a person has that goal front of mind. It’s always the goal we need to understand and talk to.
And to be clear, intent signals aren’t KPIs or “vanity metrics”. We use intent signals to deduce intent, and then target or exclude people accordingly. Intent signals should actively inform real-time content targeting when used correctly.
Types of Digital Intent Signals
The intent signals we can gather spans internal and external sources. It crosses organic and paid content, to owned and third-party platforms.
- First-party Data – CRM, website, app and email data (learn more about first-party data)
- Second-party Data – Audience interaction on non-owned channels (E.g. Facebook)
- Third-party Data – Data Companies (E.g. Nielsen)
Some signals can be very overt. Especially at late journey stages, such as filling out a contact form or adding an item to the basket. Whereas other signals are less obvious, like running a Google search to learn about a related topic, or following a competitor’s social media account.
The type of intent signal can give you clues about a person's journey stage to build real-time customer segments. It’s helpful to identify which intent signals feature most prominently at each stage of your brand’s customer journey paths.
Split targeted signals up according to the campaign goals they fit with, whether that's demand capture (late journey) or demand creation (early journey) campaign goals.
For example, if a website visitor is behaving like a user that typically converts after another couple of weeks, you can target them with the right tone of nurturing content accordingly. But if you were targeting someone showing an interest in a competitor that hadn’t been included in your campaigns previously, you could show them content that introduces your brand with the comparative benefits of your brand/product/solution over the competitors.
Here are the most common intent signals that can be tracked:
- Reading or viewing content related to specific products or services.
- Downloading or sharing content.
- Commenting on or liking blog posts or social media content.
- Subscribing to a blog, newsletter, or YouTube channel.
- Searching relevant keywords.
- Searching for reviews or comparisons related to a product or service.
- Searching for the brand name or specific products.
Social Media Engagement:
- Following or liking a brand's social media pages.
- Engaging with posts by liking, commenting, or sharing.
- Mentioning the brand in posts or comments.
- Clicking on social media ads or sponsored content
- Clicking on digital ads.
- Video ads watch time.
- Clicking on retargeting ads
- Registering for webinars or online events.
- Participating in trade shows or conferences.
- Engaging in live Q&A sessions or forums.
- Traffic source
- Visiting a website multiple times (yours or competitors).
- Spending a significant amount of time on the site or on specific pages.
- Checking product pages or service descriptions.
- Downloading content such as ebooks, whitepapers, or product brochures.
- Returning to the website after a period of inactivity.
- Using online tools, calculators, or configurators.
- Completing quizzes or self-assessments.
- App downloads.
- App usage patterns and content engagement.
- Search queries.
- Abandoned carts.
- Registration or subscription.
- User reviews and ratings.
- Adding items to a shopping cart or wishlist.
- Repeatedly viewing a specific product or service.
- Starting but not completing a purchase process.
- Checking the availability or location of a product.
- Opening marketing emails.
- Clicking on email links.
- Responding to surveys or filling out forms.
- Forwarding emails.
Customer Support Interaction:
- Contacting sales.
- Using live chat or chatbots.
- Requesting a demo, quote, or more information.
How to Use Digital Intent Signals to Inform Customer Journey Architecture
The process for incorporating intent signals into real-time, personalized media targeting requires the following steps:
Data Collection and Analysis
The first step is to collect data on your audience’s behavior across your channels, including offline touchpoints where possible.
This data needs to be analyzed to identify patterns and understand what specific actions might indicate a user's intent to purchase or engage further. What are the main actions taken within journeys, and what conversion goals can help you qualify people at each stage?
Data tools such as connectors and warehouses will help you merge data from multichannel sources for more holistic understanding and analytical power, whether historical or predictive.
A note here on data collection. User tracking and targeting across multiple advertising platforms can be achieved through more than one method. This means that what a user does on one platform can be used to target them appropriately with relevant content on another platform via:
- First-party Data - Advertisers can import their customer segments into an advertising platform using Customer Match targeting. This matches identifying information that customers have shared with the advertiser, such as an email address, to target specific ads to those customers, and also other people that behave like them (look-alike audiences). This allows advertisers to narrow in on the highest intent/value customers.
- Cross-device Targeting - Also known as people-based marketing, this approach uses Device IDs or User IDs to anonymize user data while still allowing people to be targeted individually (without cookies), so advertisers can track and target a user across multiple devices. Pixels are used for this type of targeting.
A combination of these data collection methods will give brands the most precise targeting power and best results.
Once you've identified key intent signals and conversion goals, you can segment your audience based on their behavior.
For instance, users who have abandoned their shopping carts might be in one segment, while users who have spent a significant amount of time on product pages might be in another.
Each segment will have different needs and will be at different stages of the customer journey.
Create personalized paid and organic content for each segment, addressing their specific goals or challenges, guiding them towards the next step in their journey with defined conversion goals for qualifying. Content that matches keywords and the audience’s language directly performs best.
Leverage Media Technology + Automation Tools
There are a number of built in AI and automation tools within the bigger ad platforms for marketers to take advantage of.
Setting campaign goals and conversion goals allow platforms like Google and Meta to automatically optimize targeting to achieve them. Dynamic ads can use AI and machine learning to improve their targeting and optimize ad copy tailored exactly to user search terms. And machine learning already drives real-time programmatic buying, where advertising inventory is bought and sold via an instantaneous auction.
There are various independent solutions that can be used for paid media targeting, such Blueshift and 6sense, including intent data for account-based marketing (ABM) needs.
Testing and Optimization
It's important to continually split test and optimize your campaign creatives and targeting based on performance.
Look at which intent signals are most predictive of conversion, and which types of content are most effective for each segment. Use this information to refine your targeting and personalization strategies. How you use attribution modeling is also a crucial part of your media optimization process.
Recognizing and leveraging customer intent signals in the creation of personalized customer journeys is not just a valuable strategy - it's a business imperative for advertisers seeking to drive revenue growth.
As the advertising landscape becomes increasingly digital and competitive, the brands that will rise to the top are those that truly understand their customers, meeting them where they are and providing what they need at every stage of the journey. By harnessing the power of customer intent signals, marketers can enhance customer experiences, build stronger relationships, and ultimately, achieve sustainable revenue growth.
This shift towards a more customer-centric approach rooted in data insights is not just the future of advertising; it is the present.
If your team needs support gathering, analyzing and incorporating intent signal data into your media strategy, Half Past Nine would love nothing more than to help you realize their transformative power on your bottom line. It’s what we get out of bed for! Just get in touch.
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