How to Create Fans by Turning Your Customers into Believers
Exploring viral marketing tactics to scale your brand?
Whether you’re looking to scale a DTC, B2C or B2B business, the fundamental principles of virally growing your customer base are the same.
Marketing legend Seth Godin coined the term ‘Sneezers’ in his book ‘Unleashing the Ideavirus’. The book was published back in 2001 and the main principles still hold true.
Sneezers is the label Seth chose for people who are easiest to captivate with your ideas in order to spread them virally. He says to give away your best stuff for free, even paying the right people if necessary, and your ‘idea' will spread. In essence, it’s about the decline of interruption marketing and the rise of online word-of-mouth marketing. You can read the free PDF copy of the book available on Seth’s blog (putting his principle into action!).
I think the metaphor of sneezing contagious viruses is one we’d all rather avoid at present, although it’s certainly a sticky concept that’s easy to understand. I’ll reframe it in a slightly different light and talk about ‘brand believers’ rather than sneezers. I think brand believers are actually closer to the truth, because you are converting people who want to share your great offering, versus creating an unconscious host.
The aim is to go beyond basic brand awareness and convert an audience into brand believers, aka fans. The benefits are two-fold:
1. More Cost-Efficient Marketing - Believers will proactively spread the good message to people within their personal networks. Word-of-mouth (WOM) marketing is far more cost-effective and influential than any other type of marketing.
2. Greater Customer Loyalty - Believers are incredibly loyal by nature, and with increased loyalty comes less customer churn and higher Lifetime Value (LTV). Improving customer LTV to Customer Acquisition Cost (CAC) ratio is the enlightened aim of any brand that’s building for sustainable growth.
The pay-off for your efforts comes from positive differentiation in brand believers’ behavior. Brand believers will:
- Keep coming back to purchase again, even if alternative or cheaper products or services might be available.
- Engage with and share your content on their preferred platforms.
- Enthusiastically talk about your brand with other people when the opportunity arises.
- Write great reviews if you ask them to.
- Create influential user-generated content for you.
Here are practical steps that can help you a) create loyal brand believers, and b) mobilize them into evangelizing more new customers!
How to Create Brand Believers
Believers are followers. The goal is to build something that they truly want to follow. This is achieved via a great product that nails an audience niche, combined with a solid brand identity for which your target audience feels:
- Values-based alignment.
1. Pick a Core Target Audience Most Likely To Become the First Believers
Your first step is to reach a highly targeted audience of the right people who will get your brand values or unique product and be advocates for you. These are trendsetters who can reach and wield influence over a wider audience.
They might be the people most underserved or impacted by a previous gap in the market, have larger than average relevant social or professional networks, or be dedicated content creators, influencers and media publications within your niche.
Seth refers to a very targeted audience as a hive.
Start by identifying your group of potential early adopters by describing the ideal persona in specific detail. Find where people who match these characteristics tend to congregate online most. Follow what they say and how they share content. Hashtags can be a useful tool for reaching them with your own content depending on the platform. Start courting them consistently.
Make sure the targeted early adopters have a positive experience. Or perhaps even recruit them as a trusted test group to help you get your delivery right first, with free products or demos and some kind of incentive if necessary. Aim to give something before you get something.
Once this influential group is converted to brand believers, they’ll willingly share with their followers, friends or associates. We’ll look at how you can support that process by providing a framework to amplify word-of-mouth sharing shortly.
2. Create a Brand Identity That Serves Your Audience’s Needs and Values
More than just creating interesting ideas, what really converts a believer is powerful messaging underpinned by resonating values which connect to deeper emotional needs.
A strong brand identity that fulfills an audience's personal needs with aligned values will create brand believers. When customers feel connected to a brand, 57% will increase their spending, and 76% will buy from them over a competitor.
Pick the most common combination of emotional and value-based drivers for your core target audience in relation to your specific offering. Then, consistently appeal to and appease these needs though both your marketing content and product offering. This mix is the basic recipe for creating believers - you can imagine it like a good stock as the base for everything else you add.
Here are some examples of audience needs and values you could appeal to and offer solutions for.
Examples of emotional (or psychological) needs:
- I need to feel connected to family and friends
- I need to feel worthy
- I need to feel love
- I need to feel safe and secure
- I need to rest and relax
- I need to take care of people I love
- I need to create a better world around me
- I need to express myself
- I need my body to feel comfortable
- I need to feel accepted and validated
- I need to feel in control
- I need to feel connected to nature
- I need to be entertained
- I need to have fun
- I need to explore and discover new things
- I need to feel happy
- I need to have a purpose
- I need to improve myself
- I need to feel fulfilled
Examples of personal values:
- I am on trend and have great taste
- I am intelligent / knowledgeable
- I work hard and do my best
- I care about helping other people
- I do my job better than other people
- It’s important that I look my best
- My personal time is important to me
- I am a good person
- I care about the environment
- My mental health is a priority
- I need to have the newest and best things
- I make my business profitable
- I am humorous
- I am powerful and influential
- My work efficiency is important
- I keep my home looking the best it can
- I deserve great experiences
- I provide well for my family
- I am a trendsetter
Focus groups and surveys could be a helpful means of exploring the most common combinations for your audience, whether formal or informal, offline or online.
After you identify the combinations of values and underlying needs that you can utilize most effectively to influence your customers, you then need to build your brand identity around that. Perhaps you can even inspire people to have new values-led aspirations with this depth of audience understanding, widening your potential audience.
Your marketing content is how you go about communicating your brand identity - content is the vehicle to reach and attract believers. Subsequently, your product or service user experience can create fully converted believers who start promoting your offering for you.
Treat your content as an equally important product alongside whatever your business offers, and a necessary USP for creating believers. Make your brand identity and main brand messages as unique as you can. Get familiar with your competitors so you can achieve that. Believers need a leader they can get behind - not another follower!
- Learn how to flip your brand into a media company with a solid content strategy.
3. Get Your Offering Right To Maintain Faith
Marketing content is your primary tool for building and communicating brand identity, although a brand identity is tangible and goes deeper than content. Your product or service offering needs to be worthy of your target audience’s attention and expectations. If you don’t genuinely satisfy the practical need that you’re promising to, you’ll create indignant critics rather than believers.
Make your offering and supporting customer service as good as it can be. It should be consistent and trustworthy. Create a great user experience, and go further for your customers.
Your brand identity actually provides the guiding principles to be embodied throughout your organization, actualized in the offering you provide. Word about inauthenticity spreads like wildfire on the internet, so don’t be dishonest. There are no shortcuts to long-term, sustainable growth when it comes to gaining trust and maintaining customer loyalty.
Factor your staff into the equation, because they too can act as influential believers who spread the good word and reinforce your customers' trust. You really don’t want it to turn vice versa where staff regularly become critics and work against your messaging. Treat them as well as your customers.
If you’re still working on fine-tuning your offering, it’s possible to use a linear commerce model to start building your audience and testing your content or product with them before you go to full launch.
4. Own and Maximize the Customer Lifecycle
Your customer lifecycle depends on your offering, naturally. You could be selling yoga leggings, luxury hand soap, software or a consultancy service. Payment models, upselling and repeat purchasing cycles vary widely and form the basis of your unique customer lifecycle. Customer lifecycles feed into the wider lifecycle of your business relevance.
There are a number of steps to go through, from winning new customers to advocacy, and evolving with your audience’s needs:
- Own your audience data with first-party tactics by getting permission for direct marketing.
- Keep testing content for format, messaging and communication style to optimize engagement across distinct stages of the customer lifecycle.
- Create relevant offers or benefits for repeat customers, rewarding loyalty and keeping them in a purchasing cycle. Check out Starbucks and TOMS for some rewards UX inspo.
- Interact with customers, gather feedback and update market research to adapt your content and offering as necessary.
Establishing a direct and permanent chain of communication with the people you reach is the most important factor in owning and maximizing your lifecycle. Getting followers for your social media accounts is great, getting email addresses is even better. You’ll be able to enhance delivery of personalized brand messaging depending on an individual’s position in the customer lifecycle.
Remember to give something before you get something when you are asking people to give you their personal information.
Mobilize Your Brand Believers Into a Growing Community
The feeling of community is a powerful driver to tap into; 55% of surveyed consumers said they want brands to help connect like-minded people with each other, and 36% are actively looking for communities they can belong to.
Word-of-mouth marketing (WOM) is your go-to tool for effectively achieving this, and it's the same as old-fashioned word of mouth except it’s shared online.
We can break WOM into organic and amplified:
- Organic - Brand believers become advocates naturally because they are impressed with your business and your offering - 92% of people trust recommendations from friends and family over any other advertising or marketing.
- Amplified - You design marketing campaigns to encourage WOM in existing or new communities - 88% of people trust online reviews written by other customers as much as recommendations from people they know.
Seth insightfully points out that people are self-organized into groups (or hives) that have several things in common, usually including a way to communicate among themselves, spoken or unspoken standards, a common history or challenge, and organic leaders.
To build a community, you’ll need a minimum viable population, communication channels, and supporting content that elicits emotional responses. Emotional responses can range from light-hearted to more deeply felt.
Although you are the trigger for the establishment of your brand believer community, it will ultimately be enabled and ruled by them. Aim to encourage and facilitate advocacy rather than attempting to force it, because you can’t! Once it gathers sufficient momentum, you’ll be able to use a lighter touch to keep it going.
I’ve got several tips for how to go about this.
1. Listen and Interact To Build Relationships
The best place to start with building a community of believers is to meet - and hopefully even exceed - your fans’ brand UX expectations.
Choose several communication channels to reach as much of your audience as you can using their preferred platforms where they hang out. There are tools to help you find your audience, such as Combin for Instagram, which can find followers by hashtag or location, target accounts that liked and commented on relevant posts, or search for accounts following your competitors.
Provide regular content within these platforms that can be easily shared, and use the relevant hashtags that your audience follows. Content should be engaging enough to keep followers coming back for more. Say genuinely interesting things, and minimize anything overtly self-promotional that will feel one-sided or too self-interested in your audience’s eyes. Stay on brand with your topical remit and tone of voice, and don’t go anywhere unnecessarily controversial.
Mix up your media formats to refine what works best, repurposing content for preferred communication styles. Include low-investment calls to action that get your followers interacting with your brand in fun or rewarding ways, such as:
- Quizzes or instant-result surveys, including polls for your next piece of insights content
- Subscriber notifications for new and exclusive gated insights, exclusive access to podcasts or sub-branded newsletters
- Opportunity to give input and feedback on product development
- Offers on partner deals (e.g. buy two wedding rings for 50% off a wedding planner consultation)
Be responsive to followers' comments, and comment when followers share your posts or tag you! Listening and engaging not only makes potential believers feel appreciated and trusting, but will also help you get to grips with the content that believers like best. Hire a social community manager if necessary. Take your followers’ constructive feedback on board and action where viable. (Not that you need to submit to every customer whim of course, or ignore a larger audience to please a small one.)
2. Create a Brand Messaging Bible for Believers
Give your customers memorable brand messaging to share by crafting a captivating narrative about your brand, and incorporate those messages into shareable content. This messaging will be built on your brand identity, which you have tailored to your believers needs and values, reflecting and validating their own identity.
Spreading the word should feel effortless. Give brand believers the words and content they need without having to think so they can convert more like-minded followers for you with minimal effort. Keep repeating the values-based words and the emotional energy you want people to use when describing your brand. Make content shareable on social platforms with one click, or make it super easy and quick to sign up for an affiliate program.
Use media publishers to help get messages out. Discuss what kind of stories or interviews they would be interested in publishing, pitch newsworthy stories whenever you can, or alternatively use promoted editorial options.
Demonstrate your values in action or choose a cause. People like to show their support for causes their community believe in, raising their own credibility and influence by association. For example, FIGS is a medical clothing manufacturer that donates scrubs to healthcare professionals who work in resource-poor countries. They also donate a ‘Future Icons Grant’. It’s gotten them positive organic coverage from media titles including Forbes, helping spread their values-led brand messaging. Or you can check out the YouTube video entries for the Future Icons Grant using #figsfutureiconsgrant. It's a very inspired use of both a cause and user-generated content!
3. Encourage and Share User-generated Content (UGC)
Content generated by brand believers can be more powerful; 85% of people are more influenced by UGC than brand content.
Social channels are the most natural place for UGC to help improve your organic WOM reach. The goal is for happy customers to share pictures of your product or mention your business positively. You can help this process by creating your own hashtag for people to talk about your brand. Interact with followers who mention your brand, and share their content on your brand's channels to amplify momentum.
Creating an ambassador program like Lulu Lemon's can help boost positive UGC. You can also proactively target the best-known influencers in your niche. Reach out and offer to send them your products for free to decide if they’d like to provide a review. A unique discount code that they can share with their followers will help sway them in favor. Well-known influencers may require payment, but you can try!
4. Ask for and Display Customer Reviews
BrightLocal’s Local Customer Review Survey 2020 found that the average consumer reads 10 reviews before feeling able to trust a business. That’s more than in previous years, up from 6 reviews required in 2016.
Ask people to submit a review after buying a product, providing links to where you’d like them to submit their review. Run a temporary reward campaign for completed reviews if you need a boost, with a small discount or something complimentary as the incentive.
Prominently feature (real) reviews in as many places as possible, like your website, in-store, social media accounts or Google business listing, and anywhere relevant. You can also ask for formal feedback quotes or a case study endorsement when you finish a project, perfect for featuring on your website as part of your ‘evergreen' content.
Negative reviews can happen, whether that’s the result of your staff or a customer having an off day. A couple of negative reviews are unlikely to have much impact among a positive majority, so don’t stress too much over an occasional low rating.
5. Reward Loyal Believers Who Bring New Converts
Reward people who bring you new customers, whether they are a high profile influencer or not. An official referral or affiliate program can work very effectively. Blackbaud offers a prime B2B example. Promote your program to your existing followers and customers.
Rewards could include anything from:
- A product or service discount for the customer and the person they refer
- A gift card for referring a certain number of people
- A bonus gift
- A fixed or commission based referral fee
- An invitation to a VIP customer event, like drinks & canapes with a famous business speaker
Before you decide on any rewards, make sure you know your customers’ average lifetime value. You can’t give a reward of $50 if your average customer only has a LTV of $50. Reward programs lend themselves better to businesses that see high customer retention, like a subscription service in some form.
6. Consider a Dedicated Community Platform
When your following of brand believers is big enough, adequately engaged and willing to come to you, it may be time to consider a dedicated community building platform. Tribe is an example of the popular community building platforms out there, or Mighty Networks.
A community platform is ideal for creating a safe and secure online space that’s dedicated to your brand only. Although social media sites are great for building brand awareness, and Facebook facilitates dedicated groups with admin powers, social platforms are noisy and it can be harder to retain attention. A space where your members can easily interact with each other and engage with personalized content will create an exclusive network that feels more intimate and valuable.
Articulate a captivating reason for members to join, and make it worth their time to engage with each other and with your brand. Your community platform can be plugged into your website with a linked login area. Replicate the look and feel of your brand in your community space, and create areas or tags for specific types of content, or information your subscribed customers might typically be seeking. Enable multiple types of notifications to alert members when there is new content to keep them coming back.
Following on from the previous suggestions above in the first step for mobilizing brand believers, you could also provide:
- Access to VIP promotions for subscribers only.
- Front-of-the-line access for new or limited edition releases.
- A regular member spotlight feature, such as “influencer of the month” to recognize top contributors and give them free exposure for their own business or social profile.
- Test new products on members before launch by providing free product samples, and allow your believers to interact with the product development team.
- Provide a knowledge forum for members to seek advice from each other. Try creating live polls so everyone can see how the rest of the community is handling a specific challenge, or their opinion on a particular topic.
- Track and reward the fans who invite their friends to join your contest or make purchases.
- Live streams events.
Again, consider if you might benefit from a social community manager. However, with the right space, believers themselves may organically begin taking over some group building activities and answering questions for other members.
To Sum Up
If the content, audience building and community management aspects seem time consuming or expensive, bear in mind what you stand to gain. A strong foundation of brand believers supporting you will mean that your marketing costs drop in the longer term as organic WOM takes over and reduces your need to provide amplification. It won’t happen overnight, but it will be worth it!
If you need some support exploring what’s possible for your brand, feel free to get in touch with us at Half Past Nine. Creating outstanding brand and media strategies is our passion, backed up with exceptional data leadership and infrastructure expertise. Where could a better resourced growth strategy take your brand?
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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.
Case Study: Introducing Custom Attribution Modeling for a 23% Increase in Closed Sales
Over the last year, Half Past Nine has supported a B2B client that wanted to better understand the impact of their marketing activities in order to optimize results.
They originally used on-platform ad attribution alongside Google Analytics to track results, however noticed some discrepancies between what customers told them during sales and onboarding conversations. They weren’t sure exactly how results were differing, or how revenue was impacted.
The goal was to integrate all data sources to better understand their cross-channel results and more impactfully optimize budget allocation. Particularly for paid media, where monthly spend exceeded $300,000.
Through the process of building customized attribution, the client was able to increase closed-won accounts by 23% within a year, resulting in an additional $26M ARR.
Here’s what achieved those results:
1. Hybrid Data Collection Set Up
The first step was to introduce hybrid data collection with a “How did you hear about us?” required free-text field on form submissions on the website (excluding newsletter sign-up). Free-text submissions were then reviewed regularly to group them into themes, allocating one or more categories depending on the number of touchpoints mentioned.
All content touchpoints were reviewed, mapped against the clients audience segments by journey stages, and UTM tagging was inserted where missing.
In addition, we utilized first-party data integration between the client’s CRM and their active advertising platforms to increase the visibility of interactions for known prospects.
2. Custom Model Reporting Set Up
Half Past Nine activated a data warehouse tool with integrations for all available data sources (including closed deal value), and built a custom model for the client that could attribute influence for specific campaign goals.
The model included weighting for missing touchpoints from self-reported responses after they had been categorized. Lift tests were also run for paid media brand awareness campaigns on social media.
3. Adjusted Budget Allocation
New attribution showed significantly more high-intent leads and conversions coming from social media after interacting with staff's individual LinkedIn profiles, and a podcast channel. These touchpoints had previously been missing from the attribution completely.
The end result was the clarity to shift budget allocation to optimize the touchpoints that resulted in most conversions:
- More support for personnel to create thought leadership content for their own LinkedIn accounts.
- Newly allocated promotional budget for the podcast channel.
- Optimization of ABM and paid social campaign performance.
- Less focus on organic SEO as a lead generation mechanism.
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
The Ultimate Attribution Playbook in 2023
A Guide to Building Profitable Customer Journeys With Digital Intent Signals
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.
Case Study: Implementing Digital Intent Signals for 52% Revenue Growth
Half Past Nine recently worked with a new ecommerce client that wanted to differentiate itself by delivering more relevant and seamless customer-focused experiences across mobile apps and search.
Together, we went through the process of devising and implementing a media strategy for personalized experiences based on individual intent.
The result was a 52% increase in revenue growth within 6 months.
Here’s what achieved those results:
1. Understanding What Isn’t Working
Firstly, examining what wasn't working to fix any foundational issues that needed to be resolved.
For example, some mobile experiences needed to be optimized, and KPI analysis revealed that several of the existing paid media campaigns weren't profitable despite being within budget.
Analyzing the existing touchpoints through the lens of what customers wouldn’t want meant that the client could improve the relevance of landing pages, ad messaging, and simplify the checkout process.
The end result was:
- Improved page load times to less than one second.
- Matched advert and landing page content to users keywords.
- Implementation of Google SmartLock to streamline the login and check out process for repeat visits.
2. Work Backwards From the End Goals
The goal was for the customer to feel like the hero in their own story, building creatives that positioned the client as the sidekick to help them get to where they wanted to be.
To ensure that every interaction was relevant and memorable required an understanding of consumer intent, and capacity to respond to it in real time.
- A segmentation strategy was built using real-time behaviors. Utilizing website insights allowed visitor segmentation based on the pages and content visitors had looked at, qualifying users for mid/late journey retargeting campaigns using product-based ads.
- The use of impression pixels allowed all historic touchpoints to be tracked at the individual user level, illuminating how campaigns could be optimized for journeys most likely to convert.
- A cross-channel approach for nurturing was introduced, using search ads as the first touchpoint, followed up with a video campaign. A set of 15-second and 30-second video ads targeted users who had searched with relevant keywords and clicked, allowing the client to only target videos at qualified users.
- Combined with message/creative testing for each segment and channel, the ROAS on all campaigns became profitable, hitting new benchmark ROI targets that had been put in place.
Importantly, the use of intent signals allowed us to minimize the budget that the client would have spent on continuing to target the wrong users.
3. Look Deeper Than Third-party Ad Platform Metrics
Reassessing KPI usage and introducing dashboards for data visualization was a crucial part of evolving the client’s ability to improve campaign performance. This was supported with custom attribution modeling to really understand what was driving conversions by segment, looking beyond last-click to minimize misattribution.
A deeper understanding of customer lifetime value (CLV) by audience segment allowed the client to make more strategic campaign investments. People who ordered via the client’s app had a higher CLV, allowing a shift in campaign targeting and budget allocation to improve profitability. This helped to attract more of the right customers, maintain engagement and boost customer retention.
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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