6 Growth Tactics for Marketing In a Recession: Lessons From 2008
Are we in recession? Is stagflation setting in? How much worse is it going to get? Should you still be advertising in a recession?
Good news. Economic dips don't mean brands need to experience a corresponding contraction. You could even strengthen your business to reach new heights, if equipped with the right knowledge and growth mindset.
Cycles in the economy are nothing new. There are brands that come out on top every single time. Almost any situation offers opportunities if you can identify and respond to them. Ultimately, marketing is not a cost, it’s an essential operating investment.
So unless your business is nearing the point of collapse, firmly push your CFO’s hand away from the nuclear button. Give them reassurance that your business is going to get through any challenges just fine, if you collectively keep your heads and play it smart. No short-sighted and damaging knee-jerk reactions.
Here’s what you need to know about marketing in a recession. I’ve included plenty of great examples from brands that proved the case in point during the financial crisis (aka The Great Recession, December 2007 - June 2009).
What Happens When Brands Reduce Marketing Budget?
Drastically cutting off the marketing budget should only ever be an option if it’s literally a matter of company survival. Why?
- Customer Bleed - Less brand visibility and engagement with existing customers and potential sales leads puts you out of mind. Apart from any particularly loyal customers or financially unaffected target segments you may have, customers are quick to switch to competitors that are marketing to their current needs. For example, it was found that up to 75% of consumers tried new brands during the pandemic. Any savings you make cutting marketing budget is likely to be outstripped by a loss of customers switching to other brands. B2B projects or contracts last longer, but new projects, scope extensions or contract renewals could decrease as a result.
- Market Share Costs More to Recoup Later - Your brand's share of voice and mind, brand equity and market share all depend on sustained marketing activity. A 2022 study found that most brands are already under-spending on marketing, depressing their ROIs by a median of 50%. Additional media cuts on budgets that are already proportionally low will be disproportionately counter productive as a result. Given that more advertising competition during growth periods drives up CPC and CPM prices, it would require increased spending to build back to previous ROI levels after activity is paused. (ROAS and brand awareness always have a lag period.)
- Long-term Growth Contraction - Research found that brands going ‘off-air’ can expect to lose 2% of their long-term revenue each quarter. And a 2018 research study found that stopping advertising for a year resulted in sales revenue declining by 16% on average, compounded to a 25% decline after 2 years. The effect hit smaller firms hardest. When media efforts resume, it takes around 3-5 years to recover the resulting equity losses. So to summarize, any short-term underinvestment in marketing can put your brand at a longer-term disadvantage that won’t financially balance out.
On the other hand, your brand stands to benefit if you maintain brand awareness.
- Increased Market Share + Revenue: Brands that keep advertising during recession can see up to 5% increases in market share. Translated to sales, businesses that advertise aggressively during recession have seen sales 256% higher than those that ceased advertising. Growing a successful brand in a declining market is actually easier than growing it in a very competitive one, which is why so many of today’s big brands successfully launched during recessions.
- Greater Brand Visibility For Less - A number of companies (who haven’t read this article) will pull back on marketing investment during a recession. This reduction in competition drives down ad placement costs. It means brands still advertising can quickly gain share of voice for the same investment. This is where share of voice exceeds the corresponding share of market. In the 2008 recession, advertising expenditure dropped by 13% yet statistics showed 3.5x more brand visibility for companies and organizations that maintained their marketing output. Excess Share of Voice (ESOV) is the name for this key metric where you stand to gain ground.
However, that’s not to say you should just continue as is and expect to maintain or improve your results. On the contrary.
A 2010 study of how businesses performed during the financial crisis found that 9% had come out in even better shape than before. The businesses that did best had deployed a mix of tactics to reduce costs while still investing in growth strategies best suited to the recession and post-recession periods. Firms that dramatically cut back on everything performed the worst.
Looking specifically at marketing spend, you should be looking at ways to trim unnecessary fat and make your budget work more effectively, for greater ROAS and overall marketing ROI. This may require some mix of budget reallocation, shifts in audience targeting and redefined messaging.
We’ll spend the rest of this article looking at exactly what that means, giving you inspiration for how your brand can approach recession marketing for growth.
The Primary Challenge Is Changing Customer Behavior
When it comes to marketing in a recession, your fundamental challenge is changing customer behavior. Recessions trigger a scarcity mindset which alters buying behaviors. Demand could contract but often shifts to different places; it’s not that spending always stops but rather the way money is spent that changes.
That typically includes:
- Limiting discretionary purchases or postponing projects.
- Shifting to cheaper or more cost-effective alternatives.
- Seeking more utility.
- Seeking out promotions and spending more in value channels.
If customer behavior is changing, your marketing approach also needs to change accordingly. Your marketing strategies need to meet customers where they are and where they want to be.
Analyze how your particular customer segments respond to recession.
- How is customer purchasing behavior changing?
- Are your customers purchasing other alternatives instead?
- What are the main trends of reasoning and decision-making behind any purchasing changes?
- Are any new customer segments opening up to you based on your brand’s offering and competitive positioning?
Sufficiently understanding this is the key to everything else we’re about to cover in terms of adjusting tactics.
1. Leverage Martech + Analytics
Use your available MarTech tools and resources to develop insights from two perspectives:
- Looking externally to your customers + market
- Looking internally to your own team + organization
Customer + Market Insights
Explore how to cost-effectively gather customer data to answer the questions above. That includes:
- First-party customer data collected in your CRM system.
- Campaign reporting data.
- Social listening tools.
- Customer survey tools.
- Third-party research and data sources.
- Media, government or industry-body reporting.
- Your competitors' activity.
Internal Marketing Insights
You can’t fully anticipate what will come next so your strategies need to be fluid. Agility is key. As is selling the value of marketing to C-suite and the board.
To help you improve efficiency, responsiveness and make savings where justified:
- Optimize Your Processes - Identify where you can improve processes and the use of MarTech. That includes creating, executing and analyzing all deliverables to improve results with less time invested. Each team member’s focus should be dedicated where it makes the most impact. Ensure time isn’t wasted such as on unnecessary team calls or unsuited tasks outwith primary skill sets.
- Improve Visibility On Full-funnel ROI - To optimize spending, you need to know where to invest more and what to cut out. Tie marketing investments to real business outcomes that are measurable so you can reallocate money to the biggest sources of return. Don’t forget that early journey targeting feeds bottom of the funnel supply - a balance needs to be maintained for sustainability. Optimize channel usage and touchpoints for a full customer journey.
- Improve Analytics Automation - Following on from the two points above, the right MarTech and automation set up will afford more team capacity and campaign optimization with real-time insights. Immediately pull money from campaigns or speculative activity that aren’t yielding adequate results for short-term requirements.
- Leverage Your First-party Data - Crucial for 2023 is the imperative to remove any reliance on third-party cookies to gather audience insights. User privacy updates mean they will become redundant in 2023. If you haven’t already, get a customer data collection strategy in place as a priority. Your first-party customer data should help you generate useful insights on authenticated users while keeping legislation and user privacy top-of-mind.
- Reevaluate Agency Support - External marketing partners can offer the right specialized skills and manpower as your needs fluctuate. A great agency will help your brand stay ahead of the curve. Work with your agencies to improve ROI visibility and prune unnecessary costs. Depending on the agency, you may need your own mechanisms to confirm that adequate value is being delivered. However, if you’re left wondering where the ROI is, that’s telling. It’s up to you if you want to take responsibility for driving improved value from the relationship, or consider other options. Just ensure you’re giving an agency the inputs and clarity they’re requesting first, not frequently changing goal posts or being too vague. (Feel free to give Half Past Nine a holler if you’re in this situation - demonstrable ROI is our method and track record!)
- Encourage Innovation - Challenge and necessity is often the driver for smarter solutions. Reducing waste can free up budget or time to allow your team more capacity to innovate. Innovation leads to competitive advantages that will long outlast a recession period and permanently increase market share. Focus on value for your customers based on their challenges, especially while times are tougher.
B2B Example: SAP
Used customer insights to deeper penetrate SME as a growth segment and feed 13% revenue growth in 2008
SAP responded to the economic situation in 2008 by adopting a range of cost cutting and investment strategies to come out with 13% revenue growth. They “intensified” their marketing activity and boosted their sales and marketing headcount by 29% over the year.
Their investment strategies were built on robust insight data. They built deep customer and market insights for a volume business model targeting SME audiences’ needs as a growth segment to expand into.
“We intend to widen the market we address with more attractive offerings for our customers including, for example, new data analysis and decision support solutions for business users, and software solutions scaled to small businesses and midsize companies.”
- The SAP Business ByDesign solution was used to open up a new segment of smaller businesses with between 100 and 500 employees with distinctly different software needs: “Getting their new IT solution running quickly, at minimum risk and predictable cost, is often more important for these customers than specific functional depth. Many such companies do not believe that their needs can be met by traditional software offerings or by the available on-demand solutions.”
- Over 4,200 customers signed contracts for SAP Enterprise Support services when the service was launched in February 2008: “The growing complexity of business processes, the growing SAP solution portfolio and the success of SOAs are leaving traditional support models behind, because today’s customers require more than a fault-fixing and maintenance service.”
- SAP partnered with HP and IBM to market preconfigured, preinstalled, and tested SAP Business All-in-One solutions on HP and IBM technology, bundled in a fast-start program. It was designed for midsize companies in the manufacturing, service, and retail industries, “which need a highly interoperable solution with plenty of functional reach”. The number of midsize companies using SAP Business All-in-One solutions grew 21% to 13,450.
SAP also heavily targeted industries they identified to have greater growth potential: “In 2008, we focused on strategic industries with exceptional growth potential, including, for example, banking, retail, communications, and the public sector.”
B2C Example: Walmart
Leveraged customer insights to achieve the highest sales growth of any competing retailer in 2008
During the 2008 recession, Walmart’s analytics highlighted that consumers were:
- Browsing less to reduce impulse purchasing.
- Less brand loyal, substituting for budget brands.
- Purchasing from cheaper categories (more pasta, less meat).
- Purchasing more from home entertainment and health categories rather than going out.
In response, Walmart upped their marketing spend to $2B (up from $1.9B in 2007), focusing on ‘take and bake’ advertising campaigns and promoted offers on home entertainment products. This allowed Walmart to grow 2008 net sales by 8.6% YOY - a record for any retailer that year.
2. Clarify Your Brand Positioning + Customer Targeting
Your task is to reevaluate your brand positioning in the eyes of:
- Your existing customers.
- Potential new customer segments based on changed purchasing criteria (aka, the switchers).
It costs less to keep a customer than to win a new one, so start by considering your brand positioning in the eyes of existing customers. Relationship building must be sustained, centered around the evolving needs and priorities of your customers.
This needs to fit with your brand’s unique value proposition within your competitive niche, considering the other options that customers have in front of them and why they should keep choosing you.
Segment your high-value customers out and make their needs your first priority. Each high-value customer segment might be affected in different ways. Don’t assume that all are negatively impacted by recession.
Focus on product or service strategies that increase the perceived value of your offering with a focus on long-term satisfaction. The greater the perceived value, the less likely your products or offering is to be cut.
List out the key needs and challenges for each segment and your corresponding value propositions. Include the value you already offer, and any additional value you will now incorporate in response to customers' recession challenges. Identify where you add value above your competitors.
Recessions are an opportune moment to assess which new customer segments may be opening up to you.
These segments will help mitigate any losses from existing customers who might be trading down or postponing purchasing. Diversifying also helps buffer you against shocks in individual segments, whether from the supply or demand side.
Identify who the switcher segments are and what value propositions will attract them to buy from you. For example, better customer service, your product/offering lasts longer, or replaces multiple other solutions in one lower cost.
Switchers can either be:
- Moving down a price bracket.
- Pressed to find more utility/ROI than a previous product/provider was supplying.
- For B2B, may have new requirements if they too are targeting new segments and verticals.
You may need to shake up your use of distribution channels to access these new segments.
But if you can attract these switchers, you have the opportunity to prove your value and retain their loyalty after recession passes, fueling greater long-term growth.
B2B Example: Salesforce
Majored on cost-saving brand positioning to acquire 14,400 new customers in 2009
Salesforce is a SaaS pioneer that took the business model mainstream. Their market position was perfectly pitched for the recession: “When credit is tight, big invoices for hardware, software and data centers defy logic and consume precious capital and increase risk.”
Key growth objectives during the recession period were to invest in a quality product promoted via effective account management and GTM strategies, including:
- Deeper relationships with existing customers for greater LTV:
- “As the customer realizes the benefits of our service, we try to sell more subscriptions by targeting additional functional areas and business units within the customer organization and pursuing enterprise-wide deployments.”
- “...by continuously enhancing the functionality of our service, we believe that customers will find more uses for our service and therefore purchase additional subscriptions, continue to renew their existing subscriptions, and upgrade to more fully-featured versions, such as our Unlimited Edition.”
- “Aggressively” pursuing new customers and territories with expanded targeting and the use of local partners:
- “We have created several editions of our service to address the distinct requirements of businesses of different sizes.”
- “We seek to extend our leadership position in this industry by continuing to innovate and bringing new application and platform services and value-added technologies to market, as well as by providing the tools needed by third parties to develop their own SaaS applications on our platform.”
- “We plan to continue to aggressively market to customers outside of North America by recruiting local sales and support professionals, building partnerships that help us add customers in these regions and by increasing the number of languages that our service supports.
The combination of a quality product with lower cost of ownership was a no-brainer for many businesses. Salesforce went from $749M sales revenue in 2008 to $1,077M in 2009. They acquired around 14,400 new customers during that year.
B2C Example: TJ Maxx
Educated a wider audience about off-price retail through advertising to drive 7% revenue growth in 2009
During the financial crash, T.J.Maxx increased its advertising spending by 15% as part of a strategy to target new customers affected by the downturn.
They believed that customers had fundamentally shifted their priorities towards better value, using value-based messaging that attracted customers from all income brackets. “Our marketing campaigns are stepping out and educating consumers about off-price.”
“In the tough economic environment of 2009, we were one of the few retailers to invest significantly in marketing and enhancing our customers’ shopping experience, and we will continue to prioritize investments to drive customer traffic in 2010.”
TJX Companies 2009 Annual Report
The proof is in the pudding. In 2009, 75% of TJ Maxx shoppers were new customers and retail sales grew 7% YOY.
3. Adapt Messaging + Tone
The messaging and accompanying tone of voice you use should be formed around the strategies built after going through the processes above.
Messaging is the combination of your customers needs with your corresponding value propositions. That means focusing on benefits over features or capabilities.
Recession messaging should speak to the psychological and decision-making elements that are driving your selected customer segments. The value your brand offers in response needs to be made clear.
For each distinct customer segment, you are aiming for no more than a few strapline messages, ideally one line each.
These will act as taglines and guide subsequent content development. You can plan key moments on a customer journey where these messages should be used and elaborated upon further, shaping out your content strategy.
Here are a few more elements to consider when crafting your segmented messages:
- Is Changed Messaging or Tone Actually Required? - Any high-value segments who are able to continue with business as normal may not require updated messaging. Messaging should be tightly focussed to a customer's current needs - not pointing at the unnecessary.
- Value + Benefits Over Features - A key part of successful recession messaging is conveying the value of your offerings, focusing on the benefits and outcomes delivered rather than just the specifications or capabilities. You are first speaking to the needs that you resolve. This is always best practice, but check in if you can better match your value propositions to any recession challenges your customers are currently experiencing.
- Helpfulness + Empathy - Account for the realities your audience is facing and share anything your company is (actually) doing to make things better, such as sponsorships. Develop solutions or longer-form content that offers genuine and practical value in helping steer customers through their specific challenges (being careful not to patronize customers). Empathy may be beneficial or even necessary depending on your target audience and the challenges they face. Nine in ten US consumers want brands to show empathy through their behavior, and 86% said showing empathy is critical to fostering loyalty.
- Values + Vision - If applicable for your offering, incorporate inspirational messaging around values and vision to stand out. This offers greater value for customers equally aligned, generating loyalty. Research found Americans prioritize companies that are responsible (86%), caring (85%), advocate for issues (81%), protect the environment (79%), and give to important causes (73%). Storytelling is a powerful way to back up values messaging, translating it to your actions and impact. But be authentic - not every brand needs to try and convey deeper values to meet their audiences’ needs.
- Warmth + Humor - Where appropriate, feel-good warmth or humor can be more human, relatable and memorable. The aim is to lift spirits, offering comfort and reassurance. Humor in advertising has been found to be more expressive (+27 point increase), more involving (+14) and more distinct (+11), significantly enhancing attention and positive effect. However, do be highly considered in how, where and when you use humor. The danger is humor backfiring if interpreted as insensitive. Depending on your brand, it may only be appropriate for a limited number of content pieces and platforms.
- Pricing - Do you want price to be part of your value proposition messaging? This should only really apply for discount brands unless you’re running a targeted promotion. Read the following section on pricing strategy to better understand if you want to incorporate it at tagline level.
A quick note here on authenticity and sensitivity when it comes to your messaging. Use adequate customer insights, and impact-led activity or features to match any claims you make. Don’t run the risk of being perceived as insensitive, misleading (lying), or manipulatively virtue-signaling for PR purposes. Brands that get this wrong do more harm than good. No brand wants to find itself on the wrong side of cancel-culture.
B2B Example: IBM
Used campaign messaging around a better vision for the future to galvanize record-breaking sales across multiple verticals
“Many companies are reacting to the current global downturn by drastically curtailing spending and investment, even in areas that are important to their future. We are taking a different approach.”
“In other words, we will not simply ride out the storm. Rather, we will take a long-term view, and go on offense. Throughout our history, during periods of disruption and global change, this is what IBM has done. Again and again, we have played a leadership role. We have imagined what the world might be, and actually built it.”
The key elements of IBM’s “transformation” during the recession period included:
- A continuing shift to higher value businesses.
- Investing for growth in the emerging markets.
- Global integration.
- Investing in innovation.
- Ongoing productivity resulting in higher profit margins.
IBM aligned their external messaging by launching their visionary ‘Smarter Planet’ global marketing campaign in 2008. The messaging spoke to a wider need for change as businesses and governments around the world looked to drive greater efficiencies and responsiveness. In IBM’s view, the global economy “created a mandate for business change” that required an intelligent and connected digital network built for the future. There was a pressing opportunity to upgrade global infrastructure through embedded information technology. Their messaging covered multiple key sectors, including smarter cities, smarter power grids, smarter food systems, smarter water, smarter healthcare, smarter traffic systems, smarter airports, and smarter supply chains.
In 2008, IBM’s revenue went up 5% to a record $103.6 billion.
B2C Example: Starbucks
Reestablished their brand as the best quality coffee on the market, driving them back into growth
During the 2008 recession, more than 900 Starbucks stores closed as American consumers turned to cost-effective alternatives like McDonald’s.
In response, Starbucks launched the largest marketing campaign they’d done called “coffee value and values,” designed to reassert the quality of their product and reassure consumers it was worth the cost.
They removed marketing gimmicks that had diluted their brand identity and stripped right back to the core value proposition of their brand - better quality coffee. Ad strapline messaging included:
- Beware a cheaper cup of coffee. It comes with a price.
- Starbucks or nothing. Because compromise leaves a really bad aftertaste.
- If your coffee isn’t perfect, we’ll make it over. If it’s still not perfect, you must not be in a Starbucks.
4. Review Your Pricing Strategy
More customers will be predisposed to seek out reduced prices and promotions during recession.
Does that mean you should or need to lower prices? Not necessarily. A reduction in prices is a long-term strategy, not a short-term fix.
Dropping prices can generate more sales in the short-term, albeit at lower margins. However, any new customers who chose you based on lowered prices may quickly switch away again if the price increases. Also consider any impact this would have on the perceived value of your product against the needs and resources of customers. For example, those in more affluent areas or verticals may not be driven to purchase because of reduced prices.
Unless your business needs the sales boost for survival, reducing prices is only a strong strategy if you plan to sustainably maintain them there based on your current and projected costs. For example, under a planned price skimming or penetration pricing strategy.
The same goes for promotions, which done continually could reposition your brand as a discount brand and condition consumers to only buy on promotion. Consider your margins against the additional sales volume generated and whether this is a suitable longer-term positioning tactic to attract target customer segments.
If you are shifting your pricing in either direction then explain to your customers why, bringing it back to their needs.
An alternative to price shifting is a loyalty program, or discretionary discounts for B2B brands. Selectively target loyal customers who deliver high lifetime value (LTV) and profitably reward them, not devaluing your brand in the process. For example, 62% of firms with loyalty programs said it helped retain customers during the pandemic. B2B brands could also introduce referral bonuses to incentivize new client introductions through personal networks.
B2C brands can incorporate more timing sensitivity around seasonality, such as earlier seasonal promotions to spread out associated costs over longer periods.
Additionally, brands could offer non-exploitative financing or longer payment plan options where possible.
B2B Example: Mailchimp
Launched a free subscription targeting small businesses to feed a pipeline of future customers
Mailchimp is an email platform that was initially focused on large corporate clients on yearly retainers. They didn’t even offer a free trial. However when the Great Recession hit, Mailchimp found their growth stagnating and also wanted to help smaller, struggling businesses.
Mailchimp decided to introduce a free tier to their price plans in 2009. With a limit of 2,000 contacts and a daily send limit of 2,000 emails, it massively took off. The move introduced a wave of small and medium-sized businesses to the Mailchimp platform that wouldn’t otherwise have been part of their customer base. They went from tens of thousands of users to a million in the first year, fueling their growth for years to come.
Mailchimp was able to demonstrate its value and retain these new users, moving them onto premium subscriptions as they grew. Among the customer community, requiring a move up to paid subscription became like a badge of honor as a growth milestone.
B2C Example: Hyundai
Offered a car take-back scheme to grow sales despite consumer fears of unemployment
In 2008, Hyundai managed to grow global revenue by 5% and market share by 4.7% despite an incredibly tough year for the auto industry.
They did this by not just delivering new and better quality car models at lower price points. They also reduced the risk for buyers by offering to take back cars that were financed or leased if the owner lost their job. In 2009, a finance rebate was also offered to buyers of some Hyundai models, for up to $333 a month for six months.
These groundbreaking measures empathized with struggling customers within their core target demographic, helping to build trust, confidence and maintain sales despite fears of unemployment. It was a huge publicity win generating goodwill towards Hyundai, and other companies were inspired to follow suit due to the success of the program.
Hyundai reported that its U.S. sales were up 14% in January 2009 compared to the same month a year earlier, all while the U.S. auto market fell 37%.
5. Evaluate Your Stock Holding, Products Or Offering
Certain product categories or offerings may take a hit to their bottom line. Your lead-gen budget (separate from your brand campaigns budget) should be focused on promoting categories that will offer most value and return during the recession period.
Take this timely opportunity to permanently prune out poor performers, unless they can be profitably adapted to deliver new benefits or target new segments’ long-term needs.
Keep your eye on the long-term. Invest in areas where you can outdo your rivals under the current conditions, or where you have an edge to get ahead for the recovery period. This includes R+D or product development if applicable to your brand, and your distribution channels. If you can anticipate where demand will be next quarter, prepare accordingly, especially where you have an international supply chain. Naturally, make sure any risks are carefully considered and don’t have the potential to be life-threatening to your business.
A key note here though. Building competencies or product features is a long-term strategy, so make sure the customers needs you are evolving to meet are equally long-term.
For B2C CPG, review your product catalog against sales performance during previous recessions to understand what products did well. You could add to these categories for more recession mileage. Essential or value categories are likely to do best, although people will still buy from non-essential categories too but perhaps favoring budget-friendly options. If applicable for your target segment (where pricing is valued over in-store or brand experiences) stick to the basics and minimize nice-to-haves to preserve cash flow.
B2B Example: Shopify
Shifted their product offering and invested in innovation to tap into an unmet market need
Shopify made a fundamental pivot between 2006 and 2009 that not everyone might be aware of. Shopify started life in 2004 as a Canadian snowboard ecommerce site. However, the founders decided to build their own ecommerce platform when they couldn’t buy a satisfactory CMS product. They launched the platform in 2006.
Growth was slow in 2007, until they made a significant change in their pricing strategy. Instead of charging transaction fees as a percentage of sales, they switched to a subscription-based plan and tacked on a small transaction fee that decreased as plan size increased. They also dived deeper into product development, building new value-added features that helped customers sell more, such as built-in analytics tools. They now had an affordable and easy-to-use solution that aligned with customers' needs. They became profitable in 2008 and continued to invest in their product throughout the recession period, launching the Shopify API in 2009.
Bravely deciding to go after a market gap resulted in a highly compelling and valuable product. Shopify successfully built an ecommerce platform for the needs of an emerging ecommerce retailer segment - many of whom were sole traders starting up after redundancy. They were fundamental in fueling an ecommerce sector as we know it today by providing recession-friendly value for small businesses and startups.
(IBM is another great example of successful pivoting in a changing market, shifting from a PC manufacturer to an IT consultancy.)
B2C Example: Amazon
Continued to invest in innovative initiatives for bringing customers more product choice at lower costs
In the 2008 recession, Amazon grew its sales by a staggering 28%.
They did this through continued product innovation rather than pulling back on investments, launching new products such as Kindle 2 that made books more affordable for readers. This move was a risk at the time but as we know helped grow their market share significantly, resulting in customers buying more ebooks than printed books by 2009.
In 2007, Fulfillment by Amazon (FBA) was launched as a service to attract more third-party sellers. Amazon provides warehousing within their global fulfillment network, and a ‘pick, pack, and ship’ service on the sellers’ behalf. FBA items are eligible for Amazon Prime and Super Saver Shipping as if the items were Amazon inventory. In the fourth quarter of 2008, Amazon shipped more than 3 million units on behalf of FBA sellers.
These product and offering shifts reflect the dynamic, “customer obsessed” and long-term thinking that Jeff Bezos is legendary for. His opening statement for the 2008 Amazon.com Annual Report is worth a quick read. Here are a few gems:
- “Seek instant gratification – or the elusive promise of it – and chances are you’ll find a crowd there ahead of you. Long-term orientation interacts well with customer obsession. If we can identify a customer need and if we can further develop conviction that that need is meaningful and durable, our approach permits us to work patiently for multiple years to deliver a solution.”
- “Working backwards from customer needs often demands that we acquire new competencies and exercise new muscles, never mind how uncomfortable and awkward-feeling those first steps might be.”
- “In our retail business, we have strong conviction that customers value low prices, vast selection, and fast, convenient delivery and that these needs will remain stable over time. It is difficult for us to imagine that ten years from now, customers will want higher prices, less selection, or slower delivery. Our belief in the durability of these pillars is what gives us the confidence required to invest in strengthening them. We know that the energy we put in now will continue to pay dividends well into the future.”
Amazon was another company that increased their marketing investment during the period, with increased spending across marketing channels, including their Associates program and sponsored search.
Also a quick note here on the cash operating cycle, which Amazon also offers a master class in. “Because of our model we are able to turn our inventory quickly and have a cash-generating operating cycle. On average our high inventory velocity means we generally collect from our customers before our payments to suppliers come due.”
- Learn more about how the Cash Conversion Cycle can drive growth for your retail business.
6. Adjust Media + Channel Investments
Adjusting your paid campaigns will quickly show you the effectiveness of updated targeting, positioning and messaging. You can test adjustments and variables for instantaneous feedback using engagement and conversion KPIs.
Set up campaigns properly for full KPI visibility so you can pull campaigns that don’t deliver against their individual objectives. Whether that’s to build brand awareness and intent in a new segment, or generate more sales/leads rapidly.
If you are in a position to target unimpacted segments and verticals, you may wish to allocate more of your ad budget there for the short-term. Assuming this doesn’t put you at a significant disadvantage for the rebound by ignoring key verticals for your business. Your paid audience targeting should continue to match your offering and brand positioning for key segment variables such as geo-location.
As covered earlier, recession offers the opportunity to buy more ad placements for less as other companies cut spending, offering the potential to capture excess share of voice. But bear in mind the advertising lag phenomenon, meaning you’ll often have to maintain consistent campaign activity for a minimum period of time in order to reap the rewards.
Synced cross-channel campaign delivery will amplify frequency and brand awareness, increasing your budget efficiency and conversion rates.
Profile and test new ad platforms, especially if your strategy involves targeting new segments. The performance of individual platforms is not necessarily dictated by the number of users or the CPC/CPM. If a platform successfully brings you high quality leads in sufficient volume, you can achieve higher ROAS and customer LTV regardless of the higher costs. Testing is the only way to find out.
You may not want to pull investment from poorer converting channels and platforms entirely. Consider first if they form a crucial point on valuable customers’ journeys that helps prime them for the point of conversion on another platform later. Data shows that the most effective advertising campaigns spend around 60% of budget on brand-building (or brand awareness) advertising, and only 40% on short-term activations.
Developing a clearer view of successful customer journeys will help you make more profitable campaign investment decisions. Identify existing and new consumer journeys so you can target the moments that influence purchase decisions most. This includes any shift in keywords that drive conversions for your website. Referring back to first-party data, use it to test new tactics that deliver more personalized interaction with customers and prospects at any stage of the journey. Ensure you have adequate data capture and analytics capability to support you in achieving this.
The targeting, timing and cadence of your content promotion should be in tune with customer purchasing cycles as much as possible. Work to understand and collect behavioral signals that can be used for content personalization based on the customer journey and lifecycle stages. Get in front of your customers just ahead of the times they are most likely to make a repeat purchase, or a contract is coming up for renewal.
For B2C brands, POS marketing from signage to packaging and placement are included in your promotional strategy. Ensure you update these to match any shifts in your customer behavior and updated strategy.
As part of your innovation and testing process, get creative with how you maintain overall channel visibility. Leverage organic methods more heavily where possible. Examples include:
- Trial new content formats and unique creatives within your organic channel strategies.
- PR stunts, especially driven by community altruism.
- New marketing partnerships or distribution channels that expand your reach.
- Better keyword targeting for recession-driven searches.
- More valuable or helpful content for customer's recession challenges.
B2B Example: Cisco
Cisco used new digital media channels and innovative campaign creatives to drive more audience engagement
Cisco’s R+D and sales + marketing budgets were both upped in 2008 as the company doubled down on its strategic investments. Cisco’s use of social platforms and creative media experimentation expanded in 2008.
The Human Network Effect campaign was launched in 2008, at the same time an ABI Research poll found that Cisco was seen as ‘boring but trustworthy’. Through the year, Cisco pioneered early digital marketing activity, harnessing the growing power of social media. They experimented with digital media formats using more human-oriented, optimistic and humorous content.
For example, the launch of a new series of routers incorporated the use of a campaign microsite featuring satirical videos where Santa Claus and the Easter Bunny solved their problems with the new router. It used a social share function, and posted the videos on popular platforms at the time including YouTube, Yahoo Video, Google Video and Veoh. Cisco also used a social media press release, a Facebook application and group, plus a widget featuring videos, collateral and images that could be embedded on social media pages.
The result? Cisco’s growth trend didn’t miss a beat in 2008, with revenue growth across all product categories and geographies. Revenue was up to a record $39.5 billion, an impressive 13% YOY increase.
Cisco Systems, Inc. 2008 Annual Report
B2C Example: Coca-Cola
Coca-Cola introduced innovative digital content formats to re-engage their core target audience and reverse a sales slump
Coca-Cola experimented with its paid media and creative strategy during 2008 and 2009. A number of innovative campaigns leveraged multichannel tactics at a time when digital marketing was still in its earlier stages.
A full-length TV commercial on the theme of video games was designed to target their core audience, supported by integrated digital seeding, gaming and social media campaigns. It was promoted on popular video sharing websites with banners and links to exclusive content including wallpapers, Instant Messenger icons and ringtones of the ‘You Give A Little Love’ soundtrack.
Their global ‘Open Happiness’ campaign launched in January 2009, encouraging recession-weary consumers to enjoy the simple pleasures in life. The campaign was heavily invested in and went beyond the traditional marketing tactics, with distribution across platforms including Twitter, Facebook, Bebo and YouTube. It made accompanying music videos by some of the top pop singers, ran competitions and gave away millions of ’Happy Prizes’ based on the most popular rewards on the brand’s loyalty website ‘Coke Zone’. They also used attention-grabbing tactics such as the ‘Happiness Truck’, ‘Happiness Vending Machines’ and the ‘Hug Machine’.
Coca-Cola reported a 5% increase in revenue in 2008, and a 17% increase in 2009.
To reiterate, don’t panic. Recession is unlikely to last that long once it’s officially been declared. There are a plethora of tactics to get your business through it in reasonable if not even better shape. There’s an available response to help remediate most situations. And you’ll find countless other articles and research enforcing these same messages about how to successfully navigate recession.
The basics of right audience, right message, right price, right product, right channel and right time are more crucial than ever. One or more of these elements are likely to require adjustment.
Key tools in your marketing toolbox are:
- First-party customer data and behavioral insights.
- Analytics tools used with greater cohesion and automation.
- Clear customer segmentation.
- Reframed messaging around enhanced value and benefits.
- Purchasing data from previous recessions (first or third-party).
- Personalized and localized content messaging tuned into purchasing cycles.
- Appropriate rewards or discounts for your valuable customer segments.
- Ad budget and campaign consistency to fully assess + realize results.
- Cross-channel experimentation and syncing.
Need advanced support to build your cross-channel strategy, marketing intelligence infrastructure or paid media campaign delivery during recession? Reach out to the team at Half Past Nine anytime.
What to read next
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.
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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