Revenue is a top priority for any business, no matter how big, no matter how small. It’s fundamental: without money coming in, you’ll have nothing to cover overheads or invest back into the company.
We all know that a hard-working sales team is key for bringing in new business and increasing revenue. But revenue is increasingly a priority for marketing teams too.
Many marketers turn to ROI (return on investment) to determine the profitability of a promotional campaign. In fact, more than 40% of marketers claim their main priority in 2021 is to “better measure the ROI of [their] demand generation initiatives”.
It makes sense: effective marketing should achieve a healthy return on investment (ROI) and generate new revenue. A portion of this can then be invested back into marketing campaigns to keep bringing in more money, and so on. It’s a cycle of profitability that can help businesses grow and grow.
And revenue attribution can help you create more effective, successful marketing campaigns. But what does it mean and involve?
In this article, we’ll explore everything you need to know about revenue attribution and how it relates to improving marketing ROI.
What is revenue attribution?
Revenue attribution (also known as marketing attribution) is a reporting process that involves matching revenue brought in, to a specific marketing output.
For example, you might utilize revenue attribution techniques to monitor the impact that a particular piece of thought leadership content made on sales within two months of its publication. Or you may prefer to track the effect that a new series of videos made on revenue over a shorter or longer period.
Businesses have more channels — and more opportunities — to reach consumers than ever with targeted marketing campaigns. But it’s unbelievably competitive and marketing teams must take advantage of real creativity to make an impact, especially in the most crowded sectors or niches.
Employing revenue attribution techniques empowers marketers to hone in on their most effective work and understand how they can keep refining their techniques over time.
Why is revenue attribution important and how can it help?
Revenue attribution is crucial for marketing teams who want to gain a clear insight into their strategies’ value and learn how they affect customer engagement. Fortunately, there’s a wealth of data available online to help marketers build an accurate overview of campaign performance and ROI.
Identifying how specific campaigns and strategies have been received by audiences (target and/or general) enables you to make more informed, calculated decisions on future campaigns.
You’ll have a tighter grasp on what works, what doesn’t, and what elements should be combined to cultivate the most impactful marketing campaigns. You’ll be able to capture more leads, close more sales, and improve ROI thanks to continued analysis.
Another key benefit is that revenue attribution helps businesses (particularly those in their infancy or experiencing financial challenges) get more out of their marketing spends while still streamlining their budget.
Essentially, it can make your money go further. You’re not throwing ideas at the wall to see what sticks — you’re basing your decisions on provable facts.
You can jettison those marketing techniques and campaigns that fail to bring in satisfactory ROI. All resources usually dedicated to those will be put to better use on more effective options instead.
How can you use a revenue attribution model to measure and ramp up your marketing ROI?
We understand what revenue attribution is and why it matters. But how do you put a revenue attribution model to work and start improving your marketing ROI?
While it can appear complicated for newcomers, and more than a little daunting, it will seem far simpler when we take a deeper look. In this section, we’ll cover how to use this model to both track and measure ROI — and improve it.
What types of revenue and marketing attribution models are available?
The first-touch (or first-click) attribution is one of two single-source models (along with last-touch attribution, below).
In this model, the first channel with which a converted user engages receives all credit for generating revenue. This could be an in-depth whitepaper, a blog post, a video, or any other piece of marketing content that captures the lead’s interest enough to drive a conversion.
For example, around half of marketers describe webinars as the top-of-the-funnel format generating the most high-quality leads.
While a spectacular piece of content can be enough to push users towards a sale, the first-touch model may have a blindspot — a failure to take other interactions following this first one into consideration.
As a result, you may not have an accurate insight into how effective other channels are in swaying users’ decisions.
Last-touch (or last-click) attribution is regarded as another easy model. Why? Because it involves looking at the final touchpoint before the sale is completed, which is usually simple to find.
The last touch could be something as straightforward as a well-researched sales call or a webinar that whets the lead’s appetite and inspires them to commit to a purchase.
However, the last-touch attribution model may overlook previous interactions with a user. These could include a visit to your website or hearing an ad for your business on a podcast. And, again, this could cause you to overlook the value of other channels
As you can probably assume, the multi-source (or multi-touch) attribution model focuses on all channels that lead to a conversion. Multiple touchpoints will be attributed instead of just one.
Still, while the multi-source attribution model is more of a holistic approach to measuring marketing success, there’s a crucial factor to consider: it doesn’t provide an accurate reflection of a specific touchpoint’s actual contribution to a conversion. It could lead to a false representation of certain channels’ role in the customer journey.
Six multi-source attribution models are available:
- Linear: This is the easier model to implement, providing all touchpoints with the same weight, though it can be hard to determine which were most important (as mentioned above).
- Time decay: Touchpoints will be separated by bigger and bigger gaps in long sales cycles. With the time decay model, you’ll apply greater credit to those in the later stages than those in the earlier period. They might not have been as valuable to the eventual outcome, and in particularly long sales cycles, the buyer might have totally forgotten about their initial interactions with your business anyway.
- U-shaped: A U-shaped revenue attribution model applies the credit to two main touchpoints, with fixed percentages. These are the initial touchpoint and the last, as well as any between those points. The first and last touchpoint receive 40% of the credit each. The 20% remaining is split between those touchpoints taking place in between.
- W-shaped: A W-shaped model is similar to the one above, but it adds an extra touchpoint: when a prospect is converted into a lead. So, this covers the first touchpoint, the last touchpoint, and the occurrence falling somewhere between them. These receive 30% of the credit each, while the remaining 10% is shared among other touchpoints that may be detected between them.
- Full path: The majority of the credit is assigned to the key steps in the customer journey and the rest goes to those touchpoints between. Unlike the other models explored so far, this includes follow-up chats between the customer and the sales team.
- Custom: Teams can come up with their own weighting shares according to the channels used, customer behaviors, etc. For example, you may decide that a user who subscribed to your newsletter should have more weight than someone who clicked on an ad.
Weighted multi-source attribution
Weighted multi-source attribution involves accounting for every interaction during the sales cycle and assigning weight to the most important touchpoints. This model can lead to the most reliable views of a customer’s journey.
However, it’s one of the most challenging to put into effect, as weight must be applied to a potentially large number of touchpoints.
Why is it so important for marketing and sales teams to work in partnership?
Traditionally, businesses tend to keep sales and marketing activities separate. They consider marketing teams’ role to create leads and sales teams’ to transform them into paying customers. That’s simple enough to understand — but it could be a big mistake.
Because overhauling and refining your marketing to achieve an increase in leads won’t guarantee a rise in high-quality leads.
Yes, marketing teams can drive clicks and interest, but a large proportion of leads could be of a lower quality than expected.
The aim should be to bring in leads more likely to evolve into conversions, based on carefully targeted marketing with specific demographics in mind.
By uniting your marketing and sales teams, you can start to develop a clearer understanding of which marketing efforts bring in the most valuable leads and, ultimately, conversions. Those that consistently generate the weakest leads and harm ROI should be replaced.
What are the key benefits of using these revenue and marketing attribution models?
Here are five key benefits of using revenue and marketing attribution models:
Effective revenue attribution provides businesses with an accurate insight into how much return they gain on their marketing investments. Over time, you can start to cultivate a better awareness of those techniques and strategies that engage your target audience best.
And you’ll keep reaching the right people with the most appealing messaging. This will increase the number of conversions you can expect to achieve and, eventually, the ROI you earn.
Save money on ineffective marketing
Attribution models reveal the most important touchpoints throughout sales cycles and show how marketing money is best invested. Fewer funds will be wasted on dead-end marketing.
That may free up money to channel into better marketing or other areas of your business, including sales or post-purchase support.
Hone your audience targeting
Audience targeting is one of the top methods through which advertisers increase demand. And studying attribution data reveals which types of content, messaging, and channels engage your ideal customers best.
Marketing teams can keep sharpening their material to consistently engage your target demographic(s) and minimize the risk of missteps.
Learn how to make products or services better
Marketers can get a better understanding of target customers through attribution data analysis.
Over time, this can open your eyes to ways in which you can improve products or services to suit your audience better. For example, the response to a blog post covering specific software features could inspire future releases.
The power of Revenue Funnel Optimization
Hopefully, you’re now in a place where you can see the key benefits of revenue and marketing attribution to your business. But, one of the most important aspects of attribution strategy is acting on attribution insights. And, that’s where we come in…
We’ve designed our Revenue Funnel Optimization strategy so you can get the most out of your revenue insights.
FunnelEnvy enables you to generate revenue insights by updating analytics to measure the complete end-to-end customer journey. You can pinpoint the most valuable funnels, offers, and other factors that drive revenue.
Revenue funnels comprise strategy sets focused on maximizing your website’s revenue generation through targeting the most effective offers to the priority buyer segments in your top conversion funnels.
Funnels can also be personalized by the user’s stage in the customer journey to maximize revenue further. You also can run campaigns and experiments on your most important funnels. Use direct response best practices to optimize offers, messaging, and more.
With Revenue Funnel Optimization, your decisions are driven by data and genuine insights into the buyer journey.
You’ll make stronger choices for your marketing and sales teams — and your business as a whole — by studying the facts.
Many companies are already achieving success with Revenue Funnel Optimization, with up to 250% growth in revenue and a 10x increase in Marketing Qualified Leads (MQLs).
Want to try Revenue Funnel Optimization? Start using FunnelEnvy and drive real revenue growth for your business!
If you haven’t yet heard, the cookie is on the outs — much to the cookie monster’s chagrin. The death nell was sounded by Google’s announcement of Privacy Sandbox, which is basically their plan to create a set of privacy standards.
This plan includes improving how cookies are classified, clearing up the details behind each person’s cookie settings, and plans to aggressively block fingerprinting. A fingerprint is created by stitching together a bunch of tiny signals about a person to create a full profile, and since people can’t access or delete their fingerprint, Google’s basically going to make it impossible to create them.
All of these intentions add up to one pretty plausible result — third-party cookies (the type used to make fingerprints, and fuel activities like retargeting) won’t be around much longer.
There’s another type of cookie though that’s not going anywhere — the first-party cookie, which allows marketers to collect first-party data. Focusing on shoring up your first-party data will not only prepare you for the death of the third-party cookie, but result in a stronger marketing strategy overall, regardless of the third-party cookie’s fate.
In this article, we’ll talk about the difference between the first and third-party cookie, why the first-party data is more valuable anyway, and how to use it to optimize your demand generation funnel.
First-party cookies vs. third-party cookies
Before we get into exactly how and why you should focus on first-party data, let’s straighten out the two types of cookies:
- A first-party cookie is created and stored by the website you’re visiting; the one in the address bar. If you’re a site owner, first-party cookies allow you to collect data like customer analytics, language settings, the user journey, and other information that can assist you in improving your customer experience on-site.
- A third-party cookie is created by sites other than the one you’re currently visiting. These other sites own some of the content, like ads or images, that you see on the site you’re currently visiting, and can therefore collect information about you while you’re there.
For example, say you’re shoe shopping with popular retailer DSW. When you visit DSW.com and shop for boots, you might not purchase right away. During that first visit, the homepage looks like this:
The next time you visit their site, there’s a new section of the homepage that displays the shoes you clicked on during your last visit. DSW dropped a first-party cookie on their site in order to remember that you were interested in buying boots. They then used this information to personalize your experience the next time you visited their site.
During this second visit, you made a purchase and provided your email. Two days later, DSW sends you an email about an upcoming boot sale. That’s first-party data. DSW used a combination of first-party cookies and personally identifiable information (PII), namely your email address, in order to personalize your experience.
Third-party cookies are most often used to retarget you on sites other than DSW.com. Perhaps after shopping for boots, you head over to nytimes.com to read up on the news. As you’re reading an article, you see a Google-owned banner ad advertising the shoes you just looked at:
A lot of data exchange went on behind the scenes for you to see this ad. First, DSW partnered with Google and started using Google Ad Manager to serve ads around the web. The New York Times also partnered with Google to display ads on their site, in order to monetize their content.
Google then dropped a third-party cookie on DSW’s site to collect data on your visit, and DSW retargeted you on nytimes.com in the hopes of capturing your attention, and bringing you back to your site.
These are the types of cookies that Google is looking to guard against, and they’re the ones that are likely to die in the coming year.
Your first-party is data more valuable than third-party data anyway
The thought that third-party cookies are on the way out has caused a bit of a panic among marketers, mostly because they’ll have to come up with new ways to retarget site visitors.
But the thing is, focusing on first-party data is way more lucrative than scaling retargeting campaigns based on third-party data. First off, you collected that data directly from a person, and you know it’s accurate. Second, because you collected that data while that person was visiting your site, you know they’re actually interested.
Let’s go back to our shoe example — which interaction with a potential consumer would you find more valuable — the one on your owned website, or the display ad impression they probably didn’t see?
We bet your answer is the former.
First-party data is more valuable because it’s the best indicator of buyer stage, and therefore intent. Someone visiting your website has a much higher intent to interact with your brand than that of someone who saw a display ad.
For demand generation marketers, buyers go through many stages in their journey, so it’s really important that the data you’re collecting on those buyers captures their intent at each stage.
FunnelEnvy combines first-party data insights and offers personalization in order to align the offers on your website to the intent the buyer has at the time they’re visiting. This way, you move them down the funnel every time they visit, leading to better conversion rates and ultimately more revenue.
Here’s an example from Fitch Solutions. They guide their clients in making clear-sighted decisions through data, research and analytics on the capital markets and the macroeconomic environment.
Like many B2B technology companies, they thought of their homepage as a type of welcome center where they introduced themselves to people getting to know them for the first time:
But, also like many B2B technology companies, they saw a lot of returning traffic, which is often a result of having a longer buyer journey. A “welcome center” isn’t an optimal experience for someone you’ve already welcomed.
FunnelEnvy worked with Fitch Solutions to personalize their homepage experience for each visit, and for returning visitors, they surfaced a relevant offer in place of their welcome message:
This change resulted in a 55% increase in conversion on site. By doubling down on optimizing their website using first-party data, Fitch Solutions made a huge impact on their funnel.
Optimizing the demand gen funnel with first-party data
So, how do you get from collecting first party data to activating it with a personalized experience on-site? The biggest challenge for the demand generation marketer facing the death of the third-party cookie is that first-party data is often siloed away in places like your customer resource management (CRM) software, marketing automation and in website analytics.
If you want to truly personalize an experience, you need to bring all of that data together for a holistic view of the consumer journey.
The effort is well worth it — in fact, 77% of B2B sales and marketing professionals believe that personalization builds better customer relationships.
But to get there, something needs to bring all of that siloed data together so that you can target accordingly by buyer stage. The FunnelEnvy Backstage platform brings together these data sources, website analytics and experience tools to create a unified customer profile.
If you have the data, you can get sophisticated with offer personalization. You can attribute different user experiences to revenue, target by buyer stage and scale revenue.
Here’s an example from TIBCO Jaspersoft. They had one static product page that contained multiple offers for different personas within the organization.
When they tried to squeeze multiple offers on a single page, offers competed for attention and blended in, which put the onus on the user to determine which was right for them.
We worked with them to target specific personas with a single offer, based on data they had stored in their marketing automation platform. Through testing variations that replaced the default experience with a single focused offer, we saw an almost 50% improvement in revenue per visitor.
Conclusion: the death of the cookie is nothing to lament
While the death of the third-party cookie will mean a shift in strategy, there is a huge silver lining — as it’s phased out, demand gen marketers can use the opportunity to shore up their first-party data strategies, which are likely to result in a much larger impact on their funnel.
We’ll see less focus on (admittedly crappy) ad buys and retargeting campaigns, and a larger focus on leveraging first-party data insights better at home.
If you’re stuck on where to start when it comes to shoring up your first-party data strategy, we can help. Apply now to get started.
Let’s take a step inside the data-driven demand generation marketing team. The biggest concerns on the CMOs radar are that the acquisition costs are too high and not hitting their pipeline or revenue goals. Now looking at the data, we know that not only are they spending a lot on paid and organic traffic, but the quality of the traffic is good, and it’s not converting.
So, of course, the next question would be – what can they do about it? A common answer is to focus on website conversion rate optimization, which involves running online experiments. That’s something you can put a budget around and prioritize but recognize that your executives are going to want to see impact based on pipeline and revenue and probably want to see it fast.
Back in 2017, the Harvard business review published an important article digging into the power of online experimentation. In it, they correlated successful business outcomes to a culture of experimentation.
Image Source: The Surprising Power of Online Experiments (Harvard Business Review | Link)
The article cited examples like the one below from Bing, who tested multiple different colors on their site, ran experiments. and realized an incremental $10 million in annual revenue from these experiments.
Image Source: The Surprising Power of Online Experiments (Harvard Business Review | Link)
Similarly, Google ran a test with 40 different shades of blue on their site. When they ran those experiments, they achieved $200 million in incremental revenue. Given these results, should we, as demand gen marketers, be running the same experiments?
In our opinion and experience, no, you should not.
You’re not Google or Bing. Leaving aside traffic considerations, you’re trying to influence B2B buyer behavior over customer journeys. And the reality is that groups of buyers that consider enterprise solutions are not going to buy based on the button color or other small cosmetic changes.
This is important because experimentation comes with a cost. Not only do you have people and the technology costs of running online experiments, but also your organizational ability to make decisions. So, focus on the elements that would deliver revenue and influence those B2B buyers when you’re thinking about experimentation.
When we think about the B2B buying journey or the revenue funnel it’s common to conceptualize it as a series of buyer stages. As prospects progress through those stages, they do so through exchanges, in which you’re offering something to that prospect in exchange for something else. The offer could be some content in exchange for their attention, an event, or an opportunity to speak to the sales team in exchange for their contact information. Ultimately those offers are how they learn more about your solution and how it would benefit them.
From our experience and the testing that we’ve done, the highest leverage use of experimentation for the demand gen org is to improve the relevance of those offers and the ease of engaging with them throughout the buying journey. Of course, we always want to ensure we measure the impact of those experiments based on the KPIs that matter – pipeline and revenue.
What does it mean to optimize offers? There are three components to an effective offer. One, of course, is the offer itself. That item you’re proposing to exchange with that visitor or prospect for them to understand your solution. The more relevant it is, the more effective your ability to convert them will be.
The second important aspect is how you frame it. Our primary focus here is the headline and Call to Action (CTA). Your headline is important because a visitor will spend five or ten seconds deciding if they want to stay on your site or hit the back button and go somewhere else. So, entice them to continue reading the content on the page.
Finally, the third element of the offer is the exchange and how they provide what you want. Most likely on your site this is a web form, but it doesn’t need to be. It’s increasingly common to see conversational marketing tools (chatbots) that accomplish the same thing by providing that medium of exchange for the offer.
Let’s look at some examples of how you could optimize your offers.
Landing pages are a great starting point for thinking about your offers. Many of you are probably running traffic to dedicated landing pages and putting an offer in front of the visitors hitting it. But not every visitor is interested in the same offer. In the example below, we recognized when working with a customer that they had three viable offers for those visitors coming through their paid campaigns. And rather than only showing them one, we use data to dynamically personalize the offer itself as well as framing and the page layout to reflect what might be most relevant to that visitor.
When we ran the experiment against the static landing page we saw a 44% improvement in revenue per visitor.
For most of us the most trafficked page on our site is the homepage. And on your homepage the “above the fold” section at the top gets most of the attention. Many of us think about our homepage in the context of welcoming the first time visitor and introducing your solution as in the example below.
For SaaS and Demand Generation websites it’s common to have a lot of returning traffic. Since return visitors are familiar with your solution, it wouldn’t make sense to show them that same offer. In an experiment, we targeted these return visitors and the solutions they showed interest in and presented them on the homepage. In this case, those offers were buried in the site and require additional navigation. By presenting this offer they would likely be interested in and serving those directly on the homepage, we saw almost 55% improvement in conversions coming through this page.
You can also target well-defined buyer stages. In the following example, we have a customer with a freemium model where visitors on the free plan come to the homepage and see a CTA or a button prompting them to “Upgrade Your Plan”. The baseline experience was to take them to a set of SaaS plan tiers where they could select the one that they would upgrade to.
Using this data, we can identify the specific plans most relevant for any individual and offer them directly on the homepage. The framing included the benefits and replaced the CTA with the cost of that specific plan we recommend. Since we recommend a single upgrade plan, we bypassed the plan selection (and the friction it created) and took them directly to the credit card to upgrade. By removing friction and presenting them with a more relevant offer, we saw an almost 70% improvement in revenue per visitor coming through this experience.
The most common mechanism of exchange for the offer is the web form, and as a result, we spent a lot of time optimizing them. It’s important to recognize that there’s a lot of friction for the visitor when they encounter one of these forms.Even if they’re interested in the offer, they face the prospect of handing over their email and other personal information, which often presents a big hurdle. Since it’s common to see drop-offs at this stage, we would like to take those contact forms and reinforce the benefit and the value to the visitor filling them out. In the following example, we tested an updated version of the form page resulting in an 85% improvement in conversions.
If you have the data, you can get sophisticated with offer personalization. It’s common to see pages like the one below. It is a product page that contains multiple offers for different personas within the organization. Unfortunately, when you try to put them all on a single page, they compete for attention and blend in, making it hard for users to know which one is relevant for them.
In this case, we target specific personas visiting the page based on data we had in the marketing automation platform and identify the most relevant offer. By testing variations that replace the default experience with a single focused offer, we see an almost 50% improvement in revenue per visitor.
It’s possible to waste time, effort, and money optimizing inconsequential elements of your website. For demand generation marketers, the highest leverage things to focus on are the offers – specifically their relevance to the visitor and the ease of engaging with them.
Before you undertake this experimentation it’s important to make sure you have solid revenue insights. What that means is, evaluating your existing offers as well as future experiments based on their pipeline and revenue contribution.
Some of the personalized examples above require some segmentation. Our recommendation is to prioritize segmentation based on the differentiated intent and addressable size of those segments. We often find that marketers are running building audiences that can only address 5-10% of their audience, or ones that don’t have meaningfully different intent from one another. Ultimately those aren’t going to have much value when it comes to optimizing offers.
This is why we start with buyer stages as our starting point for segmentation because it a large set of well-understood segments with differentiated intent – buyers at different stages will naturally gravitate towards different offers. The vast majority of the visitors coming to a demand gen site fit into anonymous, known lead, active opportunity or existing customer.
Finally, when it comes to improving offers, start with common sense ideas. If you start thinking about your buyer stages, some opportunities should become apparent. For example, should a known lead see a lead capture form, or can we repurpose those pixels for something more relevant? Similarly, should existing customers see the “Request a Demo” or “Talk to Sales” CTA? Maybe there’s an opportunity to get them to support resources or event upsell them.
What’s stopping you from generating more revenue by improving offers on your website? If you’re a Demand Gen marketer and need help, feel free to get in touch.