Marketing-Influenced Revenue: Clarifying What Attribution Misses

This article was originally published on ANA.net.

Many marketers have an intuitive sense that something is missing from the story attribution tells.

The very idea of attribution is hotly debated, and even those who do use it as a measure of success are skeptical about what their data tells them. Survey results from RevSure and Ascend2 tell us that only 31% of marketers are confident about the accuracy of their marketing attribution.

If you have doubts about the validity of your attribution data, then, how are you supposed to measure the impact of your marketing programs?

You re-think attribution altogether.

The point of attribution is to answer two questions:

• Do my programs impact pipeline and revenue?
• How much “credit” can I attribute to each marketing touchpoint?

But attribution may not be the best indicator of either.

Here’s why.

Attribution is limited to tracking conversion activities like form fills, webinar sign-ups, and lead magnet downloads. If someone completes one of these activities and then goes on to become a sales opportunity or customer, attribution can give credit to that activity.

But what if that person doesn’t fill in a form? 

What if they click your ad, browse your site a bit, and then exit? Shortly after, a sales rep reaches out cold, schedules a demo call, and eventually converts them into a customer. There’s no form fill or trackable marketing activity, so attribution doesn’t give any weight to your ad or speak to its impact on the buying journey.

But it did have an impact.

Even if that impact was to build brand awareness, meaning the prospect was more open to that initial call with the salesperson, your ad still influenced the deal.

Attribution doesn’t measure that impact, but influence does.

Most marketers who measure attribution use one of these models:

All of them have their flaws.

For many marketers, single-touch models are unrealistic. It’s almost never the case that a single touchpoint was the only thing responsible for the deal, whether it was the first or the last one the prospect engaged with.

This is especially true in B2B, where buying cycles are long, involving large buying committees and complex buying procedures.

Multi-touch attribution models recognize that all marketing interactions may have some impact. 

The problem is that the weighting given to each touchpoint is often arbitrary. For example, a company might give each touchpoint 20% of the “credit” for a deal, but this doesn’t account for the very real fact that some programs have more impact than others.

Influence can help understand the extent of that impact.

What gets measured gets optimized.

When marketers measure attribution, what they end up optimizing for is conversion points because that’s what their toolset allows them to track.

Instead of focusing on reducing friction across the buying cycle to speed up pipeline progression, marketers who measure their impact using attribution often focus on maximizing the number of attributable leads they generate.

This, in turn, drives a misalignment between Sales and Marketing.

Marketing is focused on building awareness and leads, while Sales manages every other stage of the revenue pipeline.

Influence, instead, aligns Sales and Marketing toward a common goal of driving pipeline and revenue, rather than focusing on individual metrics like MQLs. 

Influence measures all the factors that impact a prospect’s decision to buy, not just the conversion points.

First, you have to set qualifiers for what you consider an influenced deal.

For digital ads, for instance, some good qualifiers are:

• Target prospect. The person who saw or engaged with your ad needs to be part of the buying group you’re targeting.
• Intent. The person must have clicked an ad or seen it at least 15 times. 
• Window of time. The engagement (clicks or views) needs to have happened within 15 days of a positive sales outcome.
• Positive sales outcome. There needs to have been a new opportunity generated or progressed, or a sales conversation opened that led to that new or progressed opportunity.

If a deal meets the above criteria, then you can classify the deal as influenced by your ad program.

Once you have established that an account was influenced by a given program, the next step is to quantify that influence.

You do this by comparing the conversion rate of deals that were influenced by your program to those that weren’t.

Let’s say, for example, that you’ve converted 150 deals over the last quarter. 100 of them were influenced by your ad program with a conversion rate of 6%. The remaining 50 were not influenced by ads, and have a conversion rate of 4%.

The delta between these two figures is the additional value created from your ads.

Imagine that your total amount of influenced pipeline for the period is $30,000,000. Without the influence of ads, you would have generated $20,000,000 from that, since the cold conversion rate was 4% (vs. the influenced conversion rate of 6%).

Thus, the value of your ad program can be measured. It’s $10,000,000 in additional pipeline.

For low-complexity buyer journeys, such as you might find in certain B2C industries, attribution can give marketers some insight into what programs drive purchasing decisions.

In B2B contexts, however, decision-making processes are rarely so simple, and attribution struggles to paint a full picture of the impact of our marketing programs.

By measuring influence, we can fill the gap left behind by attribution. Marketers can better understand the impact of their programs on pipeline and revenue, protect themselves against budget cuts, and improve alignment with Sales.