How to measure incremental ROI

The key factors to consider when implementing a successful measurement strategy that will help prove impact.

Paul Frampton, President Europe at CvE, shares his views on evaluating and planning a digital media strategy...

Incrementality measurement enables marketers to understand the true impact their marketing strategies have on a customer’s decision to purchase. And yet, with the breadth and depth of data now available in digital marketing, it can be tempting to invest heavily in niche audiences that might have a strong natural propensity to purchase for a brand. 

Without a proper measurement strategy, marketers leave themselves vulnerable to over-investing in tactics that have minimal or no influence in driving incremental business results. The key is to do so responsibly with the right measurement plan.

When evaluating and planning a digital media strategy, it’s imperative that marketers ask themselves, “How are we going to measure incremental ROI?” Is it by utilising a test-and-learn approach geared toward driving a quantifiable business outcome? If so, great. If not, it’s time to develop one. Otherwise, marketers run the risk of driving suboptimal results at best, based more on correlation than causation. The good news is there’s no shortage of ways to achieve this in the digital marketplace. To be successful with any test, keep these four important considerations in mind...

1. Understand the methodologies

Traditional approaches like the utilisation of the public service ad (“PSA”), geographic splits or CRM user holdouts can be highly effective if executed with the right degree of rigor. Additionally, in the last four to five years, newer and more innovative approaches have arisen that mitigate some of the drawbacks of these traditional approaches. For instance, Facebook and some programmatic platforms have developed methodologies that can dynamically hold eligible users back for a control group without the need to allocate otherwise working media spend toward a PSA or other type of placebo. 

2. Measure what matters

Select a business outcome that you’ll be able to measure success against for the test. Ideally, this is a direct business outcome. If not, try to identify a strong leading indicator or proxy. It’s worth noting that offline data is becoming increasingly available for measurement in digital advertising platforms. Once you’ve done this, identify a KPI goal against that outcome. Keep in mind that positive lift on its own is not always a successful outcome. The lift needs to translate to a goal focused on incremental return for your business, such as ROAS or CPA among others.

3. Attain statistical significance

Carefully consider parameters, such as exposed vs. control breakout percentages, and test duration needed to attain statistically significant results. Typically, the higher an allocation can be against the group you mean to expose, the less opportunity you are leaving on the table. Therefore, rather than defaulting to a 50/50 exposed vs. control breakout, work with your data teams ahead of time to determine an ideal split that allows you to garner significance while also reaching a meaningful portion of your audience. 

4. Generate actionable results

Proving campaign performance success is great, but success (or lack thereof) should also make you smarter for future activation. Consider developing additional test cells, such as creative or audience segments, to understand which pockets of media are more incremental than others. This will enable you to derive more actionable optimization opportunities as a result of your testing.

In practice

Recently, one the largest advertisers in the UK was faced with the challenge of acquiring new customers and retaining existing ones. Much focus had been on its well-known TV ads as well as on paid search, but the brand now wanted to reduce its dependency on the latter. It was time to look at channel diversification and in particular, display advertising.

As a result, the brand partnered with CvE and Adform and through precisely measuring a control group versus an exposed group, was able to measure the true value of programmatic display through an incrementality test. The results spoke for themselves and from total click-outs, 38% were incremental from the exposed group. This meant that the brand’s marketing team was able to go back to the business and show that display can provide the business with the opportunity to grow, diversify its channel mix, and deliver more against its KPIs.

Ultimately, all incrementality measurement solutions have their pros and cons, and no one solution will be applicable for all digital channels. The key is to not let perfect be the enemy of the good but rather to define a business goal and utilise an approach that puts you in the best position to measure and optimise performance against that goal.