All mobile app marketers are looking to engage and convert more users. With so many marketing channels available, there’s a lot of pressure to quickly hone in on what will yield the most valuable business outcomes.
The more channels a business experiments with, the higher their chance for finding a blend that achieves substantial ROI. However, the experimentation process is tricky and time-consuming. Metrics like click-through-rate (CTR) and costs per acquisition (CPA) can give some useful insights, but they usually don’t tell the entire story.
Many marketers constantly wonder if their advertisement campaigns caused a consumer to convert. The answer to this question and more lies in incrementality testing.
What Is Incrementality Testing?
Incrementality testing, otherwise known as ‘Uplift Modeling,’ ‘Incremental Sales Lift’ or ‘Placebo Effect,’ measures the lift that advertising spending provides to conversion rates.
Download Branding Resources Guide
Building a brand starts by having the right tools and advice. Download our top 10 essential tools and resources to kick-start your branding.
Advertisers can use incrementality testing to see how a single variable impacts user behavior. The resulting incremental lift shows how a certain digital advertising tactic impacts sales in comparison to other marketing endeavors.
Armed with this type of knowledge, you can then use data to formulate a more concrete marketing action plan. Dividing up audiences and marketing tactics into testing and control groups through incremental integration testing gives you reassurance results are not influenced by outside factors.
What Are The Benefits of Incrementality Testing?
The benefits of this type of test are robust. Incrementality testing can:
- Validate the impact of digital media vs. organic conversions.
- Validate conversions that are new.
- Validate a single targeting tactic by a vendor.
- Validate (and then compare) incremental sales across head-to-head tests.
Incrementality testing gives advertisers the ability to fine-tune their budgets since they have a better idea of how to allocate retargeting ad spend. In an advertising industry fraught with a lack of clarity, this type of testing gives businesses confidence in their marketing tactics.
However, despite all the benefits of incrementality testing, it’s still a pretty new concept that hasn’t yet achieved widespread popularity.
Why Isn’t Incrementality Testing Popular?
It might seem a bit weird that this type of testing has not been universally adopted, especially in light of its benefits. But incrementality testing carries a couple pitfalls.
First, testing is usually costly since money has to be dedicated to placebo advertisements. However, increasingly advanced AI technology is now letting companies with small budgets and volume carry out tests.
Additionally, getting precise metrics from incrementality testing can be extremely difficult. A lot can quickly go wrong. Many marketers think incrementality can be measured merely by examining conversions before and after a digital marketing effort.
The most precise measurements, however, will come through scientific approaches like randomized control trials (RCT).
How Can I Perform a Test?
RCTs can be an easy way to take a lot of the complexity out of incrementality tests. You simply split a target audience into a control and test group and then show the test group advertisements. Then you’re able to observe conversion rates and calculate impact. This gives you a clear picture of the cause and effect of a marketing campaign.
It’s crucial to adhere to good statistical testing practices throughout the process to ensure legitimate results. This means randomly selecting people for groups from the same user pool. It also means coming up with a hypothesis, a primary outcome, and a definite start and end date to cut down on time distortions.
In the end, groups of people that have higher incremental lift probably need some more pushing through the sales funnel. Groups with lower lift are probably more likely to buy, even without an ad.
The Competitive Edge of Testing
Despite the trickiness of successfully carrying out incremental integration testing, it provides a lot of benefits to marketers and advertisers.
Understanding the effects of a marketing strategy can help optimize a budget, and getting an idea about the indirect impacts of a tactic lets you see how one marketing strategy affects another.
An optimized budget and high-level visibility into the varying effectiveness of your overall marketing strategy can position companies for long-term growth and ensure they stay a step ahead of competitors.