Elevating incrementality measurement from traditional to future-proof

As mobile marketers are moving away from solely relying on device-level, last-touch attribution data, the industry is shifting to integrate a strategic combination of next-gen measurement methods. Among these, you’ve likely heard of incrementality. It's quickly becoming a go-to concept among leading marketers, gaining rapid traction in the mobile landscape.

This is because it informs marketers of exactly what’s happening to installs or events as a result of a particular marketing effort. It answers the question, “What would’ve happened if you didn't do a specific action?” Is your campaign genuinely lifting your installs? By how much? Is it lifting event outcome on one platform and harming it on another? Are you actually cannibalizing organic installs with a particular campaign? Would you have seen the same results without the campaign? Incrementality measurement is going to give you these answers and more.

But, here’s the catch. Traditional incrementality approaches, while once effective, may not yield the same results in today's fast-paced, privacy-centric environment. Traditional incrementality breaks one audience into two segments: The control group, and the test group. Only, producing this control group is not as simple as a split down the middle. Creating a large enough, similar enough control group with minimal variables is, in fact, quite challenging.

And even if a control group is created, the result can be biased insights, inconclusive data, or a corrupted control group. Indeed, it’s quite difficult to guarantee that the group is not impacted by other campaigns running at the same time.

By improving upon these conventional methods, Adjust has unlocked new levels of efficiency, effectiveness, and innovation with our incrementality analysis solution, InSight. Leveraging the latest in machine learning and AI technology, our newest product pillar, Recommend, is our commitment to empower and advise marketers to make smart, data-driven ROI positive decisions and InSight will be the first Recommend solution to deliver exactly that. This solution not only leads to enhanced performance and profitability for you, the marketer, but also fosters a culture of continuous improvement and adaptability.

In this privacy-centric ecosystem, we do the heavy lifting for you. We leverage aggregated data to create synthetic control groups. By comparing the results of a marketing effort to an advanced machine learning model, we can measure outcomes with high precision. As a matter of fact, our models offer a confidence level of 95%!

Variable clutter is removed. Existing campaigns no longer need to be paused. Ad spend wastage is avoided by quickly detecting organic cannibalization. There’s no sifting through loads of data. All that’s left is quick, clear insights that can be actioned swiftly for campaign optimization that truly makes an impact. This also means you’ll save resources as there's no need for dedicated data scientists.

Our cutting-edge incrementality solution has been in the early access phase, carefully tested and refined with the help of our existing customers. During this period, we've gathered invaluable feedback and insights, allowing us to fine-tune our product to meet the exact needs of the market.

One such client, Sleep Cycle, used Adjust’s InSight to unveil organic cannibalization in at least 50% of campaigns tested, among other significant findings, which allowed the team to hyper-optimize campaigns for positive incremental lift. This case study serves as a testament to the impact our solution promises to deliver upon its official release.

With the launch date fast approaching, we're excited to invite all our customers–existing and new–to stay tuned for the unveiling.

InSight is set to make significant waves, offering unparalleled insights and optimization capabilities. This isn't just another product release; it's the beginning of a new era in next-gen marketing effectiveness and strategic planning. Keep an eye out for updates, and prepare to transform your marketing measurement.

In the meantime, you can request a demo to see how the rest of Adjust’s leading measurement tools complement incrementality measurement for robust, reliable analysis.