Polaris: The Privacy-Centric Incrementality MMP
Turnkey, drop-in replacement for last touch. Does not need device IDs, painful migrations, or changes to your marketing or UA processes. Offers the MMP experience, but built for incrementality, to overcome the deficiencies of last touch MMPs.
Superior Measurement Signal To SKAdNetwork
By now, you know that SKAdNetwork is a deficient signal with serious limitations. Data granularity is limited to only 100 campaign IDs. KPIs can’t be cohorted by install date. Most importantly, all performance KPIs including retention, revenue, LTV, and ROAS, disappear. Polaris measures true lift and delivers the same KPIs that you depend on.
Close The Gaps
In Your Measurement Stack
Polaris is the perfect complement to your existing last touch MMP. It is designed to deliver the MMP experience, but for incrementality, to make it easy to adopt, easy to use and easy to succeed in the new era of mobile marketing.
Easy To Use With Your MMP
Keep your last touch MMP and quickly integrate it with Polaris to get a single data hub for side-by-side comparisons of last touch and incrementality data.
Utilizes Historical Data
Get started in 24 hours. All we need is 2 months of your historical app events and marketing data. We can ingest it with a single API key for your MMP.
Preserves Your KPIs & Granularity
Keep all of your existing KPIs including retention, revenue, LTV, and ROAS. No painful surprises or process hiccups like those with SKAdNetwork.
No Migrations or SDKs
Saves you time and money by not requiring any migrations, SDKs or code changes. Easily integrates with your MMP, cost aggregator, or media partners.
Last Touch vs Incrementality
Interactive reports offer rich detail and comparisons between last touch and incrementality that give you full command of your marketing.
Data Science Expertise
Sophisticated data science expertise is captured in our fine-tuned regression algorithms to unleash the power of incrementality measurement.
Auto-Generated Experiments
Add robustness to the models by executing auto-generated experiments that measure ground truth incrementality while minimizing opportunity cost.
Transparency & Sharing
Understand our model internals like uncertainty and prediction error. Share model data with your data science team to boost confidence.
Unlocks Incrementality
Ditch legacy last touch in favor of the ideal future: incrementality. Measure the true value of each granular traffic source in the context of your overall media mix.
How Does It Work?
1
Ingest Your Historical Data
Quick ingestion of your existing historical app event and ad spend data to feed our models.
2
Train Models, Test & Analyze
Conduct model training, automated backtesting, and automated experiments to unveil incrementality results.
3
Deliver Measurement Output
Via API and dashboard at the same granularity as your spend data. Can be fed into our UA Automation solution.
"From having led a data science team, there is an awful lot of important insights that can come from having algorithms just analyze data at massive scale. That's something that people are not physically capable of doing."
– Anthony Cross, Former VP of Data Science, UA & Product Management,
Big Fish Games