Polaris = MMP 2.0
Polaris is MMP 2.0, a turnkey, drop-in replacement for your last touch MMP (MMP 1.0). No more value gaps like poor accuracy, lack of privacy-safety and limited measurement scope. Polaris looks like a MMP but delivers far superior measurement.
Break Free Of The Limitations Of SKAN
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, it cannot measure incrementality or non-addressable media (offline, TV & influencer). Polaris measures true lift and delivers the same KPIs that you rely on to drive your UA processes.
Close The Gaps
In Your Measurement Stack
Polaris closes the value gaps in existing last touch MMPs (MMP 1.0), namely, poor accuracy, lack of privacy-safety, and poor measurement scope. It is designed to look like a MMP, but merge the strengths of multiple measurement methods, making it easy to adopt, easy to use and a boost to your performance. Here’s why Polaris is trusted by mobile leaders such as Blizzard, FunPlus, Kabam and Nexon:
Easy To Use With Your MMP
Keep your last touch MMP, quickly drop in Polaris to get a single data hub for comparisons of last touch and incrementality, and one source of truth.
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.
"iOS14 led to blindspots in our performance measurement. MetricWorks allows us to make apples-to-apples measurement between iOS and Android across all channels, without using device IDs or heavy migrations. The combination of MetricWorks incrementality data alongside last touch data gives us a unique window into performance."
– Cole Carnes, Senior Growth Marketing Manager,
Kabam
