Better, Faster, Stronger Data

Great data needs a great team.

Meet the brains behind the best Data Team in App Store Intelligence

  • Michelle Tran : Head of Data Science

    Michelle Tran
    Head of Data Science

    A California native, Michelle moved to Berlin in 2012 to become Priori Data’s very first hire. She holds a B.A. in Political Economy from UC Berkeley and a MPhil in Finance from the University of Cambridge. Prior to joining Priori, Michelle worked in the economic consulting industry in San Francisco. In her spare time she enjoys food blogging and balancing her chakras.
  • Ryan Field : Data Scientist

    Ryan Field
    Data Scientist

    Ryan brings experience working in business analytics in the Bay Area tech scene. At Priori he works on the data pipeline and develops models. He has a BA in Physics from UC Berkeley and an MS in Statistics from CSU East Bay. In his spare time, he enjoys playing online chess and making MS Paint illustrations.
  • Fabian Bruckschen : Data Scientist

    Fabian Bruckschen
    Data Scientist

    Originally from Munich, Fabian fell in love with Berlin while completing his Masters in Statistics at Humboldt University. He was one of the first people to join Priori as a working student. Since then, he has graduated from a data slave to a full-time data scientist and is now in charge of several models. When he’s not out in the city discovering hot new eateries or trying to solve Escape Game riddles, he enjoys watching The Walking Dead and eating Indian food.
“Priori Data has leveraged a small team to process vast amounts of data, share it with customers and partners and expand to new markets.”
Accuracy up to

90%


in main countries
20% of our partners have

+100 Million


Downloads globally

How We Collect Data

We rely on two primary data sources

Public Store Data

Chart Ranks
Inventory
Ratings
Reviews
Metadata

Proprietary Partner Data

Downloads
Install Revenue
In-App Revenue
Data Processed:

+2 TB


Per day
Our Partners generate

+150 Million


Downloads per month

How We Calculate Our Estimates

Download/revenue data and top chart ranks are closely related

The distribution of app store downloads/revenue across top chart ranks follows a predictive curve
With the help of data from our publisher partners, we can determine what this curve looks like
As a result, we're able to get estimates at every rank position.
More than

1,300


Partners trust us
Data for more than

20,000


Apps collected
Historical data since

Sept 2014

Partner Apps + Top Ranks = Better Accuracy

Our data coverage is increasing over time

100%
Share of markets where we track ranked apps in Q2
99%
96%
Share of markets where a partner ranked in the Top 10 in Q2
69%
10
Median rank of partner apps on top free list
27
7
Median rank of partner apps on top grossing list
24
Now check it out for yourself.
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