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Look Ahead: Deep.BI Makes Data Analysis Quick and Easy for Publishers

Guest User
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August 28, 2019
Look Ahead: Deep.BI Makes Data Analysis Quick and Easy for Publishers
Guest User
August 28, 2019
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X MIN Read
August 28, 2019
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X MIN Read
August 28, 2019
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X MIN Read

This article originally appeared on Editor & Publisher on August 6, 2019. The text has been reprinted with permission from the author.

Many news publishers are overwhelmed with the amount of solutions out there that promise to convert online readers into paying customers, but Deep.BI, a software provider with offices in California, Florida, the UK and Poland, has the potential to change the game.

Recently, Deep.BI made the Recency, Frequency and Volume (RFV) scoring metric developed by the Financial Times available, with real-time capabilities, to any media organization.

RFV is a combination of different usage interactions: recency is the number of days since a user used the product; frequency is the number of days (over a span of 30 days) a user has been using the product; and volume (content consumption) accounts for page views and active time spent using the product; whether this is reading, listening to radio, podcasts or music services.

Deep.BI goes beyond implementing the scoring metric by creating “fingerprints” for a user. Using the RFV score, Deep.BI is able to take a snapshot of a user’s RFV at any particular moment.

“Because we have this kind of fingerprint data left on all of the data events, we’re able to average the data and kind of spilt it anyway we want,” Alex Krzoska, Deep Score Product Manager, said. “We’re able to say, for example, ‘What is the average engagement of a user who read this particular content category?’”

The in-depth information collected by these fingerprints allows publishers to create thresholds for different automatic actions. Krzoska and CEO/CTO Sebastian Zontek explained that a publisher can implement an automatic paywall for their site or as many other actions as they like with the information they receive from Deep.BI.

The process of collecting data in order to calculate RFV is simple, Krzoska said. “We put our scripts either directly on your site or onto a Google Tag Manager and we immediately can begin the collection of data.” The only catch is that a publisher must have 30 days worth of data to begin with, so that Deep.BI can properly present the initial RFV score, otherwise the publisher can simply install the code and wait 30 days.

To date, Deep.BI has worked with over 20 newspapers around the world. Rafał Arciszewski, head of analytics at Polska Press Group/Verlagsgruppe Passau, said, “Deep.BI provides comprehensive real-time user engagement scores which not only allow us to know and target our user base, but also allow our editorial team to review content flexibly from an engagement perspective, adapting powerful metrics from Deep.BI and creating new metrics that suit our editorial needs.”

Zontek said that when publishers work with them, “It’s not going to be a year project to implement custom metrics. Everything here is so easily accessible…you can build your own tactics, strategies and products. This is what we want to provide for the media.”

For more information, visit deep.bi.

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