DataCultr uses a genome mapping approach to understand smartphone users

A new kind of advertising technology start-up is trying to understand the smartphone user by using a genome mapping approach. DataCultr, the smartphone data company launched by parent Boxer Internet in 2012, has been scrambling to mine smartphone user data.
Founders Neel Juraisingani and Sujoy Ghosh say the platform is more of a result of endless experimentation at Boxer. The two founders had previously been building ad servers for mobile platforms.
DataCultr works by noting events on smartphones. Such events include turning on a device or checking into an app. Each action defines the consumer behaviour and is turned into an informable piece of data. Such data may be used to make informed and personalised advertising and product recommendation. As an example, Juraisingani says:

“Let’s say, I drop my phone 6 times and break the screen once. On the seventh time, what if I get a call from a mobile insurance company that will cover me against future mishaps? I’ll be more inclined to sign up with them then as they are solving for my immediate need.”

DataCultr has been live since October 2016 across various client OEMs. The firm’s business model is SaaS-based with monthly or annual subscriptions. In addition, DataCultr offers a licensing model for enterprise clients.
Projected revenues for 2018 are somewhere between $150,000-$200,000, according to Juraisingani.
Though competition within deep user profiling is certainly fierce, Juraisingani adds:

“Our differentiator is the same as the one with the QC system we placed in our partner OEMs’ devices. No one else is close to figuring out the scope and breadth of this data and doing deep profiling of the user – genome mapping of the smartphone user – to the extent and clarity that we have managed. But the truth is, we need competition as we alone cannot capture the market. We like to think of it as collaborating with the others, instead of seeing them as competition.”

In the future, DataCultr plans to apply its algorithm to IoT devices and ship devices with pre-installed data mining capabilities.

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