Babar Khan Javed
Sep 13, 2017

Better targeting starts with knowing content habits: OpenDNA

With publishers, an AI-enabled app, and Android device makers all playing roles, the company says it is arming advertisers with a better ability to target consumers according to mood and intent.

OpenDNA's Jottr app
OpenDNA's Jottr app

Retargeting is rife with problems.

There are many reasons for this, key among them being that DSPs cannot determine the intent by which a user visits a website.

This is fairly reflected within Google Analytics. When users filter audiences by in-market segments, they can find a list of product or service categories. These infer, based on browsing behavior collected by Google, the interests of a user and the likely inclination toward purchase. And for most cases, the data is accurate. But as most of us can attest, the possibility remains that users will be the victim of retargeting gone awry, where a campaign relentlessly targets someone who is not truly a qualified customer. 

With coalition of publishers and device makers, plus a content-discovery app, OpenDNA is offering what it claims is a solution to this problem.

“OpenDNA is giving advertisers a greater level of personalization when targeting their brands to consumers,” CEO Jay Shah told Campaign Asia-Pacific. “Subscribers access high-level machine learning, which allows them to generate highly detailed individual customer profiles and distribute ads to individuals.”

Using proprietary artificial intelligence and machine learning that mirrors to logic inferences of the blockchain, the OpenDNA system determines intent based not just on search habits but also on content-consumption habits.

The value for advertisers is knowing the phase and mood a reader is in, which informs the relevance of running an ad against an emotion or intent at the time.

Shah says that users of OpenDNA software include a subsidiary of Woolworths, US-based business analytics company Looker and publishers such as the Robb Report.

OpenDNA relies on data gathered from Jottr, an app similar in purpose to Flipboard, with the exception of one key difference. Like Flipboard, the app aggregates news and presents it to users. But it also applies machine learning to serve repeat users content that is similar to their reading interests, whereas Flipboard simply shows its users the most popular news from a specified news cycle.

“So most services on the market offer content from a fire hose and not a tap,” Shah quipped.

Publishers signed on with Jottr have experienced a noticeable change with regards to the average time on site and the pages read by each unique visitor. There are two ways the company works with publishers, The first is including their content in the Jottr app. The second is to have publisher install OpenDNA script that can change the content of a website, so the content being served matches the psychographics of the visitor being tracked by Jottr.

OpenDNA works with advertisers and ecommerce companies to sell products and services to audiences that have been identified to be intent on making a purchase, as well as audiences that are monetarily qualified to do so. It also earns either a flat fee or a performance fee from publishers that want their content appearing on the Jottr app. Publishers that rely on income from sponsored content may also opt in to have their content appear on sites that are being visited by their target audience, with the opt-in working both ways.

OpenDNA has signed mobile-phone OEMs (original equipment manufacturers), including Future Mobile Technologies, to pre-load Jottr on their Android-based phones. In turn, these OEMs stand to earn a fee from monetization events where the device is the key touchpoint. They also stand to increase their customer lifetime value in a time when the smartphone is commoditized.

“Once HTC sells you a handset, [the handset] makes money”, Shah said, but not for manufacturers who are not named Apple. “The customer goes on a website, and Google makes money off the ads. You download an app, Google makes money. You pay for something on Google Play, Google makes money. With us, handset manufacturers are making money after selling the device, delivering value to the user even after selling the hardware. And this revenue-model shift lowers the cost of the handset, in the interest of getting it into more hands.”

“Customers of the OEMs that we work will have a handset that will personalize the entire experience of news, ads, and search,” Shah noted. “It’s a no brainer.”

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