Cillian Bracken Conway
11th Mar, 2016

The crystal ball in advertising BlabPredicts has announced its global public release of its new platform. With capability of Conversation-Based Data Segments, the feature allows publishers, brands and agencies to drive campaign engagement using predictive data of up to 72 hours in advance.

From a social monitoring platform, the company has now turned itself into a data targeting firm.

Vice President of Product and Marketing Ryan Bowermaster said that BlabPredicts has become a “data provider for media targeting”.

The new platform allows brand messaging to be directly targeted into topics that people are most interested and engaged with at any given moment. An advertiser only need to direct relevant ads right into ongoing and keyword-segmented social conversations. This delivers live audience segmentation more effectively and in real time. This also reduces inefficient spending on paid social ad buys and programmatic digital media.

BlabPredicts’ dashboard reports have been extended to enable trends, keywords and segments to be used directly by advertiser-focused DSPs (Demand Side Platforms) and DMPs (Data Management Platforms). Horizon was the first agency to use the new platform with their DSP, as part of its HX programmatic solution.

Unlike traditional cookie-based targeting, BlabPredicts’ new platform allows conversion of real-time streams of information into actionable audience insights. Brands can then create messaging that is relevant to trending conversation among consumers, even before they happen. The same platform also curates data segments to target audience across Display, Social, Search, Mobile, Video and Native. These segments are then refreshed in real time, so brands can stay engaged with their clients throughout a particular campaign. This would lead to maximum results.

Previously, BlabPredicts was sifting traditional news, blogs, social media and other sources to detect brand-relevant keywords and trends. But clients told them that they wanted to do more than read dashboard reports.

A producer of fabric softener, for example, discovered that “musty” was a term parents commonly used when posting information about Halloween costumes or used clothing. Using the insight gathered through BlabPredicts, the company then changed some of its marketing to emphasise on the anti-musty properties of their product.

During a Valentine’s Day campaign, another company discovered lesser-known phrases linked to the occasion through the social monitoring platform. They then used the terms “Netflix and chill by myself” and “forever lonely” to direct ads to people who are single or self-proclaimed uncouples, instead of the usual phrases Valentine’s Day and love.

Bowermaster pointed that the breadth of data resources, trends and associative discovery of keywords are what makes BlabPredicts different from other platforms that target conversations and detect trends, such as Taykey.