Cognitiv Launches First Deep Learning Incrementality Solution To Help Marketers Find New Customers

Cognitiv Incremental: A Marketer’s Answer to a Brand’s #1 Question “Did My AD Campaign Cause a New Consumer to Convert?”

Cognitiv, the first self-learning, fully automated neural network technology available for marketers, announced the official launch of Cognitiv Incremental, a new product designed to help marketers accurately achieve consistent, scalable incremental lift.  Cognitiv Incremental is the latest product in the company’s robust portfolio of performance-based solutions which includes Cognitiv Performance, Cognitiv Audience, and Cognitiv Search. These solutions leverage Cognitiv’s award-winning NeuralMind™ platform to identify and serve impressions and choose people that make a difference, driving consistent campaign success at scale.

Cognitiv co-founder and CEO, Jeremy Fain stated, “For brands that want to drive truly new, incremental customers, Cognitiv Incremental gives them an undeniable competitive edge. Advertisers have long struggled to find a partner that can deliver consistent lift results at scale.  Cognitiv has long believed that Deep Learning is the only way to achieve this goal and now, with this new product, marketers finally have a tool that does that.”

A Fortune 100 company and one of the most recognizable brands in the US leveraged Cognitiv Incremental and achieved 11x lift in incrementality over all other partners. To achieve these results, Cognitiv runs several neural networks at once, in real-time, to more accurately predict whether an impression will deliver not only a conversion, but an incremental conversion. This is the first time ever in digital marketing that more than one neural network has been used in real-time for buying impressions. Additionally, lift results have stayed consistent over time as the marketer grew monthly spend by 20x.

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Fain continued, “Incrementality is the gold standard of performance metrics. However, predicting and achieving incrementality has historically seemed like a crap shoot.  It has now become common knowledge that machine learning is the only way companies can effectively analyze data, make assumptions, learn and provide predictions at scale with accuracy impossible to replicate by humans. At Cognitiv, we have created the first deep learning marketing platform and real-time execution system that can execute neural networks at programmatic speeds.”

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Cognitiv’s suite of innovative solutions are all designed to leverage first-party data combined with Cognitiv’s proprietary data assets to provide marketers with custom, autonomous deep learning algorithms tailored for their individual brand KPIs. The algorithms then self-optimize to predict consumer behaviors and improve advertising performance. The Cognitiv solution portfolio includes:

Cognitiv Performance

With Cognitiv Performance, a marketer’s neural networks choose the impressions that will meet or exceed the KPI goal. Cognitiv implements and manages the entire campaign leveraging first-party data and evaluating impressions based on the desired KPI to drive greater ad efficiencies and deliver vastly improved ROI at scale.

Cognitiv Audience

A marketer’s neural network scores users and creates custom audience segments.  These segments can be pushed to any DSP or DMP and then compared against other audience segments to see the dramatic difference in results. Cognitiv Audience also leverages first-party data to effectively and efficiently identify high value users. The solution features a simple, quick activation within DSP or DMP environments with daily updates.

Cognitiv Search

Marketers can optimize Google Ads campaigns in real-time with the first-ever deep learning search optimization platform. Cognitiv Audience helps marketers better reach their target audience, and obtain insights into what is working and what is not. This solution automates and optimizes bids in real-time based on internal goals (CPC, conversions, revenue, etc.) and external factors (time of day, weather, location). Creative can be adjusted based on performance, location, and other metrics.

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