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One Silicon Valley Insider’s MarTech Predictions

I recently had the chance to chat with CTO Madhu Therani, Head of Artificial Intelligence at Near, a data intelligence platform in Palo Alto, California. Madhu is a friend of TopRight and a fellow traveler in the world of cutting-edge digital systems and martech developments. Though his personal history is in the nitty-gritty world of…

I recently had the chance to chat with CTO Madhu Therani, Head of Artificial Intelligence at Near, a data intelligence platform in Palo Alto, California. Madhu is a friend of TopRight and a fellow traveler in the world of cutting-edge digital systems and martech developments. Though his personal history is in the nitty-gritty world of robot building, machine learning, and large-scale data analysis, he’s spent the last ten years out in the front end with public-facing tech startups building scalable data-intensive systems that can be successfully brought to market. 

With a doctorate in robotics from Carnegie Mellon University, Madhu is the type of guy you want to talk to when you have questions about advancements in artificial intelligence. His company Near provides actionable intelligence for marketing and data enrichment, offering insights that go far beyond the analysis of a few location pings, blending both online and offline data signals. Madhu’s team uses in-house tools and AI to analyze brand affinities in addition to a range of insight-rich demographics. Near is the only company aggregating this quality and quantity of data at a global scale—over 1.6 billon users in 44 countries. They take raw data signals from multiple sources, such as aggregators, wifi partners, census data, and public hotspots, and put them in context using advanced data science models

Because of his experience, unique position, and exposure to the inner workings of global-scale marketing technology, he was fairly clear-eyed about what he says we will see happen in martech in the near term. And he would know!

Data-Secure Personalized Consumer Experiences 

The year 2020 will see a blend of privacy-aware technologies in the personalization of consumer experience. In the past, personalization has always been a bit on the clumsy side, with unfortunate tradeoffs being made between efficiency and efficacy. But new developments in data analysis, privacy tech, AI, and VR are going to create compelling physical and virtual experiences like never before. Both online and offline consumer touchpoints will utilize various first- and third-party enriched and privacy-safe data gleaned from spatial, temporal, and behavioral cues. As the tech advances, there will be fewer misfires or errors and far more day-to-day normalization of on-the-spot instantaneous personalization experience. 

Data-as-a-Service (DaaS) 

Madhu and his team expect data vendors who deal in various kinds of information related to consumer audiences, geographic locations, and related entity data to start launching reliable data-as-a-service offerings. These will enable better decision-making for consumers and have the benefit of driving app economy publishers and retailers to enrich their first-party data sets and use it to drive better consumer acquisition, retention, content offerings, and project measurement. Daas will therefore become more user friendly, more affordable, and will vastly increase in quality as new data works to cleanse and enrich the old on a continuous basis.

Continuous Intelligence 

This concept basically refers to an institution’s or entity’s ability to harvest and integrate new data, processing and simultaneously using it to improve outcomes and guide operations minute-by-minute. Consumer-facing businesses will continue to generate huge amounts of data as all consumer touchpoints are instrumentalized for data collection and adaptive data use will become increasingly critical. This will lead to a leap in the ease-of-use and accessibility of not-yet popularized “smart” products such as smart mirrors, a gizmo that relies heavily and necessarily on high-quality continuous intelligence. Incorporating the data in real time to drive better decisions across the consumer journey and improving overall business processes will be a key objective as enterprises adopt continuous intelligence

All Digital Omnichannel Advertising

As modern viewers consume more and more media across the multiple channels available to them digitally, brands will integrate more digital OOH, Connected TV, and OTT television advertising in addition to their existing channels as part of a broadening of omnichannel marketing efforts across the board. This will drive adoption of programmatic advertising practices across most channels and formats with improved media effectiveness measurement across both online and offline channels in an integrated manner. No longer will omnichannel marketing simply be a matter of aligning print and digital campaigns, but of engaging consumers everywhere and unifying across all digital media with a focus on streaming networks and digital TV. 

If you want to learn more about martech or pick up some insights on branding, go ahead and follow me @TopRightPartner, connect with me on LinkedInsubscribe to our blog, or buy a copy of my latest book, Marketing, Interrupted.

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