Interview with Jeremy Fain, CEO, Cognitiv

Jeremy Fain
interviwes
Jeremy Fain
[mnky_team name=”Jeremy Fain” position=” CEO, Cognitiv”][/mnky_team]
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[easy-profiles profile_twitter=”https://twitter.com/teamcognitiv” profile_linkedin=”https://www.linkedin.com/in/fainjeremy/”]

“The biggest challenge for a CMO to create a comprehensive marketing solution is the walled-garden social platforms themselves. “

On Marketing Technology

MTS: Tell us about your role at Cognitiv and how you got there. What inspired you to start a deep-learning company?
I am the CEO and Co-Founder at Cognitiv. My partners and I are lucky to have strengths in mutually exclusive areas that make us a very effective team. We’ve also been close friends since we were 10.  We all started as computer science guys in middle and high school but I went off and wanted to do the business side of technology. Now, decades later, we have mutually exclusive specialties. I handle the business side of the company, Marc Hudacsko is our CTO, and Aaron Andalman got his PhD from MIT in Neuroscience and is therefore our Chief Science Officer.  We started Cognitiv because we had wanted to start a company together since high school.  Our lives went in separate directions in college but two years ago we came back together and all of us were at the right place, to quit what we were doing, and start this Deep Learning company.

MTS: Given the changing dynamic of data available to marketers, how do you see AI evolving by 2020?
Data is only getting richer and more interesting. Although the regulation of data continues to evolve, the mobile device along with the IP-addressable outdoor and television/OTT spaces is making a centralized AI for marketing much more realistic. That’s one of the many reasons we started Cognitiv. The ability to more fully describe and understand a consumer’s behavior is more complete than ever before, and that kind of data will make AI marketing tools even more effective over the next few years.

MTS: How should B2B marketers leverage “neural networks” to improve the omnichannel experience with greater authority?
Marketers, B2B or otherwise, can use neural networks to solve any discrete problem where there is a lot of data and the answer needs to be the better prediction of outcomes. The challenge some B2B marketers have is the large amounts of data required. Data strategy has been the key to success over the past decade for B2B marketing, and neural networks make that even more important now. The more data a B2B marketer can gather on its customers, its target audiences, and its omnichannel experience, the easier it will be to apply neural networks to any of the challenges they have along the entire path to conversion and the customer lifecycle. Cognitiv then takes that data, makes it easy for neural networks to consume, and pushes it through our NeuralMind platform, thus creating a neural network algorithm that is unique and specific to the problem the marketer is trying to solve.

MTS: How is deep learning different from machine learning? How does it benefit marketers?
Deep learning is defined as a subset of machine learning, but it is a big paradigm shift in the discipline.  Before Deep Learning, machines were not very good at approximating human-like insight and understanding. It is easy to see how powerful and ground-breaking Deep Learning has been to the world. Before Deep Learning, phones did not understand your voice, cars could not drive themselves, and Facebook could not auto-tag your pictures. Every day, a new innovation is now being released, powered by Deep Learning, that is making advancements in computer-led capabilities that were only science fiction a few years ago. We are entering an age of technology-enabled solutions that will drive efficiency throughout business, and every-day life, speed-up scientific discovery, and automate many manual tasks.

MTS: How do you see recent regulations in data privacy laws impacting personalized customer experiences?
Protection of consumers privacy is important to all of us. Consumers should control what business and government know about them.  However, personalized customer experiences will still be an important part of everyday life as long as they offer, at a minimum, fair value exchange. A personalized customer experience at Disney World based on what you have done during your visit, Siri or Alexa learning what you like and giving you more of that, or even enabling advertising on your favorite subscription-less site will continue to be enabled by the consumer because they offer an important benefit that enriches their lives.

MTS: What’s the biggest challenge that CMOs need to tackle to make their customer data analytics work effectively and accurately?
Data centralization.

There have been a lot of discussions about data portability. That is important because marketers’ data sits all over the place right now.  But the data has to be brought back to a central place in order to take full advantage of Deep Learning’s power. A complete view of customers’ experiences with a marketer’s site, offline experiences, CRM, advertising, etc, will be necessary for marketers to compete and be successful now. Most marketers do not centralize their data. We see this as a big opportunity for tech solution providers right now.

MTS: With growing noise across the offline, online, the web and social media, how does Cognitiv democratize disparate and complex data sets to build a singular definition of a customer?
Right now, the easiest way for us to do this is by either placing pixels in the appropriate places on the marketer’s site(s) or using a universal ID system like Liveramp’s IdentityLink.  This is not really a technical problem right now, though.  The bigger problem is the accuracy of the data being made available.

MTS: What is the biggest challenge that CMOs need to tackle to make their social selling decisions work with accurate marketing attribution?
The biggest challenge for a CMO to create a comprehensive marketing solution is the walled-garden social platforms themselves.  Without the freedom to find possible consumers and then understand their interactions with your brand at a very discrete, detailed level, those consumer interactions will remain separated from a shared data strategy. Those interactions will not be centrally enabled through the CMO’s AI solutions.

MTS: What startups are you watching/keen on right now?
Beyond marketing AI startups, I mostly keep track of augmented reality and blockchain startups. Augmented reality because I see that as the next huge evolution of the way our society integrates and works with technology. Blockchain because everyone else thinks it’s going to change the world.

MTS: Could you tell us about a standout digital campaign? (Who was your target audience and how did you measure success?)
Our Deep Learning products have enabled our client marketers to take their campaign goals to the next level. A financial services company wanted to convert more consumers, able to deposit large amounts upon opening an account.

We worked with them to get the right 1st party data from their CRM system, train a neural network to look for more of those people, and then began managing the media they bought through programmatic channels.

By dynamically valuing every impression based on the user, site, time of day, type of device, and everything else we knew about the target users and the new prospects, Cognitiv drove 20X return on ad spend for them as compared to all other campaign partners.  Deep Learning was able to find the right people with less waste, enabling the client to find more of those people with the same amount of money.

MTS: How do you prepare for an AI-centric world as a marketing leader?
Again, it’s all about data.  Today’s marketer needs to use all the data points available to them.  All the data is useful to neural networks if you have a company like Cognitiv to translate it for you.  It will be many years before most marketers have Deep Learning data scientists working for them, so putting together a centralized data set is the most important task.  Then partnering with the right Deep Learning company will give them all the advantages of AI without any of the heavy lifting.

This Is How I Work

MTS: One word that best describes how you work.
Decisively

MTS: What apps/software/tools can’t you live without?
iPhone, Google Docs & Drive, PC (not Mac) laptop, Whatsapp, Kindle.

MTS: What’s your smartest work related shortcut or productivity hack?
Block off time in the calendar on a daily basis and wait until then to get all the small tasks that build up done at once.

MTS: What are you currently reading? (What do you read, and how do you consume information?)
Chasing the Last Laugh: Mark Twain’s Raucous and Redemptive Round-the-World Comedy Tour and The Last Good Man by Linda Nagata.  History and Science Fiction.  That’s about all I read as books go.  I want to learn from the past and dream about the future.  I read everything on the Kindle app on my iPhone.  I can read anywhere at any time with it.

MTS: What’s the best advice you’ve ever received?
Always finish what you start.

MTS: Something you do better than others – the secret of your success?
I think to be successful in business you have to listen to your gut.  Often, you have to make a decision quickly with less than complete information, and your instinct is all you have.  If your gut is right much more than it is wrong, you are in the right business, doing the right thing, and you will be successful.  If it’s wrong more than it’s right, unfortunately, you should probably find something else to do.

MTS: Tag the one person in the industry whose answers to these questions you would love to read.
Sabio Mobile’s CEO, Aziz Rahim

MTS: Thank you Jeremy! That was fun and hope to see you back on MarTech Series soon.

Experienced Interactive Advertising leader with specialization in:

  • digital marketing strategy
  • audience and data-driven solutions
  • ad technology, innovation, and marketplace
  • interactive advertising policy
  • real-time bidding (RTB), programmatic buying, exchanges

Core Expertise: Revenue leadership, digital marketing and media strategy; interactive advertising revenue operations and policy; interactive product management and creation; advanced inventory monetization strategy

CognitiveCognitiv builds custom programmatic buying algorithms using the latest advances in Deep Learning. Our platform enables DSPs to offer custom algorithms to all of their clients, advertisers to build custom algorithms for all of their brands and ROI-types, and agencies to offer more sophisticated targeting solutions to its programmatic clients.

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The MTS Martech Interview Series is a fun Q&A style chat which we really enjoy doing with martech leaders. With inspiration from Lifehacker’s How I work interviews, the MarTech Series Interviews follows a two part format On Marketing Technology, and This Is How I Work. The format was chosen because when we decided to start an interview series with the biggest and brightest minds in martech – we wanted to get insight into two areas … one – their ideas on marketing tech and two – insights into the philosophy and methods that make these leaders tick.

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Sudipto Ghosh

Sudipto Ghosh is a former Director of Content at iTech Series.

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