Kelly Nickerson

Epsilon’s Retail Strategic Consulting practice counsels clients on CRM and loyalty strategies that help drive profitable growth. Advising on best practices to optimize customer acquisition, retention and personalization, the team helps clients navigate through customer-centric transformation. This Meet a Marketing Expert series is designed to pull the curtain back on new viewpoints from across Epsilon, its affiliates and partners, on deepening customer intelligence and implementing programs with impact.

In the second part of this series, Kelly Nickerson, Vice President, Retail Strategy & Analytics sits down with Mark Sucrese, Vice President, Machine Learning and Marketing AI at Epsilon to discuss what brands should be investing in and how they can implement new machine learning and AI capabilities.

Meet Mark Sucrese

We often work with Mark to devise approaches for the automated gathering and synthesis of customer intelligence. In his role, Mark focuses on marketing technologies and solutions with emphasis on machine learning, 1-to-1 personalization, big data, analytics and best-in-class digital innovation technologies like Artificial Intelligence (AI). He oversees critical partnerships with industry leaders in the software arena with an eye to helping clients achieve their strategic goals via actionable test-and-learn methodologies. Mark’s team helps Epsilon clients become more insight-driven and innovative with an agile crawl-walk-run approach to implementing new machine learning and AI capabilities that can scale for growth.

Machine learning and AI are hot topics with clients today. What are your particular areas of interest?

Anything on the bleeding edge of martech innovation including blockchain, dynamic content, virtual and augmented reality, cognitive computing, neural networks, bots, voice/retina recognition, and sensory-driven applications.

In our lab environments at Epsilon we employ a variety of technologies to help clients prepare to move towards a new AI-first type of world including Google TensorFlow, H2O, Sidekick, FB messenger, Siri, Cortana and Alexa-type voice and messenger BOTs, among others. Apps are being edged out in favor of voice and sensory response design. For example, we’re looking beyond the smartphone to ‘conversations’ with your earbuds in which an ad campaign might be relevantly inserted.

All of that being said, fast media messaging needs to be highly relevant and more effort needs to be put towards eliminating noise.

What should retailers be investing in?

Not just retailers, but companies in general, need to invest in three critical pillars to advance their machine learning and AI capabilities:

1. Data: We go through a strategic data road mapping exercise to identify where data lives and how it needs to be structured to enable machine learning. If you are trying to sell shoes, you might not need call center interactive voice response (IVR) data, for instance; but if your product is Term Life insurance, that would be critical data needed for a customer service rep to deliver the right message. There is a taxonomy and metadata identification process to assess attributes (for clothing, say - size, color, fabric, texture, silhouette, photograph style) to facilitate the learning. H&M actually has a nice chat bot where you can photograph an item of clothing you like and it can respond with a product recommendation for you.

2. Content: Ecommerce sites and marketing outreach mostly deal in static images today, but retailers need to move to a more dynamic nature of serving video and imagery that’s closer to real-time. Richer content and libraries for advanced messaging systems are required for on-the-fly assembly of the ideal message at the ideal time. Robust digital asset and content management are key.

3. Technology: Machine learning and AI technology in lab/factory innovation setting, with the right skills to proactively unearth (and action upon) insight.

Build the plane and fly it simultaneously, as they say.

We see retailers adapting to change in many ways. What business process and organizational evolution do you think they should prepare for?

There will be new roles in the future that don’t exist today that retailers and other businesses need to anticipate. For example, the Citizen Architect, sitting on the fence between the business/marketing function and IT. The Citizen Architect is able to effectively translate use cases into IT requirements.

Middleware layer Business Scientists will help IT create algorithmic models and rule sets that incorporate unstructured and big data while Content Librarians will manage democratic data taxonomy and metadata for more agile group sharing of distributed information-to-insight.

Machine Learning analysts and strategists will synthesize factory business insights for growth in a rapid test and learn environment. They will facilitate quick-turn recommendations for product development, inventory movement, pricing, new content and revised messaging; if the machine suddenly learns that everyone in Boston is clicking and convert on the color green, for example, that could be big a strategic opportunity.

Traditional campaigns and segmentation fall away as we move towards singular recognition of individuals in context of a particular need state at a particular touchpoint. Accurate identity recognition and interaction in context is critical. Epsilon’s digital media arm, Conversant, is leading the way in leveraging the digital data layer for audience message governance; we are moving together in the march towards machine learning optimization.

There are so many great sources of information out there today. What kinds of publications do you like to read?

I enjoy Fast Company, Forbes, Inc., Wired, Ted Talks and NPR’s newsfeed. I love The Rolling Stone, too. With two kids in college, staying abreast of youth culture and technologies that influence them gives me a lens into their fast changing world.

Work-wise I regularly follow news and publications from Forrester, Gartner, SiriusDecisions, Econsultancy, Harvard Business Review, eMarketer, Google Think and IBM Watson.

We do a fair amount of work in the airline, cruise ship and vacation destination space – Skift.com is a great provider of news on emerging and fringe technologies for the travel industry. Skift means ‘shift’ or ‘transformation’ in Nordic language, they have a unique perspective on defining what the future of travel might look like.

What is life like now outside of work?

Being an empty nester, I get a chance to shop and eat out a lot more. I’m enjoying the retail shift to experiential marketing and seeing how stores, restaurants and other high-touch interaction business models are rethinking how they go to market. It’s no longer ‘build it and they will come’, but about engaging customers with unique experiences in the physical location. It’s interesting how the ‘human channel’ is now being engaged actively as part of digital marketing’s reach, leveraging data for ‘brand ambassadors’ to recognize and personally service customers as part of their journey. I find being in the mall can be fun now, especially during the holidays.

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