TechBytes with Steve Zisk, Product Marketing Manager at Redpoint

Tell us about your role/team you handle at Redpoint. What inspired you to join the company?

My team at Redpoint handles Product Marketing, which means we get to translate the complexities of a feature-rich, broad, and deep engagement hub to buyers, users, and gatekeepers. That kind of “technical evangelism” was one part of what drew me to Redpoint, and the other part is the people.

The passion, depth of experience, and focus on client success in every part of our organization is a great reason to come to work… even now, when work means my home office!

What is the most contemporary definition of Customer Data? 

Customer data is all of the signals, both direct and subtle, that tell an organization what path the customer is on. Transactions and interactions, life changes and aspirations, and their expectations of your brand. Those signals are not just in the obvious sources like POS systems or web visit statistics but also hidden in social posts, household buying habits, or even in time-of-day for opening emails.

It’s crucial that customers be consulted and informed about the data a brand collects, how it will be used, and what they will receive in return for their consent to use data.

Tell us more about the engine driving predictive intelligence to “Determine Next Best Actions.”

There are three things to think about when it comes to predictive intelligence and determining best actions:

1. Next-Best-Actions (NBAs) are not simply an attempt to drive a customer to buy the next thing. Instead, they must recognize the customer journey in the customer’s own terms: discovery, exploration, aspiration as well as loyalty, transaction, promotion.

2. An NBA “engine” is only as good as its data “fuel,” so data scientists have been focusing huge amounts of time and energy on data preparation, measurement, and optimization. The best systems automate as much of that as possible to let the experts focus on the premium parts of the job: modeling and experimenting.

3. The user of the NBA engine is not a scientist, but a marketer! Given that, it has to be automatic and easy to deploy, measure, and improve NBA models.

How is Redpoint’s CDP different from other CDPs? What makes CDP product teams so dynamic in the modern context of MarTech DevOps?

Redpoint focuses on the CDP as a data engine for revenue generation. That means it will be used and managed by marketers, but has to meet enterprise standards for data control, privacy, performance, and even project management! Our platform offers all the tools marketers will use – connections, segmentation, orchestration – but also exceeds their IT requirements for security, scalability, encryption, and deployment control.

The dynamic CDP market is driven by the twin pressures of reducing friction in customer engagement and respecting customer expectations for relevance and privacy. The explosion of MarTech (over 8000 offerings in 2019) has made tracking, integrating, and managing that data in all of those places a continuing headache for Marketing teams, and the CDP proposes an answer for that: All your customer data in one place to drive all your engagement channels.

Tell us about your experience in working with AI, ML, and Big Data. Where is the CDP tech-building heading to, in the next 2 years?

I think the demand for data in the AI/Machine Learning (ML) world is a reflection of the need for better models. I work with our development teams – particularly our Automated Machine Learning group – to define that need for our clients. Accuracy, relevance, and business focus are driving organizations to invest in a more complete and consistent data science “pipeline.”

And serendipitously, Customer Data Management technologies (not just CDPs but Data lakes, Event stream managers, and Customer identity management) are now being used by CDOs to build that pipeline and deliver the insights and decisions that are needed by Marketing and other customer-facing groups. We see many other teams playing catch-up to provide a pipeline that meets the promise of real-time, ML-driven, scalable, and “bullet-proof” CDP.

Tag a person in the industry whose answers you would like to read here:

Joseph Enever, at Gartner. He covers Marketing Data and Analytics, but has a fascinating background at Carphone Warehouse and Lastminute.com.