Interview: AgilOne Delivers Customer Happiness via Predictive Marketing

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Predictive marketing uses machine learning to give marketers powerful insights into the customer experience. AgilOne seeks to take this machine learning and combine it with human intelligence to satisfy customers and boost  revenue. We sat down with Dominique Levin, CMO of AgilOne, to find out more.

insideBIGDATA: Predictive marketing is a relatively new arena for data analytics. What can marketers learn from data scientists?

Dominique Levin

Dominique Levin: Data scientists can teach marketers that analytics is the key for gaining deep insights into what your customers want which ultimately leads to long-term, profitable relationships. What a business learns about a customer might make them shift marketing tactics, overall policies and best practices. Also, today’s marketing landscape has also changed. While data scientists and a technical degree may have been required to decipher customer data in the past, the modern marketer can leverage easy to use predictive marketing technology without the help of IT.

insideBIGDATA: What are AgilOne’s products and services in this field and what sets you apart from the competition?

Dominique Levin: AgilOne is a cloud-based predictive marketing platform that makes advanced analytics and predictive targeting easy for all marketers large and small. We believe all marketers have the right to deliver happiness. Unlike offerings from large vendors such as IBM and Adobe, AgilOne is easy to install and easy to use. It is the only integrated platform that combines data integration (omni-channel customer profiles) with advanced predictive analytics and out of the box predictive marketing campaigns (actions).

insideBIGDATA: Which vertical markets does your company currently serve? What other markets might you see as viable?

Dominique Levin: Predictive marketing is relevant to anybody who serves a large number of customers so we like to say that we serve the “b-to-many” market. Today, AgilOne predominantly serves the retail market. Retailers are really ahead of the curve in terms of analytics adoption, and our typical customers triple their margins, grow overall revenues by 30 percent, retain 20 percent more customers, cut email unsubscribe rates in half and grow email revenues by 125 percent.

insideBIGDATA: Can you talk a little about the underlying technology your company employs?

Dominique Levin: Some of the secret sauce of AgilOne includes:

  • Self-learning predictive algorithms that automatically adjust from customer-to-customer and from time-to-time. We don’t need to do any custom algorithm development and this allows us to scale to a large number of customers.
  • We have a Hadoop based technology stack that allows us to handle very small and very large customers. Our largest customer is serving 425 million consumers and we collect, analyze and act on all customer behavior for these consumers.
  • A playbook of built-in campaigns that are push button. This way any marketer can deploy predictive without having to know any analytics or data science. For example, a marketer can launch with a single click a campaign aimed at reactivating customers at risk. “At risk” is calculated automatically and the reactivation offer may include content personalized based on “cluster analysis”.

insideBIGDATA: Many see predictive marketing as the future of marketing. What’s the future of the future?

Dominique Levin: While predictive is the future it is certainly not futuristic. In fact, what is most often misunderstood about predictive is that it is making targeting easier, not more complex. Predictive is offering automatic segmentation and targeting that is often replacing rules based systems. Nevertheless, the next step is to apply these insights in real-time, no matter where we are – in the store, on the phone, on the go (mobile). We finally see a true integration of digital into our physical world: we will interact with the mirror in a store and our phone will tell a store clerk what clothes we like. The internet of things is becoming a reality and there are more and more data sources to analyze and turn into an awesome experiences for us all.

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