Teradata Universe Report: How BevMo! Moved Toward CCPA Privacy Compliance

The Teradata Universe conference, held Oct. 20-24, brought together 3,200 attendees in Denver to gain greater insights into data analytics, along with practical examples of how they can be applied to improve business intelligence and operations. Retail speakers included executives from Meijer, Mercado Libre, Rakuten, Loblaws, and Nordstrom. Additionally, analysts and academics discussed a wide range of topics, such as the multiple ways AI can enhance marketing campaigns via personalization and real-time reactions to digital advertising.

How BevMo! Protects Customer Privacy

The California Consumer Privacy Act (CCPA) is scheduled to take effect on Jan. 1, 2020, with enforcement beginning six months later. The law will have significant impacts well beyond the Golden State, since the CCPA jurisdiction applies to any company doing business with California residents. The law includes low minimums for the number of customers and amount of revenue generated to trigger the CCPA’s application, according to Jay Irwin, Director of the Center for Enterprise Security at Teradata. “Companies will need to be able to tell these residents where they got their data, who they bought it from, what they are planning to do with it and who they are going to sell it to,” said Irwin during a session.

{loadposition GIAA]Additionally, gaining a consumer’s consent will be mandatory, and companies will need to be prepared with a 12-month “lookback,” to show not just what they are doing with consumer data now but what they did with it during the previous year. Companies can be fined up to $750 per person for CCPA violations.


BevMo!, a 164-store wine and spirits retailer with a thriving e-Commerce business, serves more than four million customers per year, according to Jayson Pritchett, the retailer’s Senior Director of IT. The retailer’s preparations for CCPA compliance have included significant data mapping.

“Our touch points include our web site, call center, retail stores and mobile, and we also work with third-party aggregators,” said Pritchett. “That consumer data usually isn’t in sync in terms of elements such as who else is in the customer’s household, social media identifiers and contact preferences, and the disparate systems aren’t always talking to each other.

“We knew our current customer master data wouldn’t solve all of these issues, and that we needed more real-time integration,” Pritchett added. “We needed to consolidate our customer data into one touch point so that we could manage it from start to finish.”

Prep work included identifying and defining what types of personal data were within BevMo!’s systems. “We had to map our systems for where data is sourced and stored, and who is collecting it,” said Pritchett. The retailer also had to integrate with second-party and third-party vendors to determine what they needed in order to come into compliance with both CCPA and GDPR, he added.

BevMo! has taken a key preventive step: encrypting any data that could identify an individual customer. Using encryption protects companies from being sued in civil court in the event of a data breach, according to Irwin.

Irwin advised companies to be proactive with their privacy protections. “There are nine states besides California that are looking at similar legislation, and I predict that within 10 years or less there will be 49 or 50 CCPA-style laws,” he said. “It’s good advice to pick the [law] with the strictest restrictions and stick with that.”

What AI Can And Can’t Do To Enhance Marketing

Using AI and machine learning in marketing can have a significant impact, but for retailers to apply them successfully, they must align deployments with key business objectives and consumer pain points.

“AI use cases in marketing include identifying the ‘next best’ experience,” said Brandon Purcell, Principal Analyst at Forrester, who spoke at a session titled, How AI Will Change Marketing Forever. “It’s about bringing together the right customer at the right time with the right message or experience. AI can identify which customer has a strong propensity to buy, as well as which ones have the highest risk of churning, and it can use factors such as products that are frequently bundled together or what this customer tends to buy.”

However, the session panelists warned that because AI and machine learning applications are both data- and resource-intensive, retail marketers should use them strategically. “There are lots of places to potentially ‘throw’ AI, but companies should ask themselves some questions before they do,” said Felipe Thomaz, Associate Professor of Marketing at Oxford University’s Saïd Business School. “Would it be valuable to use AI in this context? Does my consumer want this? Can I get a competitive advantage by predicting the ‘next step’? And, do I have the assets and people that I can bring to bear in order to make use of it? Many systems, and the data within them, aren’t yet organized to work with AI.”

AI can be extremely effective in marketers’ personalization efforts, according to Purcell: “AI-driven personalization focuses on the customer,” he noted. “Some solutions have tools to consistently tag experiences and see how they have worked with micro-segments of a customer base.”

Both Purcell and Thomaz predict greater use of AI and related technologies in honing marketing campaigns. “There’s a lot of work being done in digital content optimization, where every aspect of a digital ad gets organized to optimize lift and potentially, conversion,” said Thomaz. “It can all be generated in real time, and it involves the connection of a significant amount of data about the consumer; contextual information from the web site they are visiting; and a powerful tech stack that can generate as many as 30,000 to 50,000 different iterations of the same ad.”

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