Smarter Data Management Helps Retailers Compete

Chain Store Age recently spoke with Hiro Yoshikawa, CEO and co-founder of Treasure Data. He discussed how a new level of customer data analysis can improve the customer experience.

How has unified commerce and digitally influenced retail stepped up the game on data management?

The vision for a unified commerce platform opens up a fire hydrant of data from so many different channels — online, mobile, offline, first-party, partnered data — that it forces retailers to get much smarter about finding out which pieces of data are the most symbolic of their customers’ choices. Now the challenge is performing that customer data analysis at the speed of e-commerce — and making a relevant recommendation before the consumer’s attention is stolen away.

What needs to be in place for retailers to harness — and learn from — incoming big data?

Learning from the data and capitalizing on it are two different things, of course.

Most data analytics platforms still require a data scientist, or even an entire data science team, to separate signal from noise, make sense of all the customer data, and turn that into decisions. These can be everything from design changes on the e-commerce site to what products are displayed together in physical store planograms. We designed the Treasure Data platform so the most useful data bubbles up to the top, giving any decision maker in the organization real-time access to that meaningful information.

For retailers to survive and thrive in a given market, they must be able to nimbly interpret customer data and use it to innovate the customer experience. Physical retailers need to come up with novel ways to reinvent the shopping experience through faster delivery, special deals, unique services, greater personalization, and creative digital marketing strategies. They need the mechanisms in place to drive action at the corporate level, and implement quickly, uniformly, and on brand, at the store level.

“Learning from the data and capitalizing on it are two different things, of course. […] For a retailer to survive and thrive in a given market, they must be able to nimbly interpret customer data and use it to innovate the customer experience.”

Where do retailers still struggle when it comes to data management?

Large, legacy retailers are all struggling to adapt to the challenge of Amazon and companies born in the digital age. Shopping habits have changed, and the new breed of retailer manages large volumes of data over a robust online infrastructure to innovate even in unseen parts of the organization, like delivery staging and supply chain.

What role does artificial intelligence (AI) play in helping retailers compete?

Using Treasure Data’s Customer Data Platform, retailers can combine online browsing data and in-store purchase history to develop a complete, anonymous customer profile. Joined with real-time store inventory data, they could use AI and machine learning to make personalized, predictive algorithms around purchase intent. AI could then automatically execute data-driven incentives like personalized coupons and timely, well-targeted in-app push notifications, at the moment when the customer is considering buying a specific item, and where to get it.

How can Treasure Data help retailers achieve their data management goals in this new digitally driven landscape?

Treasure Data can help retailers reposition themselves, even internally, as a modern, data savvy organization. We can process more than 8 million web and mobile events per day and analyze more than 3 billion transactions per year. By delving into processes like browsing behavior and app usage, we can help retailers bridge the gap and find out what their customers truly want.

We can help increase sales revenue by unifying customer data from any number of channels, and performing deep analysis of that data. For example, we’ve helped a 650-plus-store global retailer push the frontiers of innovation with strong growth in core retail operations, including bedrock key performance indicators like same-store sales. This brand has proven that in-store traffic and revenue can increase with a strong understanding and use of customer data.

Treasure Data’s Customer Data Platform gives retailers the ability to obtain data instantly and use this understanding of online consumer behavior to drive offline shopping purchases.