BETA
This is a BETA experience. You may opt-out by clicking here

More From Forbes

Edit Story

5 Things Retailers And Brands Need To Know About Data In 2019

Following
This article is more than 5 years old.

Getty

There are currently more smart devices than humans on the planet. The abundance of these devices has fundamentally changed how consumers collect, absorb and share information, whether it’s data that consumers have explicitly shared or information that retailers have inferred and promoted through social networks and beyond.  It has also given retailers and brands seemingly limitless access to data to understand consumer preferences and anticipate the products and pricing they expect.

During the NRF Big Show, I had the opportunity to sit down with retail industry influencers Michael Bopp, Head of Analytics for Synchrony Financial, and Sucharita Kodali, VP and Principal Analyst Serving Ebusiness & Channel Strategy Professionals at Forrester, as part of the “ReTales from the Frontline” podcast series.

Together we discussed the impact of data as it relates to consumer experiences and retail innovation. Here are 5 key takeaways from our discussion that break down what retailers and brands must know about data in 2019.

Retailers Overwhelmed by Data Need to Keep it Simple

As Sucharita observed, despite access to limitless data, retailers and brands often still don’t know what to do with that information and how to make it actionable. She added that sometimes companies’ efforts are akin to trying to boil the ocean. Just looking at basic data about what a consumer might have purchased before and what they may be in the market for now presents some of the biggest opportunities for retailers.

At the same time, data is ubiquitous, but insights are rare. The good news is that the data that we collect on how the consumer behaves is fact-based. Retailers have the opportunity to personalize more content than ever before. The missing piece for retailers has been how to anticipate what the consumer is going to do next based upon the information that has been collected. Now, thanks to predictive analytics, retailers can leverage this unstructured data to create a structured format with insight about what happened in the past to anticipate what a given consumer is going to do next. Predictive models can anticipate the expected outcome of how products are going to perform, forecast the selling price over its life cycle and help retailers segment consumers down to a granular level.

Retail Is Connecting with Finance for Better Commerce Experiences

When it comes to collecting data on transactions and payments, retailers need to extend the entire customer journey into financial sectors, which could include applications for credit or even handling of fraud.  While there has been an unofficial wall between retail and the financial institution supporting a transaction, this is changing.  Michael noted that connecting a consumer’s financial preferences to retail can truly personalize all aspects of commerce. Data that a financial transaction can provide, such as a request for waiver on a late fee, can also be shared with a retailer, and is often critical to help them to make better decisions on how to customize and personalize the buying experience.

Journey mapping also pulls in financial elements like credit, helping retailers design purchase experiences which factor in the application process and open up new opportunities for additional purchases.  Even instances of fraud can be counteracted with machine learning algorithms that quickly confirm fraudulent transactions and help get that credit card back in the customer’s hand faster to enable additional purchases.

Shiny New Tech Has Become A Distraction

With media giving so much space to new technologies like drones and blockchain and their transformative effects on the industry, retailers are running around trying to understand how these shiny new technologies would transform their own businesses.  But they’re losing sight of what technology should be helping them to achieve right now.  Retailers need to get their heads back into the present day and understand and bolster data sources with a customer-centric model.  Sucharita mentioned that not a single retailer she knows of actively captures insights on when a shopper walks into a store and asks the store associate, “Do you carry Axe?” and the answer is “No.” Technologies need to be in place that either enable the store associate to capture and communicate that data or enable the customer to report it.  This is gold for retailers.

Humans Will Share Data with Bots if it Means Better Experiences

The question of whether a human would want to answer a bot or feed their data into a bot, versus a sales associate, also hit the table.  But it’s no longer a question of whether a machine can outperform a human. Consumers are already using this technology to share information every day. Just think about how human navigation changed with Waze, and how crowdsourced predictive models enable us to anticipate traffic levels. We’ve learned that consumers are willing to share data authentically if they know that they’re going to get something good out of it. Leaning on technology is now woven into the essence of who we are as humans, and it is only improving our overall experiences as long as it is not done in an unethical or intrusive way.

In the Race for Data, Amazon Doesn’t Have to Win

The retailer that has the most information and uses it most effectively in retail wins. Most of the time people think that means Amazon, but this isn’t necessarily true. Amazon may have half a billion products and almost as many customers, but Sucharita pointed out that 95 percent of retail in the United States is not happening on Amazon. Further, Google arguably has even more data than Amazon, but they don’t use it as effectively as it relates to consumer sales. Now new trends are emerging where the brands are taking control of the consumer. Direct to the consumer strategies like Nike’s Consumer Direct Offense leverage the power of digital and being in direct contact with consumers sheds light on big opportunities. Capturing data when consumers proactively reach out asking for things is another big opportunity that can help top Amazon at the data game. There are other solutions that consumers want and are actively seeking but the challenge is that retailers are not always good at recognizing what they have and the power it would grant them.

In the end, Michael said it best when he noted that the power is in data aggregation and stitching together all the experiences consumers have while extending these experiences beyond the store and into financial third parties. This can bring retailers more data assets and views of their customer, all while rounding out the customer experience. It’s important to keep focusing on being ahead of the curve and finding new opportunities to gather and really utilize all the data to improve the customer journey. Predicting customer desires and turning data into actionable information are table stakes for every retailer and brand.