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Is Covid-19 Stymying Retail’s Intelligence – And Making AI More Critical Than Ever?

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By: Bryan Pearson |

Posted on July 15, 2020

Covid-19 Is Testing Retail Intelligence. Will Retailers Pass?

The question came to mind after reading this statement in an article by the CEO of AI firm Daisy Intelligence: “These turbulent times only reinforce the importance of being able to plan for the future based on the dynamics of retail rather than what has happened in the past.”

In short, Covid-19 is causing consumers to change their once-predictable purchasing behaviors dramatically, and in doing so it’s undermining the traditional statistical modeling retailers use to help frame their inventories, merchandising and marketing.

Should the models rise to the occasion?

Only if in-the-trenches retailers – scrambling to adjust to hairpin changes in shopping behaviors while implementing safety protocols – can find the bandwidth to rationally invest resources into AI’s prediction-enabling technologies while acknowledging the dynamics are changing.

They likely have little choice. Covid-19 is proving that retail artificial intelligence and complementary technology is more than a nice to have, even short-term. And in the long-term, it will be non-negotiable – and costly to ignore, largely because it presents such an opportunity to embrace the next wave.

It’s Up To Retailers To Learn How To Use It

This is because traditional methodologies may not be enough to fully break down what is happening in the weeds of consumer behavior right now. More advanced tools like AI can help retailers identify and understand outlier behaviors and subtle changes that could make the long-term difference between remaining relevant and connected to customers or missing the cues that are part of the “new normal.”

The challenge for retailers, as Daisy points out, will be applying the data in an adaptive manner – starting with what they have, and then testing and learning as they go.

Artificial Intelligence Can Eliminate A Lot Of Pricey Unknowns

Retail traditionally relies on predictive models using historical information and behavioral data to analyze and identify purchasing trends. This information helps them prepare for what shoppers will be looking for, which manifests in good inventory management, more relevant marketing and more accurately personalized promotions.

The hitch is that Covid-19 has shifted some foundational areas of retail that benefit from traditional statistical modeling:

  • Retail supply chains are scrambling. An entire shopping season was lost and the operating model is completely different in terms of the balance between e-commerce to physical retail. Retailers are struggling to find that settling point while reopening stores in the midst of a new season – and they aren’t getting a lot of lead time to do so, which puts more stress on their supply chains. What do retailers reopening now do with all that spring inventory? How do they price it?
  • Purchasing behavior has become erratic and will likely continue to evolve as we enter this new normal period, so future activity will be far less predictable.
  • This unpredictability doesn’t only alter shopper behavior. It also changes how retail competitors respond to the crisis as they face these unprecedented circumstances. And as they try to navigate these times, the present and future may not look like the past.

All of this means that reliable shopper data is hyper-critical, and yet the amount of change makes it even more challenging to analyze.

Some Retailers Are Integrating AI During Covid-19

The retail industry was never one to turn down a challenge, however. Let’s break down these Covid-19-instigated data hurdles and see how AI can help resolve them, with some examples.

Restoring shopper confidence. If retailers can get the new data to understand shifting consumer trends, they can likely ease customer anxiety and boost brand confidence. Beauty chain Ulta, likely recognizing its customers missed the experience of using its in-store product testers, began promoting its GLAMlab digital tool, so users can virtually try on thousands of beauty products. Yes, it’s a customer-engagement strategy, but it also can gauge how consumer interactions are shifting so that Ulta can address underlying and hard-to-identify trends.

Linking supply chains to that unpredictable shopper. As long as the ramifications of COVID-19 are uncertain, consumers will feel unsure about their needs. These emotions lead to unpredictable purchase behaviors not only in terms of what shoppers buy, but how they buy it. Online purchases by first-time buyers rose 76% at traditional chain stores in April 2020 over April 2019. To make sense of this information, the incoming data sets have to change. AI is the perfect way to model and identify critical behavior outliers in ways that can uniquely provide the insights in these uncertain times. Companies such as Amazon -1%AMZN and Walmart WMT +1.1% are likely bolstering these efforts.

Preparing to reopen on a dime. Some early investors in AI are benefitting now as they strategize about safely reopening locations. Starbucks SBUX +3.7%, having introduced its “Deep Brew” AI program in 2019, tapped into its predictive analysis to decide which stores were the safest to open early and to support its mobile ordering, cashless payments and contactless receipt strategies. Starbucks also uses the data for scheduling and inventory, which it will automate for each restaurant.

AI Can Help Restore Shopper Confidence

The question retailers and suppliers should pursue in the midst of any behavior-altering crisis isn’t what shoppers will do next week. Instead, they should point their AI partners toward the predictions their models can produce based on past behaviors during crises or how AI can support the traditional algorithms by focusing on very specific problems in the retail ecosystem. This is where AI can really earn its keep.

Yes, as long as shoppers are unsure of their futures, they will be unsure of their shopping lists. But people also really want solutions. Those retailers that make sensible suggestions and find ways to acknowledge the underlying challenges consumers face are more likely to build the kind of confidence that entrenches their brands positively to build for the future.

Bryan Pearson is a Featured Contributor to The Wise Marketer and currently serves as a director and strategic advisor to a number of loyalty-related organizations. He is the former CEO of LoyaltyOne.

This article originally appeared in Forbes. Be sure to follow Bryan on Twitter for more on retail, loyalty, and the customer experience.