How Generative AI Can Revolutionize Retailer Competitive Insights
Generative artificial intelligence (AI) has brought the retail industry and several other sectors of the U.S. economy to the cutting edge of innovation, delivering disruptive tools with the promise of far-more-powerful insights and applications.
As exciting as that may seem on paper, the impacts have had the opposite effect in the real world, with many retailers recoiling at the notion of generative AI, often due to limited knowledge about it and possibly even less trust in it.
Still, generative AI for retailers — when paired with the right shopping and transaction data — can offer extraordinary new ways to analyze, interpret, and understand the competition, share of market, share of wallet, consumer behaviors, shopping trends, and so much more.
With that, generative AI could offer retailers far more effective forecasting tools, giving them a stronger grip on the future, rather than anchoring them to past performance.
Here’s how.
What Is Generative AI for Retailers?
To understand the power of generative AI for retailers, it’s crucial to know the ins and outs of this innovation.
Specifically, retailer generative AI refers to AI-powered tools designed for the retail industry to:
Accept user inputs: Retailers can enter data, ask questions, or key in prompts to get started.For example, retailers could enter a query like, “Did consumers spend more over Black Friday 2023 or Black Friday 2022?”
Create content as a “response”: Using text, visuals, sound, and/or other data inputs, generative AI tools can assemble an “answer,” delivering all-new “results” in any medium requested. For instance, the output to the above query could include written paragraphs, bar graphs, and other “results,” depending on the entry.
While generative AI cannot devise brand-new, never-before-seen solutions or concepts for retailers, it can generate novel outputs and near-instant results, based on vast inputs and datasets.
That’s why retailer generative AI is poised to shake up the industry, with real power to change the big winners and losers in the coming years.
What Retailers Need to Know About Generative AI: 4 Key Facts
Retailers that know and take advantage of the following can make the most of generative AI now, strategically applying it to catch up to or outpace the competition faster and more effectively than was otherwise possible.
1. With retailer generative AI, data quality is crucial.
GIGO — garbage in, garbage out — isn’t just a rule of thumb for computers and math.
It also applies in retailer generative AI, as these tools can only generate insights as reliable as the data they’re provided.
In particular, the latest AI-powered data tools don’t pull data out of thin air or improve data quality.
They can only play with the hand they’re dealt. If that hand includes poor-quality data, the results won’t be as insightful or powerful as they could be if more comprehensive, higher-quality data sets were input.
2. Ignoring generative AI could kneecap some retailers.
Fear of new tech, learning curves, and even misconceptions about what it actually takes to implement innovative tools are just a few of the reasons some retailers may thumb their nose at generative AI and the next phase of the data revolution.
Others may worry about busting their budgets or having to siphon off the little-to-no resources available to get up to speed AI-powered data tools.
No matter why some retailers don’t get onboard, the reality is that:
Retail titans are already embracing AI tools, cutting-edge analytics, and future-focused data. That includes industry powerhouses like Target, Lowe’s, and Walmart. It’s also true for ecommerce giants, like Amazon.
Yesterday’s tools simply can’t keep up. Simple tools of the past have done a lot to get retailers to where they are now, but they won’t be as competitive moving into the future if they refuse to acknowledge and attempt to keep up with generative AI.
Procrastinating the adoption of generative AI could backfire in a big way in the big picture. With major retailers generally onboard with generative AI, those who fail to adapt and figure out how to leverage this innovation could be left far behind when it comes to understanding customer shopping trends, dialing into competitive insights, and really understanding the market and where it's going.
Additionally, it’s important to understand that traditional data analysis for retailers has focused on internal data related to a business’s customers, transactions, inventory, and more. Moving into the future, retailers that enhance their internal data with external data could gain far more profound market insights while also effectively tracking and monitoring the competition, consumer behaviors, and more.
3. Retailers don’t need teams of analysts to unleash the power of data and generative AI.
Accessibility is at the core of generative AI, offering unprecedented access to extraordinary data insights. For retailers, that means that specialized professionals are not inherently necessary for leveraging generative AI tools and the near-infinite insights they could provide.
Instead, with distinct inputs regarding shopping behaviors and card transaction data, retailers can put nearly any staff member in the data analyst “chair,” as generative AI will deliver composed answers that can incorporate near-real-time data. The outputs are not typically technical spreadsheets or obtuse datasets that only a trained eye could decipher.
On the contrary, generative AI can function sort of like a search engine in that a user inputs a query or prompt.
Those prompts could pertain to:
Niche sectors of the retail industry
Specific competitors, called out by name, like “Amazon” or “Walmart”
A general type of competitors, like “big box stores” or “grocery stores”
A customer base generally or specific segments of it
Specific geographic regions
Spending over certain periods of time, like Black Friday or Prime Day
When compared to data analytics of the past, generative AI has simplified and expedited the process of gleaning insights while also offering the potential to uncover far deeper connections — without having to hire data analysts to get the job done.
4. Generative AI could help retail Davids truly compete with industry Goliaths.
With consumer spending and card transaction data, generative AI for retailers can put smaller, newer, and niche retailers on an even playing field with the big dogs in the industry. With extraordinarily powerful generative AI tools already making waves — like Mobius from Facteus — it’s possible to turn the tables and:
Make faster, better decisions informed by near-real-time data.
Stay ahead of shopping trends and consumer demands, getting a leg up on inventory and sales.
Better understand the customers for a given retailer, shopping holiday, or sector of the market.
Remain agile, competitive, and at least a step or two closer to (or ahead of) the competition.
Take control of the most advanced tech and tools available to devise better strategies and solutions for the challenges of today and tomorrow.
While artificial intelligence has been disruptive and possibly even unnerving for many in and outside the retail industry, the truth is generative AI paired with robust card transaction data could be many retailers’ secret weapon for goal-shattering success in 2024 and beyond.
