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Make Good Choices: 5 Ways to Evolve Your Retail AI Strategy

A robot inside a computer screen helps a woman with a wheeled cart shop as part of retail AI strategy.
Your retail AI strategy needs to boost the customer and employee experience for generative AI initiatives to succeed. [guoya | Getty]

Whether expanding AI initiatives or testing out new capabilities, the retailers we talked to are shoring up their CRM and data initiatives first.

Generative artificial intelligence (AI) has been the fastest-growing consumer application of all time, and retailers are quickly seeing its business value. Some of you are looking for bottom-line improvement, some of you want top-line growth. But everyone agrees your retail AI strategy needs to impact both the customer and employee experience if you want these initiatives to be successful. 

Where is your organization in this AI-powered world? Are you running, walking, or crawling? We spoke with dozens of executives and surveyed 1,390 retailers globally to see how they are using AI. They’re focusing their time and resources on several key areas that help them grow revenue and build relationships.

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Focus on the customer and associate experience

The best place to experiment with generative AI is to address issues you already want to solve. Half of the retailers we surveyed said the main focus of their retail AI strategy is the customer experience. So first think about what your customers need and whether AI could help you deliver it. Identify processes where friction, inefficiency, or a lackluster experience need to be addressed.

For most of these sticking points, you probably already have initiatives in place, along with budget allocations. How can you apply AI to help solve those problems more efficiently and at scale? By tying AI into existing initiatives, your retail AI strategy feels less like starting at square one and more like fast-tracking known issues that have proven tough to solve.

What you can do: Prioritize trust and the retail experience over the tech stack and practical skills. Successfully deploying AI isn’t about solving everything with the click of a button: To realize AI’s true potential, first use it to understand your customers and employees, then to enhance those relationships.

Make data the bedrock of your retail AI strategy

Retailers must get their data house in order. ChatGPT’s power comes from analyzing all the data across the internet. But the most important data for optimizing AI is within your own four walls. 

The challenge? Most retailers told us they’re still trying to harness the power of their own data: 54% of retailers are not fully able to use data to effectively deploy generative AI. In fact, 60% of retailers are not fully able to use data to make decisions. 

Over time, you’ve collected reams of data about your customers — shopping preferences, purchase history, service inquiries, marketing messages, interactions with your loyalty program. That trusted data is the key to personalizing customer interactions and increasing profitability and lifetime value. To optimize AI, first break down silos and unify your data across the entire organization so everyone can securely access it. Then be sure your AI is goverened by security guardrails and ethical policies.

What you can do: Use enterprise data within your four walls. You’ll use this data to train your AI, so the more comprehensive, accurate, and trusted your data is, the faster the AI will learn and the more accurate its recommendations will be. Most importantly, using first-party data — managed within your organization — helps maintain your trust with customers.

Embed AI in the workflow

Retailers don’t want yet another user interface for their in-store or back-office employees to toggle. Our research shows that, on average, retailers use 44 systems to manage customer engagement, and store associates access 12 systems on a daily basis. That’s anything but efficient. 

Retail executives estimate 36% of their employees are already using generative AI and expect that to grow to 45% by the end of 2025. Not surprisingly, 64% of retailers plan to use existing applications and user interfaces to access generative AI. Instead of creating another interface, embed AI in your existing workflow. This will help deliver excellent experiences for shoppers – and in-store workers – throughout their journey. 

What you can do: Ask yourself and your team which processes are slowing down employees and store associates. What interactions with your website and stores frustrate consumers? The answers to those questions will point to key workflow challenges, which are ideal starting points for smart deployment of AI. 

Keep humans in the loop

Generative AI will not replace your workers, but it will make them more productive. It will also help you humanize every engagement in the shopping experience – both digitally and physically. For example, store associates will continue to build personal connections with shoppers in your stores. But AI can help you add human interactions across other channels, whether shoppers are browsing, comparing prices, making a purchase, or returning an item. 

Additionally, AI can take care of rote tasks and busywork to free up employees for more strategic and value-added work, empowering them to do more at scale. Employees can find creative solutions to complex or unique problems. They also bring expertise to vetting the recommendations made by AI for accuracy, ethics, and emotion. This helps create a consistent retail experience where everyone is speaking in the brand voice. The result? More sales at better margins. 

What you can do: As AI helps evolve the role of employees, keep in mind that it will require new skills of your workers. Be prepared to train store associates and home-office employees as part of your AI retail strategy, an investment that will improve the customer (and employee) experience, as well as the bottom line.

Prioritize practical use cases

Simple use cases that help you meet existing business objectives make for quick wins and immediate ROI. For example, give a nod to predictive product recommendations: Over the last 12 months, 13% of all online sales were influenced by product recommendations generated by AI. 

You’ll find value in simple tasks that improve the customer experience. Build an AI-powered solution that addresses a single customer pain point. Once it proves successful, use those learnings to continue building out your retail AI strategy to solve existing challenges.

Our research found retailers believe the top practical uses of generative AI include composing personalized responses for service agents (32%), creating a digital shopping assistant to help customers find a product (30%), creating personalized promotions for loyalty members (27%), and producing creative assets (26%).

Still not sure where to start? Look at areas where both operational efficiency and customer experience can benefit. These often are areas where employees are in the loop to confirm, verify, and validate AI’s recommendations:

  • Try marketing functions like automated email content creation or audience segmentation 
  • Beef up commerce with SEO-boosted product descriptions, personalized product feeds, conversational commerce, or a commerce concierge 
  • Round out customer service with human-sounding (but GPT-generated) responses, automated work summaries, and search answers
  • Increase sales with opportunity suggestions, sales bots, and email generation

What you can do: Test and learn with generative AI. Find a simple use case for a targeted pilot, then try, test, tweak, and evaluate before undertaking company-wide deployment. 

Get ready for more AI in retail 

AI can be a helpful tool for retailers looking to improve their efficiency while amping up the customer experience. To do it right, start by unifying all customer data across your organization, then build a secure AI model that masks your customer data and operates ethically. 

To seize the many opportunities of generative AI, be thoughtful and deliberate in your retail AI strategy. Look for initial use cases that are straightforward, already on your radar, and will immediately improve engagement of employees and customers.

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Michelle Grant
Michelle Grant

Michelle Grant is a seasoned researcher who helps global organizations build the future of their business. At Salesforce, she blends data and analysis to create thought provoking content that helps companies understand how new technologies will impact the future of their business.

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