Over the past decade, following Amazon’s lead, big-box stores and other national chains have fundamentally altered what customers expect from the shopping experience. Local and regional retailers must find ways to match the speed, personalization and seamlessness of their big-brand competitors in order to bring shoppers in the door, stem customer attrition and stay on solid financial footing – and do it quickly to avoid losing additional ground.
That requires developing three critical capabilities: an always-available, persistent memory that unifies information from every customer touch point to enable frictionless, personalized service and help turn online interactions into in-store visits; predictive purchase suggestions that reflect real-time local inventory to move customers closer to a purchase decision; and tools that assist associates on the sales floor in acting on those insights to convert shoppers into buyers.
Newer off-the-shelf retail technology solutions built specifically for mid-market brick-and-mortar businesses can deliver these and other capabilities without years of custom engineering and enterprise-sized budgets. The payoff includes fewer dropped leads, increased foot traffic, faster conversions, better upselling and cross-selling, bigger basket sizes, more repeat visits and a stronger bottom line.
Bringing Customers in the Door
The core challenge for mid-market retailers striving to offer Amazon-style service is that critical information such as customer purchase history, call center logs, chat and text records, email communications and real-time inventory is siloed in a series of databases. If a customer has been shopping for a sofa, computer or refrigerator, the merchant has no easy visibility into that individual’s search history or contact with other business touch points.
That means that every online, phone and in-store customer interaction must start from scratch, costing time, trust and sales in a world where shoppers are accustomed to being instantly recognized across every channel. It also discourages online shoppers from making the effort to visit a brick-and-mortar store, and leaves sales associates without valuable context that can help close sales when customers do walk in the door.
Retail tech that provides a unified memory infrastructure as well as product recommendations during chats or other online interactions can help draw shoppers to the physical store by answering virtually every question quickly, intelligently and in a way that’s tailored to the consumer’s specific interests. It can also strengthen sales associates’ ability to steer in-person conversations to the finish line, answer the phone, check store shelves, verify a loyalty account and convert a call into a buy online, pick up in-store (BOPIS) order.
Three Core Criteria
Many of these features are powered by AI, but not every provider can provide a comprehensive solution that covers all of these bases. Some focus on chat or helpdesk. Others lack critical unified memory or features built for brick-and-mortar businesses. A true full-stack solution offers three capabilities that are essential to achieve results. The optimal platform:
- Remembers every customer interaction. A unified technology layer treats chat, voice, text, social and in-person interactions as one persistent conversation. This eliminates the need for customers to repeat information about what they’re looking for – often creating frustration and lead abandonment – while also equipping associates with vital background that can help guide consumers toward a purchase.
- Personalizes with local inventory. Recommendations must be grounded in what is actually on the shelf, in the back room or available for same-day pickup. Lightweight predictive models that dynamically update stock information enable retailers to make personal, actionable suggestions that can help convert a conversation to a close, rather than providing generic recommended-for-you lists.
- Supercharges sales associates. In addition to furnishing insights into previous customer interactions, the best retail AI provides timely prompts, cross-sell cues and planogram reminders so that employees can be knowledgeable ambassadors, not order takers. This also increases the value of neighborhood retail, amplifying the human advantage that online retail cannot fully replicate.Â
Getting Started
If you run local stores and want to meet the modern bar for personalization, begin with pilots co-designed with store staff and iterative sprints that change one workflow at a time. Be sure to:
- Choose retail-specialist partners with full-stack solutions that focus on persistent omnichannel memory and have proven POS, loyalty and voice integrations.
- Start small, human-centered and measurable — one region, one workflow and one clear metric such as calls converted to BOPIS or repeat purchases from loyalty outreach.
- Unite identity and inventory to ensure that recommendations are real at the checkout. Use dynamic content to make outreach personal and timely.
- Operationalize consent and explainability from day one, including clear opt-ins, simple explanations for AI actions and governance for data use.
- Give associates AI that helps, not one that replaces the human touch. The best outcomes come when people and machines play to their strengths.
Remember: Amazon’s advantage was to have the vision and resources to build a memory technology layer and the operations to act on it. Today, thanks to newer technology solutions inspired by Amazon’s example, local and regional retailers can both replicate many of big tech’s abilities and adapt them to the needs of their brick-and-mortar businesses. It’s a case of beating the national brands at their own playbook – and protecting your company’s future in the process.
Evan Kubicek is the Chief Revenue Officer of AiPRL Assist, a retail technology provider specializing in optimizing the customer experience for mid-market retailers.
