What is Knowledge Management in Retail?

Knowledge Management in Retail Defined

Knowledge management (KM) in retail is defined as the process of capturing, curating, sharing, and leveraging knowledge in retail to improve operations across customer service, merchandising, supply chain, and store operations.

Frontline Staff Challenges

With frontline retail staff juggling ever-changing promotions, evolving product catalogs, and rising customer expectations, it’s critical that trusted knowledge is easily captured, continuously curated, and proactively delivered into their workflows to provide fast, consistent, and personalized service at scale.

Types of Knowledge in Retail

Knowledge in retail goes far beyond product manuals or training guides. Below are examples of the types of knowledge that help power seamless customer and employee experiences:

Data

How much is the current promotional discount on X product?
What is my loyalty account number?
Where is my order? (WISMO)

Policies

What is the return policy?
Do I have to pay for shipping when I return?
What is the credit approval policy for the store card?
What requirements to be a silver tier rewards member?
What is the store’s current layaway policy?

Insights

Which customer segments are most responsive to in-app promotions?
What is expected foot traffic during the holidays based on the past 3 years?
What product bundles increase average basket size?

Procedures

What are the steps to open a rewards card?
What are the steps in the returns process?
What are the steps for troubleshooting POS system issues?
What procedures must be taken when closing the store?

Expertise

What model would you recommend for my requirements and situation?
What is the best way to handle high-stress customer situations?
What are the best practices for visual merchandising in the holiday season?
How do I negotiate better pricing from suppliers?

Knowledge Management in Retail: Challenges

In retail, effective knowledge management must overcome challenges like high employee turnover, constantly changing product and policy information, and the need to deliver fast, consistent service across channels. Here are just a few of the key obstacles that can stand in the way:

Information Overload Across Channels: With SKU information and data pouring in from stores, e-commerce platforms, mobile apps, and contact centers, retail teams often struggle to surface timely, actionable insights—slowing down service and decision-making.
Labor Shortages: According to a recent report from Deloitte, labor shortage remains a core challenge. Adding to it, retailers struggle to hire and onboard seasonal agents year after year. Delivering contextual knowledge to workers to speed up onboarding and make frontline employees effective continues to daunt retailers.
Inconsistent Customer Experiences: 75% of customers say they’re more loyal to stores that deliver consistent customer experiences across channels. Inconsistencies in customer experience often arise due to disparate knowledge silos that retailers struggle to maintain.
Constantly changing policies and procedures: With product lines, promotions, and return policies frequently being updated, frontline employees are left scrambling to keep up without a modern knowledge management system.

How AI can help

McKinsey predicts that gen AI will deliver between $240 billion to $390 billion in economic value for retailers. Here are some of the ways that AI-powered Knowledge is helping retail transform their operations:

Automate Knowledge: In retail, AI-powered knowledge streamlines knowledge management by automatically generating content, spotting frequently asked questions from shopper and employee interactions, and closing knowledge gaps—so frontline staff always have timely, accurate answers.
Faster onboarding for seasonal staff: AI-powered KM systems surface role-specific guidance instantly, allowing new hires to become productive with minimal training time.
Eliminates siloed content and outdated knowledge: AI-powered knowledge management systems dynamically update content based on real-time interactions, usage patterns, and feedback—replacing outdated knowledge with accurate, context-aware guidance that evolves with business and customer needs.
Enables better omnichannel experiences: AI-powered knowledge ensures shoppers and employees receive the same trusted answers across all touchpoints—whether in-store, online, in-app, or through the call center—driving seamless experiences and reinforcing brand credibility.

Knowledge Management in Retail: Best Practices for Success

Here are the best practices for deploying KM in retail:

Find the knowledge you need:
Use AI to identify and dynamically surface the most common and high-impact customer inquiries—such as order status, product availability, return policies, and pricing. Focus your KM effort to help handle those questions first, using the 80-20 rule.

Unify knowledge in a modern KM system:
Eliminate siloed content across operations by centralizing FAQs, policies, product data, and store procedures into a structured, AI-ready, omnichannel knowledge hub—ensuring consistent, trusted guidance whether online or on the sales floor.

Embed AI-powered knowledge into core systems:
Integrate trusted knowledge into POS, CRM, and order management platforms to provide real-time support at the moment of need, reducing resolution time and increasing employee confidence.

Enable proactive, AI-driven customer engagement:
Deploy AI Agents to handle repetitive queries and provide smart routing and guidance—freeing up associates to focus on high-value interactions and improving overall efficiency.

Knowledge Management in Retail: Success Stories

Leading omnichannel retailer is automating and augmenting customer service with eGain, leveraging digital self-service, messaging, chat, and IVR deflection to digital service, all backed by the eGain AI Knowledge Hub™, to handle over 9 million customer contacts per year. They are deflecting 45% of phone contacts and 30% of IVR contacts with digital self-service and chat messaging, delivering joined-up omnichannel service with context-aware escalation to agent-assisted service.

Hypergrowth retailer was struggling to meet the soaring demand for customer service. They tried out eGain’s Virtual Assistant through the eGain Innovation in 30 Days™ program, a risk-free production pilot. Delighted with the experience, the retailer deployed eGain chatbots for multiple brands. The bots are resolving a wide range of shopper queries, deflecting customer contacts by up to 90%. Where needed, they escalate the conversation to agents, who can see the full self-service context in the eGain Advisor Desktop™, to seamlessly move the conversation forward.

Knowledge Management in Retail: Conclusion

In today’s retail environment, AI-powered knowledge management equips frontline teams—both in-store and online—with real-time, accurate information and expertise to resolve customer issues faster, drive consistent experiences, and reduce operational friction.

eGain’s AI-powered knowledge solutions are purpose-built for the fast-paced demands of retail. With free pilot programs for both the Knowledge Hub and AI-Agent, eGain offers a low-risk way for retailers to improve customer satisfaction, empower staff, and reduce service costs.