While consumers are making purchasing decisions across multiple channels, many retail businesses still manage products through disconnected systems built for a far simpler era. 

As product lifecycles become increasingly compressed and sales channels multiply, those operational gaps are becoming commercial liabilities, according to Jason Lee, VP, Apac sales, with Centric Software. 

Retailers that connect product data and decision-making stand to improve speed, margins and customer experience, he told Inside Retail’s Amie Larter in the latest edition of her podcast series Retail Untangled. Those that don’t risk losing sales long before a customer reaches the checkout.

The retail market has become considerably more challenging as consumers migrate from buying products in physical stores to purchasing online or through social media.

That shift has exposed just how fragmented product management remains within many organisations. Design and development are often managed in one department, merchandise planning in another, pricing might be managed in spreadsheets, and product information is owned elsewhere. Every hand-off introduces delays, inconsistencies and missed opportunities, and those inefficiencies become increasingly expensive as retailers expand across channels and markets.

Some businesses, he says, focus purely on brand management while outsourcing manufacturing. Others own product design before passing production to manufacturing partners. Regardless of the model, AI offers an opportunity to connect teams working across different geographies and stages of the product lifecycle, reducing the inefficiencies created by multiple time zones, languages, departments and markets.

“The retail process has become more complicated than before, and everybody is using their own way to sell. We have a customer in Indonesia that sells only online. It does not have a store, but it makes a lot of money and is growing very fast.”

Competitors, he says, are recognising they must respond to changing consumer behaviour far more quickly than in the past.

Complexity is replacing linear retail

Selling through more channels is only one part of the challenge. Today’s successful retailer must also navigate an expanding calendar of online shopping events, including promotions such as 10.10 and 11.11, where demand can change rapidly, and inventory decisions carry greater financial consequences.

Retailers are constantly balancing product assortment with inventory levels. Carry too much stock and markdowns follow. Offer too little and customers simply shop elsewhere.

“They need to react faster to meet the market requirements – and then make money. The process has changed from linear to concurrent,” says Lee.

Timing has therefore become one of retail’s biggest competitive advantages. Product development, merchandising, sourcing and pricing increasingly need to happen simultaneously rather than sequentially.

“You need to quickly respond to the market, with buying to meet customer requirements. That’s where they lose money.”

Such decisions ultimately depend on the quality of the information available. “The decisions come from data. So AI is everything, but without data AI cannot do that.”

For retailers lacking reliable, accessible product data, the commercial impact is immediate.

“Business literally walks out the door,” says Lee. 

Customers increasingly expect accurate information, competitive pricing and immediate availability, regardless of where they choose to shop. Retailers operating across multiple Apac markets and product categories are managing a level of operational complexity that barely existed a decade ago.

Lee believes AI should support better commercial decision-making, but only if organisations first establish a trusted data foundation.

While many businesses are currently using AI for language translation and communications, he sees significantly greater opportunity in applying it to product management, enabling retailers to better understand customer demand and reduce the time between product concept and market launch.

Margin is earned before the sale

Speed to market often dominates discussions around AI, but Lee argues retailers should pay equal attention to where profitability is quietly disappearing throughout the product lifecycle.

“Margin is everything,” he says.

Many established businesses look for opportunities to improve profitability by changing the product itself. Lee believes a far bigger problem is that retailers frequently overlook customer feedback already available within their own business.

“For example, if I produce more product and sell to the market, but the market does not like black colour, they prefer other colours, I lose money. You need to have a well-organised system to manage that data, then you use AI to help you to close the gap.”

The information required to make better decisions already exists, he argues. Retailers generate vast amounts of customer, sales and product data every day.

“They just do not use it. So when I meet my customers, I show them how AI can help them use the daily or weekly data to analyse and forecast for the future.”

Instead of relying on historical buying patterns alone, retailers can identify changing customer preferences earlier, improving product selection while reducing excess inventory and missed sales opportunities.

Consistency matters across every channel

The value of connected product data extends well beyond forecasting demand.

When products launch across multiple channels with inconsistent descriptions, different imagery, missing specifications or conflicting prices, the customer experience deteriorates, and margins suffer.

“Most organisations are aware of this. They might be thinking about how they sell to different channels – some through their own stores, some to a wholesaler – and they are using different pricing.”

Managing pricing consistently across markets has become increasingly difficult as retailers expand internationally and operate across multiple sales channels.

Lee says AI-powered monitoring tools can collect pricing information from different markets and channels, including through image recognition technology, providing retailers with a comprehensive view of pricing differences across competitors and their own operations.

“So you have a full picture. Then you can close the gap, and manage price or margin across different channels at headquarters.”

That visibility helps retailers protect both profitability and customer trust, something that can be quickly undermined by pricing inconsistencies. A customer who finds the same product selling for less online than in-store is unlikely to complete the purchase in person.

“This transparency must be kept. In China, it is transparent. Store prices can be changed immediately. If you go to a store, you see the price is lower, they will immediately give you a discount.”

To Lee, AI is not all about automation or replacing people. Its greatest value lies in helping retailers bring fragmented product information together, enabling faster, more informed commercial decisions.

• Listen to the podcast for more insights from Jason Lee into AI’s role in retail.