For decades, e-commerce companies have focused on attracting shoppers to their websites and optimizing the purchase journey once they arrive. According to Maju Kuruvilla, former Amazon technology leader and founder and CEO of Spangle AI, personal AI assistants are beginning to move product discovery and buying decisions beyond that traditional model.
Instead of browsing numerous products, consumers can increasingly describe what they need, including the occasion, activity or personal preferences involved. AI assistants can then interpret that intent, compare options and recommend products. Kuruvilla argues that retailers must make their product, inventory, brand and merchandising intelligence useful in this new environment.
The challenge is not a lack of data. Retailers already use analytics, marketing, merchandising and e-commerce systems, as well as tools designed to measure their visibility across AI platforms. The difficulty, he says, is turning identified opportunities into coordinated action while keeping pace with changing inventory, promotions and product availability.
Kuruvilla also cautions that increased AI traffic or more product citations do not necessarily translate into improved business performance. He believes retailers should assess AI investments through outcomes such as conversion and revenue, beginning with a defined business problem, establishing a baseline and testing whether the technology produces measurable improvement.
Spangle’s platform is designed to combine information about a retailer’s products, inventory, brand priorities and commercial goals. Its AI Discovery product helps identify what consumers are asking AI assistants, determine where a retailer’s products may be relevant and prioritize opportunities for action.
The company points to Express as an example. The retailer had identified more than 800 opportunities related to its visibility across AI platforms, but still needed to determine which actions mattered and implement them. Spangle says its agents helped translate selected opportunities into shopping experiences that the Express team could review and approve.
In the first full month after launch, Express reported a 14.5-times increase in AI-attributed revenue compared with the previous 30 days. AI-referred sessions rose 6.9 times, while the conversion rate for those sessions increased 6.7 times. Spangle notes that these were before-and-after comparisons rather than a controlled measurement of incremental impact.
The company is also applying the same underlying intelligence to paid acquisition and onsite shopping experiences. Its stated approach links the identification of opportunities with decision-making, execution of approved actions and measurement of results.
Kuruvilla says Spangle is intended to work across functions that are often managed separately, including marketing, merchandising and e-commerce. Rather than adding another isolated tool, the company aims to give retailers a shared understanding of their business and help them turn that intelligence into actions while retaining control over brand and commercial decisions.
Sources: WWD.