Amazon sees its new AI search engine, codenamed Project Nile, helping to increase sales from mobile users

• Amazon is planning to roll out a new AI-infused search experience.
• The new search engine will launch on mobile first.
• Amazon gets most searches from mobile, but the conversion rate is much lower than its website.

Amazon is working on a new secret project called Project Nile that will overhaul its search engine to include AI chatbot technology.

According to a transcript of an internal presentation given earlier this year by Joseph Sirosh, VP of Amazon Search and Alexa Shopping, one potential outcome of the improved search experience is increased mobile sales.

The AI-powered search bar will be more conversational, in-depth, and personalized. Sirosh stated that it will be “mobile first” because the new features may have the greatest impact on sales.

“One interesting thing is that on mobile, we now have 78% to 80% of searches but much lower conversion.” According to the transcript, “the conversion on the website is dramatically higher.”

“If we can increase the conversion on mobile, because we provide great experiences, great expert answers, then that could be a potentially significant lift to Amazon,” he said.

An AI-driven revenue boost like this would be ideal for Amazon, which has seen its growth slow. Sales increased 11% to $134.4 billion in the most recent quarter, a significant decrease from the 30% to 40% growth rate it experienced during the pandemic.

Sirosh stated during the presentation that the new AI conversation layer will be added to the existing Amazon search bar. He compared it to Google Maps, which also has an assistance layer. He added that the upgrade will provide better search results, expert answers, and suggestions on the fly.

Sirosh expects the new AI feature to function similarly to an in-store salesperson who is intimately familiar with each shopper’s tastes and preferences.

“Before e-commerce, your search engine was the salesperson in the store.” And that person was well-versed in the products…They’d look at you and know exactly what you’re looking for because customers like you have visited the store before. “They may have known you in person, so they may be aware of your preferences, and then they can synthesize all of that information together in a natural language conversation with you and assist you in your shopping mission,” Sirosh said during the meeting.

“And if you can scale that up to everything in Amazon, that would be the future mission we want to aspire to.”