AI Shopping Assistant

OPPORTUNITY

As the Sr. Director of the Transactional Team at People, Inc., I helped users confidently find and purchase the right products.

My team conducted extensive user research including user interviews and regular usability testing to deeply understand our users goals, needs, & pain points of The Researcher Persona. We used this data to optimize our product roundup template, but wanted to explore how we could streamline our users’ experience across their full shopping journey.

PROBLEM STATEMENT

Consumers researching products visit multiple “Best Of” sites, retailers, and platforms to validate sources, evaluate options, and hunt for the best price. In a world where organic traffic from Google is declining, the business is looking to build direct relationships with consumers and be the final step in their shopping journey.

HOW MIGHT WE...

Provide all the information consumers need in one place to make a confident purchase decision and become a trusted resource for future purchases?

PROPOSED SOLUTION

Meet the AI Shopping Assistant!

An IA driven chatbot that compiles information from select resources and provides a flexible, conversational way for users to get relevant product details, read customer reviews, and track prices all from one Product Roundup page.

The Shopping Assistant can query data such as content from the People, Inc. pages and product databases along with external partner data such as Amazon to support tasks at any stage of the consumer’s shopping journey, such as…

Personalized product recommendations based on user criteria
Surfacing relevant details about each product
Building comparisons of selected products
Gathering customer reviews from retailers
Showing price history
Saving products and tracking prices

PROTOTYPE

In the prototype below, the AI Shopping Assistant is helping the user find the best espresso machine based on their specific needs such as features, budget, and level of experience.

Once the user has selected their preferences, it can provide recommended products right in the chat, eliminating the need for them to dig through the article.

Once the user selects a product, it can provide more information about that product such as, how difficult it is to assemble, or real customer reviews from sources like Amazon.

And if they prefer to wait for the product to go on sale before they purchase, we could Save and Track products for them and when a user creates an account to save a product, they can get notified when saved products go on sale.

HYPOTHESIS

By providing all the information and functionality consumers need in one place, they are more likely to convert on our sites, and return for their future product research needs.