TTC Labs - A personal shopper that gives back control

A personal shopper that gives back control

5th Nov 2019

Online shopping is now connecting people to new products around the world, and they have come to expect a curated, personalized experience. However, people want more control over their data without sacrificing individual recommendations. While many may want these recommendations to support gift shopping for friends and loved ones, they also don’t want what they’ve browsed interfering with their own personalized suggestions. People need simple, empowering tools that let them manage how their data is being used and improve their tailored item recommendations even when they’re shopping for others.

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Product Context

Totes is a digital marketplace that sells a wide range of goods from thousands of brands worldwide—everything from clothes and tech products to some age-restricted items. Totes also hosts a marketplace for peer-to-peer resale. The app prides itself on connecting people to beloved items and recommending new ones for them to enjoy.

In order to provide the service, Totes is powered by some of the following data:

  • Past activity and interests on Totes (page views and clicks on specific products)
  • Purchases and behavior outside the app
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Problem & Opportunity

While people expect a personalized shopping experience, they also want more control over their data and easier, transparent ways to manage it. They also want their digital shopping apps to be multifunctional, places where they can shop for themselves and others. These competing needs require new features to provide them with the same accurate product recommendations when shopping for others and to not have these suggestions influence their own personalized recommendations.

How might we...

...create a feature that gives people more control over how and when their information is being used without sacrificing a personalized experience?

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Design Features
Toto, your personal shopper

Toto is a personal shopping assistant who offers people private, personalized shopping suggestions for a person’s friends or loved ones. By using Toto, people can feel secure that they’re not only getting recommendations tailored to a friend, partner, or pet but that the browsing history from these shopping session will not affect their own suggested purchases in the future. At each step, Toto asks for information and offers brief explanations on how data is being used and why. For those who don’t want to share personal data, there’s a brief survey they can take to generate recommendations, which isn’t saved or used outside of interacting with Toto. The feature's simple and transparent choices allow people to make more informed decisions about their data.

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Design Features
Browse in private mode

This feature allows people to browse in private mode. The app’s background color changes from white to black, visually reinforcing the private browsing feature. Private browsing allows shoppers to freely explore products without their taps and views influencing future recommendations. Maybe it’s a one-time, necessary purchase that they don’t want showing up in their browsing history. Since Toto runs on personalized choices, it’s disabled in the private browsing mode.

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Next steps

These features offer new ways for people to engage with Totes, while introducing more privacy and data transparency options. They also show people how their taps and views are being used to provide future recommendations. In the future, Totes would benefit from testing to understand how people with different needs may use the private browsing mode and Toto, the personal shopper. More research must also be completed to better align account data (especially those accounts with multiple profiles that Toto could potentially access) while ensuring personal safety and consent. Assuming people like Toto’s recommendations, it would be useful to add the choice of saving Toto-generated searches and suggestions to access during future shopping sessions.

How might we build on Totes’ ideas to give people more control over their data and more private shopping features without influencing the personalized experience?

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