Increased consumer willingness and ability to share data, advances in data science, and supply chain innovations have resulted in new startups that are able to provide unmatched personalization in consumer products and services. However, many consumer product/service categories are still dominated by experiences that haven’t been innovated for decades. As an example, we still search for travel by scrolling through endless flight and hotel options. When we search for a home or apartment, we manually categorize many options without easy ability to trade off between characteristics. Across consumer categories, we perform the same repetitive searches without consumer companies learning from our previous likes/dislikes and tailoring options to our unique characteristics.

As a result, we believe the problem of “search fatigue” is a major one in many consumer categories. For example, in travel search, customers are inundated with thousands of unique travel options every time they use Kayak or Expedia. These search engines don’t learn from previous purchases, and also make it very difficult to trade off between characteristics.

These companies also potentially have the ability to improve the unit economics of specific consumer categories. They may do this by either reducing cost to deliver a product/service, or by increasing customer willingness to pay. As an example, the customer may be willing to pay an additional fee or subscription to access a service that provides tailored recommendations (e.g., Stitch Fix). The customer also may be willing to pay more for the underlying product/service itself, due to its customization. If the service is a marketplace, sellers may be more willing to access more highly qualified customers. Underlying cost to deliver the service may be reduced by cutting out the middleman or reducing the human element of a product/service. As an example, consider the cost to provide a robo-advisory service, vs. the traditional cost of a financial advisor.

These new startups have the potential to take significant market share from incumbents, who are wedded to an old paradigm that requires the customer to repeatedly search through an endless array of options every time they are making a purchase.

Examples of these types of companies have begun to proliferate across industries. Stitch Fix is perhaps one of the best examples, combining algorithms and human touch to enable personalized styling at scale. Spotify and Netflix are two additional examples in the media category, providing a personalized music platform, and personalized viewing experience, respectively. Lastly, in the fintech space, Betterment has built an automated robo-advisor that eliminates the need for an individual wealth advisor.

The impact of this new generation of companies is truly created experiences that feel personalized, yet more cost effective, to the consumer. While personal stylists, wealth advisors, or boutique travel agents have existed for decades, these services have typically been out of reach for the average consumer. We believe that new data-driven platforms have the power to fundamentally shift this paradigm, and make personalized services available to a wider array of consumers.