Applications of Personalized Consumer: Market Characteristics
In our Applications of Personalized Consumer theme, we laid out the theme overview, along with key product characteristics that define successful companies in this space. In this article, we outline the market characteristics that illuminate ideal categories. While there are many categories where a personalized consumer approach can be applied, we believe these characteristics are most representative of markets that will benefit from personalization at scale.
Those characteristics are:
- Metasearch platforms present many complex choices, and self-selected filters limit product discovery. The consumer is looking for a more intuitive way to evaluate complex choices without having to do a lot of manual work: As described in our original article, we believe consumers are experiencing “search fatigue,” and this problem is exacerbated by outdated filtering options. While consumers can often select from a series of available filters, these options are binary in nature (e.g. afternoon or evening flight, non-stop or one-stop, etc). However, this framework doesn’t incorporate the weight of those preferences, or incorporate any nuances with regards to which selection is more important to the consumer.
- Decisions are not driven by brand recognition: Well-known brands are often able to leapfrog the choice overload problem, cutting through the noise with brand loyalty and alleviating some of the search fatigue. As a result, markets that lack well-known brands, or categories where purchasing decisions are not driven based on brand recognition, are particularly well-suited for a more personalized approach.
- The purchase process itself can be done easily via web or mobile, and isn’t solely dependent on price. The best markets for personalization are ones where the consumer is willing to transact digitally, and is not reliant on a broker or intermediary that forces the transaction to be online. This enables maximization of the impact of personalization. In addition, these are markets where price is not the primary factor evaluated, so that the value of the other characteristics is also important.
In summary, products/services in these markets will be able to: (1) assemble data sets through the user voluntarily or passively providing data, or access data sources via API, (2) make proactive recommendations, replacing repetitive customer search queries, (3) narrow down complex options to a smaller set of tailored choices, reducing the need to scroll through many options, and (4) constantly learn and improve the tailoring of options through AI.
Based on these market characteristics, we are most excited about the application of a personalized consumer approach in the real estate, travel, furniture, and beauty markets. In real estate, we are specifically interested in platforms that alleviate the apartment and roommate search process, which continue to be difficult decisions. In travel, we see real opportunities to provide better experiences booking both transportation, as well as accommodation. Lastly, in the furniture and beauty market, we see an overt manifestation of the search fatigue problem given the sheer explosion of products available online, and through meta-search platforms.
We believe an increased willingness to share data from the consumer perspective combined with advances in data science open new possibilities for personalized consumer experiences, and new startups in these categories will have the potential to take significant market share from incumbents.