Last week, venerable local consumer reviews service Angie’s List had a $100 million initial public offering the same day Yelp filed for its own $100 million IPO. Recommendations and reviews are a key segment of social commerce, but companies in the market face accelerated evolution and disruption driven by the social-local-mobile technology phenomenon.
Right, now there are three distinct business models for recommendations and reviews:
- Hybrid. Angie’s List may be alone with its business model that mixes paid subscriptions and advertising. It is trying to be the Consumer Reports of local services (home repair, health care, automotive) by harnessing members-only reviews and a tightly controlled ad environment. Only well-reviewed services, about a quarter of its coverage, can advertise in limited amounts. Customer acquisition costs are high, due to its premium membership and its strategy of exclusively focusing on national advertising.
- Mass media. Yelp is going for broader advertising reach with low-cost user-generated content – reviews and ratings of local shopping, restaurants and home services. (Companies like CitySearch and Yahoo also fit in this category.) When Yelp enters a new market, though, it has to license local information. And Yelp has battled Google over content scraping, all while being dependent on Google for over half of its traffic.
- Software and services. Companies like Bazaarvoice and Power Reviews offer white-label consumer reviews and ratings platforms for online retailers and manufacturers.
Social, local and mobile disruptive forces
Social technology businesses often attract investor and developer interest for their potential network effects, where the value of the network increases with the number of participants, creating potential lock-in and winner-take-all outcomes. The three models exhibit only modest potential for network effects. Although the software companies can develop data analysis services for merchants using massive volumes of reviews and users, their partners “own” the reviews, so syndication opportunities are limited.
If any of the models achieve local market scale via volume in users, reviews and advertisers, that scale increases the value of the whole. That is, more advertisers or merchants will want to reach more viewers, who in turn will be able to evaluate more choices. But review quantity does not guarantee quality, and neither Angie’s List nor Yelp seems to have algorithms that are sophisticated enough to help. And while becoming the go-to place for local reviews could lock in advertisers, there is too much competition for either to own that role. Even then, they are still dependent on building big ad sales forces. Meanwhile, the software companies are not necessarily focused on local markets, and their technology platform approach will enable them grow more cost-effectively than the other models, leading to faster profitability.
Mobile access is critical for product and venue reviews, less so for an Angie’s List type of service. Yelp has good mobile distribution on iOS and Android, though it may face increasing competition from Foursquare, which just beefed up its site with Yelp-like content. The software companies are dependent on their partners for mobile access. Real-time mobile reviewing is probably less important than access, although check-in behavior can support loyalty programs for advertisers.
In other words, the recommendations space is vibrant but challenging. The two local-focus models face Groupon-like costs in marketing and sales but with fewer opportunities to use customer data to build new services. Angie’s List has no direct competitors, but I would like to see it shift its advertising from national branding to lower-cost and better-targeted social media like Facebook and Twitter promotion. Rather than a stand-alone company, Yelp might be better off as part of a search engine or daily deals company with a big ad sales force and more services to sell to merchants. The software players are the only ones with traditional tech startup growth and profit potential.