Part 1: Local search is starting to get more social
Part 2: How the battle for local search will be won
Part 3: Google Hotpot a strong competitor to Yelp
Part 4: Statistics on business and consumer engagement in local search
Part 5: Foursquare 3.0 takes mobile ball to a whole new level
Social search has been talked about for several years now as the wave of the future. We’ll get better information with the help of our friends. Local is the ideal place to prove that out:
- Most people tend to have a lot of friends in their immediate area.
- Local search revolves around everyday experience.
- The “answers” are based on opinions.
Google’s entry into the space is Hotpot, a local ratings and recommendations tool. It is spending a significant amount of money to promote Hotpot in the Portland and Austin markets.
Hotpot is clearly meant to compete with Yelp. To a lesser degree, it competes with Facebook Places and foursquare. (It’s funny how much the local search space has changed in the last few years. AOL, Mapquest, CitySearch and newspaper Web sites have largely dropped off the local map in recent years.)
It’s important to set the context in this fight: Google is already the undisputed leader in local search. Despite the attention that other sites get, Google is the number one place people go to get local information. More than 20% of Google queries are local in nature. Google Search serves about 170 million users. I bet 99.99% of them have done a local query. Yelp serves 26 million users in the United States. But many of those users come through the Google front door. (Partly because Yelp is one of the best SEOs out there.)
There are two core problems to be solved in local search. Providing someone additional information on a business whose name they know and providing guidance to those who are open to suggestions on a business.
Business name searches
The first problem is largely solved, despite the fact that the scope of the problem has increased. Just a few years ago, it meant providing someone the name, address, phone number and a map for a business. Today, it increasingly includes providing hours of operation, attributes such as romantic, kid-friendly, links to make reservations and menu information.
Distribution and integration helps Google capture business name searches. You can use the browser’s search box and Google.com to get your answer. With an Android phone, it’s even simpler. Press a button, speak your search and the answer appears.
Google can answer most of the basic questions about many businesses in the United States. Yelp has the best data out there for restaurants and bars in the United States. I’ll get to the reasons why later.
Google has difficulty with non-standard venues. For example, in Portland, it does poorly with food carts. In most cases, I don’t advocate manually updating a database to address localized concerns. But given the amount of money that Google is spending on promotion in Portland and the importance of food carts in the city’s dining scene, they should follow the advice of an Oregon company and “Just do it.” A basic effort could be done in a day by using online resources. A street team could hit all of the major food cart areas and provide enhanced data such as hours and pictures in a few days. (While also handing out Google stickers.)
The other core problem in local search is discovery — helping to find an appropriate answer when they only have a few parameters or no clue what they’re looking for. These are the questions like “I want a kid-friendly pizza place nearby.” “I want to go to some place fancy,” “I’m looking for a special night out on the town.”
This is an area that Yelp excels at but Google generally sucks at. The problem with Yelp (and the opportunity for Google) is that getting the most out of Yelp requires a lot of work from the user. Yelp has an incredible amount of rich data on local businesses. But it’s too much. It’s overwhelming to see hundreds of reviews. Using Yelp also means trusting people you don’t know, whose tastes may be very different from yours. And it means dealing with the snarkiness of reviewers who often spend more time talking about their life stories and girlfriend problems than the business they’re supposedly reviewing.
Yelp has introduced a number of tools over the years to alleviate this problem. It does data summarization across reviews so that you can see at a glance what are the things most frequently mentioned about the restaurant (e.g. popular menu items). You can see a distribution of the ratings to see how consistent a restaurant is. You can also see ratings trends to see if the restaurant is getting better or trending downward.
But often, people just want a few options. Too much choice and too much data is overwhelming. People don’t want to spend 30 minutes figuring out where to go. We’ve been getting recommendations from Amazon and Netflix for decades. “People who liked X also liked Y.” “Based on your previous ratings, here are places we think you’ll like.” This is especially important in mobile, where people are often more hurried and the screen real estate in which to read is limited. That’s what Google is trying to do with Hotpot.
In some ways, this is an easier problem to solve than Web search. If you’re looking up answers for Jeopardy, there is usually only one right answer. And if Google can’t find it, you know right away. For a discovery-oriented local search, there is more than one right answer. And if the answer isn’t what you were expecting, you won’t know for hours and you might not blame Google. (The restaurant might have had an off night.) For more details, see my earlier post about making intelligent recommendations in local search.
Picking the right social graph
In order to make the best recommendations, you need data. You need data from the user about their preferences and you need a good social graph from which to present options. The more data the better.
This is a significant challenge for Google. Other companies in the social space such as foursquare, Gowalla, Quora and Instagram, have piggy-backed off Facebook’s social graph. That’s not an option for Google. And I’m not willing to spam all of my friends to invite them to use Google Hotpot. The advent of Facebook Connect has made such spamming less socially acceptable. As a result, I have exactly one friend on Hotpot — and he’s a Google employee.
Foursquare’s social graph is OK, but it’s a bit small given the current focus on check ins. The number of people who I want to be able to see where I’m at in realtime is fairly small. But I’d be comfortable sharing historical data on reviews and ratings with a much larger audience.
Facebook’s social graph is ideal for this application. It has a lot of personal connections, including both close and loose connections. The loose connections are important because they help provide coverage that you might not have in your tighter friend circle. For example, the data to make recommendations for Indian restaurants in Paris might be from a former colleague who now lives in Paris.
In the next part of this series, we’ll look at some of the key success factors for local search.