Understanding Searcher Intent for Restaurants: Converting Traffic to Customers
Google reportedly processes more than 3.5 billion searches each day. This presents businesses with a lot of opportunities. One can argue that using search engines to provide direction about products or potential purchases is part of virtually every consumer’s journey, and is no longer considered novel.
But search volume alone doesn’t equate to bottom-line success, and neither will simply getting traffic. Where the opportunity lies, is developing a deep understanding about the type of information that users hope to find from their searches, and providing them with that, to ensure that you’re generating the right traffic to align with your business goals.
In other words, learning more about searcher intent, which can (most of the time) be broken into four categories – do, know, go, and blended. Look familiar?
- Do: actionable queries, such as “book reservation at Main Street Cafe”
- Know: informational queries, such as “types of craft beer”
- Go: geo-based queries, such as “tacos near me”
- Blended: Mixture of two or more of the above categories, such as “best restaurants in [insert city]”
What is Searcher Intent?
Whether you know it or not, every time you use a search engine, you’re trying to find information that’s related to the keywords that you search. At its core, this is searcher intent: seeking information that relates to the words you search.
Whether you’re looking for the newest pair of your favorite brand’s basketball shoes or searching for restaurants in your hometown, you’re intending to find results that pertain to your search, then take action to learn more by, say, either shopping for a new item or booking a reservation.
Through countless years of providing information, the search engines that serve these results have gotten pretty good, too. Think about it, when’s the last time you searched something and weren’t able to come up with the results? It’s a rare occurrence, and this is because search engines have parsed through millions of data sets and analyzed countless engagement metrics to understand what users are looking for when they’re searching and interacting with the results of their search. And if for some reason results are served that have low engagement, those results will swiftly be removed because search engines can now understand low engagement in a timely fashion and adjust results and rankings accordingly.
The evolution of understanding these data sets have been sped up by technological advances, specifically machine learning. Yes, machine learning can be frightening because it’s oft associated with certain things like the demise of humans, but I’m not going to go there right now. That’s another topic, for another article, for another time. In the context of helping to nail down what searchers really want information about, machine learning has done a lot of good. Count that as a win for us.
Local Search & Local Businesses
While many types of businesses have capitalized on the added visibility that search provides, the local ones have arguably emerged as the leading beneficiaries. It’s been noted that 82 percent of smartphone shoppers search locally. The leading categories are food and entertainment.
But what entails a local search? See the examples below. They’ll likely ring a bell, too.
- Restaurants near me
- Restaurants in [insert city]
- Map search
If we use the sample searches above, we see that searchers are specifying that they don’t want to find any type of restaurant. They simply want to find restaurants that meet their search criteria—and are thus near them or in a specified city, for example.
These types of queries – localized searches – account for nearly one-third of all the searches that are made on Google. This presents local businesses with a tremendous opportunity to grow their brand reach and get their name in front of potential customers.
To take things to the next level, Google has now enhanced its results to enable its searchers to take action by making reservations, getting on waitlists, scheduling appointments, and learning more about peak hours. So while users have more information to process at once, they also have fewer steps to go through.
And, since 42 percent of all local searches lead to store visits, suffice to say this is a win-win for local businesses and consumers alike.
How Restaurants Can Capitalize on Local Search
For starters, restaurants should be sure that their local presence is optimized for search. There’s quite a bit that factors into this, but by making sure that your restaurant’s online reputation is strong, reviews are positive, and social media profiles and websites are optimized, you can set yourself up for success to get found online. And this shouldn’t be something that gets pushed to the back-burner, especially since 75 percent of diners choose a restaurant based on search results.
Once your digital strategy is intact, though, what else can restaurants do to bolster their chances of converting searchers to customers? If searcher intent is any indicator, one might recommend that allowing users to book reservations straight from the company’s Google My Business profile is a strong candidate.
Recently, Google has launched partnerships that enable guests to book reservations directly on the company’s Google my Business page. And luckily, restaurants are one of the industries that are benefitting, specifically those that utilize a reservation system.
This is a notable enhancement that has been made to fulfill searcher intent and simplify the user journey, especially since reviews, photos and hours of operation are already included on these profiles.
Below are scenarios where potential customers might find this functionality useful.
Use Cases
Near Me Searches
Shopping is not Evan’s forte, but because the holidays are around the corner, he’s decided to take his kids with him so that they can have a hand in the gift-buying. His kids are approaching high school, so this is more of a bonding time compared to frantically checking off a Christmas shopping to-do list. The evening begins approaching, and before making the trek back home, he thinks to himself that a family dinner would be an excellent way to cap off the day. Being across town and relatively unfamiliar with nearby options, he does a quick search for “restaurants near me.” In between home and the mall is a reasonably priced steakhouse he’s wanted to try. He books a reservation an hour in advance, wraps up the shopping and heads to dinner.
Traditional Search
Karen is leading a work event and would like to treat her team to dinner afterward. She knows where she wants to take them, a nearby tapas restaurant with a fun, laid back environment. This restaurant group has several locations throughout the city though, meaning her search must be hyperspecific to get the one that she wants. Knowing this, she searches the restaurant’s name with the street that they’re on, and sure enough, their Google My Business page appears – displaying the hours and address, so she’s able to confirm this is the right store. With one click she can reserve a 10-top for the evening and return to the event.
Maps Search
Adrian is traveling out of town to spend a weekend with friends. She is a selective consumer who makes educated decisions, priding herself on choosing quality over quantity to inform most of her purchasing decisions. On the way from the airport to her lodging accommodations, she types in the address of their rental on a maps app to get a visual representation about the surrounding restaurants. Though a few blocks further than most options, she’s spotted a nearby trattoria with an authentic menu. This is the spot – photos look good, reviews recommend a visit. She books a reservation without having to jump through several hurdles and will be there in a few hours.
Conclusion
Understanding how users search and what they want when they’re searching can help ensure that your restaurant is getting in front of potential customers. By having a grasp of searcher intent, you’ll be able to capitalize on this ever-growing market.
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