Estimates from Google suggest that around 46 percent of searches have “local intent.” Furthermore, the vast majority of these lead to a sale.
If small, local businesses are going to take advantage of this, however, they need to keep up with the latest trends. Here’s what’s new for local SEO in 2020.
Voice SEO Will Dominate
Over recent months, there’s been a bit of a backlash against voice SEO. Prominent commentators have come out and stated that the hype we saw about the new kind of search a couple of years ago was overblown.
Voice search, however, is on an exponential growth trend. While it is still small in comparison to typed queries, its popularity compounds every year. By the mid-2020s, it will have exploded into the dominant way that users interact with the web.
For NJ local SEO experts, this presents a challenge. The task is to shift the keyword finding process away from what people type and towards what they say when optimizing pages. There could be subtle differences.
Furthermore, experts will also need to help their clients take advantage of the fact that more people than ever use voice search to find local services. Data from the Voice Search For Local Business Study, 2018, found that 56 percent of people had used voice search on their smartphone in the last 12 months to search for a local business. Of those who didn’t, only 18 percent said that they wouldn’t do it under any circumstance.
SEOs Will Use More Structured Data
Search engines are sophisticated, but they’re not perfect. You can still type in questions into the search box and get answers that have nothing to do with your original intent. For consumers, it is frustrating.
Now, though, we see a trend towards what analysts are dubbing “structured data” that seeks to solve the problem. The current challenge for search engines is that they don’t understand concepts. They’re unable to intuitively link ideas together in the way that a person can. In short, they don’t have common sense.
Structured data is a meta-approach that seeks to take care of that process for search engines. By tagging the information on pages in the right way, SEOs hope that they can send signals to search engines, demonstrating that pages are relevant for particular search queries, even without upgrades in search engine AI. =
Firms Will Prioritize Ranking For Long-Tail Questions
Google’s search algorithms, however, aren’t completely stupid. The company is increasingly using machine learning to link questions to answers in an attempt to provide users with more value. It is not uncommon today to be able to type in what seems like an esoteric question and for the search giant’s servers to spit a relevant answer in the form of a highlighted box.
Companies that operate locally can take advantage of this feature of Google’s service by trying to rank for various business-related questions users submit.
Here are some examples:
- Where can I find the best hairdressers?
- Which is the best restaurant near me?
- Where can I get my car serviced in New Jersey?
- How far is it to the nearest coffee shop?
You’ll notice that a lot of these questions involve the term “near me.” It turns out that Google takes this particular phrase very seriously indeed and uses it as a way to determine search intent – that is, what the user really wants. Businesses who can show search engines that they operate locally stand the best chance of getting their pages in front of these people.
Companies With Poor Service Records Will Be Punished
SEO used to be about your ability to create content and get links from trusted authority sites. In 2020, though, Google will prioritize firms with the best reviews and customer service too.
The reasons for doing this are clear: Google wants to forward users to firms that offer a quality local experience. It doesn’t want to disappoint them with poor results.
New Local Engagement Metrics Will Come To The Fore
Google knows that if it can make better recommendations to users, it’ll become more popular as a search engine. The company, therefore, is always looking for new engagement metrics that will tell its algorithms whether to privilege a particular local service in rankings for any given customers. User telephones, for instance, with the company number in their address books, may be more inclined to use that particular’s firm’s services. Likewise, the content of emails in their Gmail account could be an indication of the kind of income they have and, therefore, the type of services that they prefer to consume.