How to Leverage AI to Overcome the Top Enterprise Local SEO Challenges

Search engine optimization (SEO) is complex and ever-changing, making it a challenge for even the most experienced marketers to keep up. But as SEO becomes more sophisticated, so too must enterprise SEO teams.

Enterprise SEO comes with its own unique challenges, from managing large budgets to dealing with complex organizational structures. But perhaps the biggest challenge facing enterprise SEO teams today is how to keep up with the latest trends and best practices.

But it doesn’t end just there. Enterprise SEO is a mix of everything from local SEO to national SEO and everything in between. Local SEO for the enterprise itself can be challenging for a number of reasons. Let’s take a look at the top five enterprise local SEO challenges and how AI can help you overcome them.

1. Understanding When To Prioritize Local vs. National SEO

Knowing how to toggle strategies and when to focus on local SEO vs. national SEO can be difficult for any marketer, let alone enterprise SEO teams. After all, both local and national SEO campaigns come with their own unique set of challenges and benefits.

The biggest challenge with SEO is that it’s not always immediately apparent which strategy, local or national, is better suited for your business goals at a given time. To succeed, it’s crucial to build an understanding of when to focus on local or national SEO.

Knowing how Google regards certain terms as local can help you build your keyword strategy and figure out which approach supports your SEO investment needs. It is also important to note that site design and keyword strategy play a big role in how much traffic you could lose or gain.

Understanding Local Search Intent

We all are aware of the search intent, right? It is the why behind every search query that users type in the Google search engine.

When it comes to enterprise SEO, there are four main types of search intents you should focus on search queries with:

• National search intent
• Sem-national search intent
• Hyper-local search intent
• Local search intent

You can know the search intent behind a query by looking at the features that appear on the SERPs.

For example, if you want to know the search intent behind the query “local SEO,” you can tell it is local because of the “Local Pack” feature that appears on the SERPs. This pack includes a map with three local businesses that match the query.

On the other hand, if you want to know the search intent behind the query “SEO,” you can tell it is national because there are no local features on the SERP. The only thing that appears is the national SEO results.

Let’s take a closer look at each search intent type discussed above:

Queries With National Search Intent

These are the search queries for which there are no SERPs features, no location-specific pages, and no map pack. Look at the below image, for instance.

Since this SERP doesn’t show any local results is a sign that Google probably doesn’t see these search queries with local intent. But if searchers start to redo this query with location info such as “NY newspaper” or “Washington newspaper,” the search engines will likely shift to results that have some local intent.

Queries With Sem-National Search Intent

The SERP features for queries with semi-national search intent are a mix of both national and local results. You can tell that the query has some local intent because there is a map pack on the SERP. However, this map pack is not as prominent as it would be for a query with purely local intent.

Take a look at the semi-national SERP features for the query “lawyer” below. As you can see, there are both national and local results.

Queries like “lawyer” that have semi-national search intent might show a map pack because there’s an equal amount of local and national clicks. This could be due to the reason that some users might be looking for a lawyer close to them while others might be looking for the lawyer’s main website.

Queries With Hyper-Local Search Intent

Search queries with hyper-local search intent are the ones in which the SERP features are entirely local. For such queries, not only is there a map pack, but also a “Local Finder” and “Local Teaser” feature.

Look at the image below to see what the SERP features for a query with hyper-local intent look like.

As you can see, the SERP features for this query are entirely local. This is usually the case for queries that are looking for a specific type of business in a very specific location. What matters the most for businesses to rank for these queries is their proximity to the searcher.

Queries With Local Search Intent

The SERP features for queries with local intent are very similar to those of queries with hyper-local intent. The only difference is that there might not be a “Local Finder” feature on the SERP.

Look at the image below to see what the SERP features for a query with local intent look like.

As you can see, the SERP features for this query are very similar to those of queries with hyper-local intent. The only difference is that there might not be a “Local Finder” feature on the SERP.

There goes a lot into understanding the search intent behind a query. By analyzing the SERP features, you can get an idea of what Google thinks when it comes to a particular query. And once you know that, it becomes much easier to create content that ranks for that query.

How to Use AI to Identify Search Intent?

If you want to take your search intent analysis to the next level, you can use AI. Using an AI-powered tool, you can get a more in-depth understanding of the search intent behind a query.

An efficient AI SEO tool can analyze a huge amount of data in a very short time and identify the search intent behind a query with great accuracy. Not only that, but such a tool can also help you optimize your content for the right keywords.

To sum it up, understanding search intent is crucial to ranking in Google. And the best way to understand search intent is to analyze the SERP features. However, if you want to take your search intent analysis to the next level, you should use an AI-powered tool.

2. Managing Multi-Locations

Listing management is usually a breeze for single-location businesses. But once you start managing multiple locations, it can become quite a daunting task. Local listing management companies like Yext and Uberall can help you manage your listings more efficiently.

However, for multi-location businesses that don’t have a “single source of truth” for all of their location information, managing listings can be quite a challenge.

That’s where AI comes in. AI can help you manage your listings more effectively by giving you a complete picture of all your locations. It will also help you keep your listings up-to-date and accurate.

For instance, if you own a chain of restaurants, you can use AI to track the opening and closing times of all your locations. You can also use AI to monitor the menu items and prices of all your locations.

3. Optimizing Store Locators

As we mentioned earlier, many brands outsource their store locators to third-party vendors. While there’s nothing wrong with this in theory, it can often lead to problems.

One of the biggest problems with third-party store locators is that they’ve limited control over how they’re displayed on a brand’s website. For an SEO-friendly store locator, it’s important to have control over how the store locator is displayed on your website.

Luckily, AI can help you optimize your store locator for SEO. AI-powered store locators can be customized to fit the look and feel of your website. They can also be optimized for different devices.

Create And Optimize Location Page Content

Many businesses make the mistake of creating location pages that are nothing more than a list of store locations. While this might be enough for some businesses, it’s not going to cut it if you want to rank in Google.

If you want your location pages to rank in Google, you need to create content that is relevant to the location and topics you are trying to rank for.

Here’s how you can use AI to create and optimize content for your location pages:

• Research relevant topics for your location pages. It can also help you find relevant keywords for your location pages.
• Create catchy titles and meta descriptions for your location pages.
• Optimize your location pages for different devices.

4. Google Business Profile Management And Optimization

Your Google Business Profile (GBP) is one of the most important assets for your local SEO strategy. But if you’re not careful, it can also be one of the biggest liabilities.

However, by using AI to manage and optimize your GBP, you can avoid many of the common mistakes that businesses make. For instance, you can use AI to:

• Monitor your GBP for duplicate listings.
• Make sure your NAP (name, address, and phone number) information is accurate and up-to-date.
• Make sure your business hours are accurate.
• Optimize your GBP for the right keywords.

These are just a few of the ways you can use AI to improve your local SEO strategy. By using AI to manage and optimize your listings, store locators, and business profiles, you can take your enterprise’s local SEO to the next level.

Successful enterprise local SEO requires a lot of moving parts working together seamlessly. But with AI, you can manage and optimize all of your enterprise’s local SEO assets more efficiently and effectively. So, if you’re not already using AI to improve your enterprise’s local SEO, now is the time to start.