Map Rank Tracker by Semrush: Rank Radius and Share of Voice (SOV) vary, set expectations with clients

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TL;DR

Andrew Shotland used Semrush’s Map Rank Tracker to measure how far from their physical location businesses actually rank in the local pack—and found most don’t rank beyond ~0.5 miles.
Rank radius and Share of Voice (SOV) vary by city size and competition, with smaller cities like Midland, TX showing dramatically larger SOVs.
Their team now uses this data to set realistic expectations with clients and assess which geographies are more viable before targeting keywords or locations.

Andrew Shotland

Oct 29, 2024, 2:12 PM

*UPDATE: <https://docs.google.com/presentation/d/1qX6BpYMsktuyVbA5f9fZPHctZMLMOkkcrJDXwVWLT50/edit?usp=sharing|Here’s a slide deck with the info> if scrolling through Slack is not your jam*

Last month Semrush gave me a bunch of credits to figure out some cool stuff with their Map Rank Tracker - their version of a local grid rank for Google Business Profiles. When I looked at the data, the first thing that stood out to me was their Share of Voice report which showed the radius for businesses that rank in the Local Packs across the grid you are viewing. Below is an example of their SOV report for Plumbers in Los Angeles. What stood out to me was that across this 20 mi x 20 mi grid, none of these top-ranked plumbers appeared in the top 3 Local Pack results very far away from their physical location. This got me thinking - what is the average distance from its location where a business can expect to rank well in the Local Packs?

Since I had a thousands of credits, I decided to put them to use. Read on…

Andrew Shotland

Oct 29, 2024, 2:16 PM

I set up “campaigns” for 10 different business categories for the same 20x20 grid in Los Angeles. I then measured the average “Rank Radius” - the average distance from its location every business listed in the results ranked in the top 3 spots in the Local Packs. I used 11x11 pin grids so for each category we could see rankings for up to 2,420 businesses (11*11*20 positions per grid rank). I also looked at the average longest distance from the locations GBPs ranked in the top 3 and the average longest distance GBPs ranked in the top 20. Here’s what the data showed:

Andrew Shotland

Oct 29, 2024, 2:20 PM

Most businesses, regardless of the category, did not rank well after ~.5 miles away from their locations. Plumbers was the only category where they ranked in the top 3 more than .5 miles away.

I also looked at the Share of Voice for the top 10 GBPs per category. Plumbers had the largest avg SOV in the grid at 2.02%. Most categories had an avg SOV of <1%:

Andrew Shotland

Oct 29, 2024, 2:23 PM

I suspected LA was a tough city to rank well in because there were so many competitors. So I tried checking some queries in smaller cities. For “Roofers”, a category where I would have suspected the distance between the biz and its customers was far, I found that the avg SOV did increase somewhat as the city size got smaller, but not consistently. That said, as I got to the 200th largest city in the U.S. - Midland, TX - the avg SOV jumped dramatically:

Andrew Shotland

Oct 29, 2024, 2:26 PM

In the case of Midland, it appeared that the relatively small number of competitors combined with a very spread out population created a lot more opportunities for a business to rank well.

This made me think about the “ideal” business location in denser cities. In many cities, there are districts where similar businesses locate. For example, there’s a neighborhood with all the auto repair shops. But that means you are going to be competing for Rank Radius with your neighbors. So if you are going to locate a new biz, perhaps don’t do it in the district for you category.

Andrew Shotland

Oct 29, 2024, 2:30 PM

This exercise made me think trying to rank in Local Packs beyond a short distance was kind of hopeless, unless the geography was favorable.

But one businesses’ data made me rethink that. A PI attorney in Houston had similar issues with ranking well for queries in the Local Pack _in Houston._ But when I expanded the grid to areas outside of Houston, which have a lot less density, this attorney ranks quite well for “Houston attorney” queries. So when someone say in Galena Park TX is looking for a big shot city slicker lawyer, these guys do great.

Andrew Shotland

Oct 29, 2024, 2:33 PM

Now, when we are pitching a new client, we always will do an exercise like this to determine what the potential Rank Radius is for a business in their service area. It helps us all set realistic expectations.

We are going to do much more complex studies on this stuff over the next year, in fact we are about to start crunching data for our next study this week. If you have any thoughts around this data and what kind of stuff you’d like to test/see, feel free to DM me. We’ve got lot’s o credits to play around with :)

David Mihm

Oct 29, 2024, 2:36 PM

did you write this up somewhere outside of slack you could link to

David Mihm

Oct 29, 2024, 2:36 PM

the formatting is brutal LOL

Andrew Shotland

Oct 29, 2024, 2:54 PM

Yeah Slack tends to do that <https://docs.google.com/presentation/d/1qX6BpYMsktuyVbA5f9fZPHctZMLMOkkcrJDXwVWLT50/edit?usp=sharing>

Noah

Oct 29, 2024, 2:59 PM

Really great. So put in the existing clients in the vertical in the same geo and see what their average SOV is at different radii to understand what’s reasonable to expect?

Andrew Shotland

Oct 29, 2024, 3:02 PM

That’s what we have been doing so far. It’s usually pretty sobering. But the PI Attorney example made me look at it from a different perspective. Usually you think about query + geo first, but now I find myself often focusing on which geos have the opportunity first.

Oct 29, 2024, 3:59 PM

Depends on the population density and competition. Google will show alternates closer first unless they’re showing to be a satisfactory provider. Google limits a lot of businesses significantly in the way they drive attrition to grow their ad revenue.

Oct 29, 2024, 4:22 PM

In Canada when I google Locomotive agency I get one in Montreal and when you do it you get the Carolina version. Google is a local first search and factors proximity in even thousands of miles away.

Kim Kuhlman

Oct 30, 2024, 8:10 AM

FWIW I’ve seen the same for “hair stylist” in the SLC area using Local Falcon. Extremely localized. Now the challenge is increasing that darned radius.

Yan Gilbert

Oct 30, 2024, 3:00 PM

Getting an idea of maximum Solv is important to understand when you need to shift gears and target a different keyword or when to open up a new location. I always look at the best ranking competitor to get a sense of what the upper limit may be for visibility

queries with locations in them don't have the same solv bubbles, as outside the area google will consistently show the same profiles with little variation no matter where the searcher is.

if you did 'houston car accident lawyer' from NYC you would see the same from a search in LA

I recently did an analysis for a client that tracks two queries across 300 locations. I found that the average max solv's were not the same for the two keywords, meaning that it was inherently more difficult to rank for one keyword than the other.