How to calculate local SEO ROI — template from RocketData
Local optimization is a set of measures aimed at improving the company's position in the SERP (by local queries), and also working with company's locations online: submitting information about offline locations to all relevant sources, correcting inaccurate listings that contain mistakes.

Today mapping out a marketing budget, almost every company prefer paid ads, SEO, other types of media activities. But often the business' owners don't take into consideration the investments related to marketing of locations: submission of the information about the company to the maps (creation and optimization of listings).

The main reason that scares marketers is unclear profitability, calculating ROI seems rather difficult.
By the way, the most important ranking factors in local search are maps and Google My Business "signals", according to Moz survey:
So, in this material, we'll tell about key metrics of local SEO (on the example of optimization of locations) that will help to understand that the investments are cost-effective. Also, we'll offer a formula for the calculation of local SEO ROI.
The key metrics of listing's optimization (GMB) which prove that your local SEO efforts are performing
*The increase in quantitative indicators is considered on the basis of the difference between the periods (BEFORE and AFTER).
The ranking of the company's listings on Google Maps.
It's very important to track changes in ranking for the keywords you are targeting (for example, "pizza nearby", or "cafe near The Public Theatre").

If the position of the listing has been raised (getting on to the Local Pack more often and being more "visible" than competitors), most likely this happened due to local optimization:
A property configured business' category (the main and also additional: Food> Restaurants> Pizzerias), maximum of accurate information (contact details, etc.), photos, 3D-panoramas , content, listings on the other interactive maps, citation "signals", working with reviews and the "Questions and Answers" of Google My Business.
Track impressions on your listings.
The increase of the listing's views by users testifies that the company's mini-landings have started to rank higher on generic local searches (getting on to the Local Pack).

Thus, the more reliable information presented, the more likely a company will get on to the top and be "visible" to potential customers.
The increase in the number of users' interactions.
Statistics from the GMB dashboard allows to track the number of clicks to call button, conversion to the website, routes paved. The more often listings get on to the top by relevant queries, the more users view them and perform target actions.

Since you can only go back 90 days, it would be better to copy all the data into a spreadsheet so you can track the trend.
How to calculate local SEO ROI for your business?
If a company has tens or hundreds of branches (like as retail, banks, state institutions, post offices, etc.) it is extremely difficult and time-consuming to go through each source to find, add or update listings manually.

Local listing services like solve this problem. But there is a question of how to calculate ROI?

Usually, the coefficient is calculated by the formula:
If ROI is calculated for a certain period (for example, six months), you should use the data exactly of this period.

Coefficient=100% means that the income (profit) is two times more than the cost of investments.

Let's consider the example of return on investments that were made in local SEO (on the example of optimization of locations in Google My Business).

Talking about ROI in this context, firstly it's necessary to determine the profit that was earned as a result of working with locations (Local SEO Revenue = L). Since the statistics on Google My Business listings* are available in your account, it will not be difficult to make a calculation.

*As the company's Google My Business listing is like a website, thus it makes sense to track the conversion in a similar way.
The revenue that was earned due to the optimization of locations can be calculated by the formula: L = K х S х C х V

L = Local SEO Revenue;

K = the volume of keywords searched (in other words, the number of queries);

S = % of searchers who became visitors of GMB listing;

D = % of visitors who became leads (in other words, % of those who perform interactions like clicking a call button, etc.);

C = % of leads who become customers (you can use the average conversion rate);

V = the average order value (total amount of revenue divided by the total amount of orders).
The indicators above are calculated based on the difference between the quantity AFTER optimization — the quantity BEFORE. This will be the result that was achieved thanks to the campaign.
Let's calculate ROI on the example of a real campaign where the cost of investments was $ 3500.
the difference between the number of keywords searched "After - Before" (K) — 267 066;
% visitors of GMB listing (S) — 0,00724;
% of visitors who performed a target action/who became leads (D) — 0,47543;
the average conversion rate (С) — 0,1;
the average order value (V) — $150.
Multiplying the indicators K х S х C х V, we get L = $ 29,039 (the profit that was earned as a result of working with locations by means of Google My Business).

ROI=[(L — Cost) / Cost] х 100%

So, [(29 039–3500)/3500] х 100% = 729%
This example illustrates that the investments related to the optimization of locations are cost-effective and demonstrate high profitability.

Listings on the map give an advantage to companies even compared to the first positions in the SERP. From this, we can conclude: the shortest and the most effective way to purchase is through the map.

To understand whether there is a result (and profit) of working with locations in your company, use analytics and key metrics from Google My Business account. Be sure to optimize all of the company's locations, even if there are hundreds of them.
Get a free report on the online-presence of your locations.

Find out where you don't have listings, where the data is incomplete or mistaken