Though we can point to numerous indicators to demonstrate the importance of local search optimization for local businesses, as an industry we have not yet settled on a standard method for measuring the return on investment (ROI) for these efforts. We can and do gesture to the 97% of online users who turn to desktop and mobile search to find out about local businesses, or the 50% of mobile searches with local intent — both figures published by Google and quoted by everyone. We can reference David Mihm’s Local Search Ranking Factors report, updated in August, which catalogues the industry consensus on practices that influence the ranking of businesses in local searches. The assumption going into a project like the Mihm report is that the catalogued activities will have a significant impact on customer traffic to the business’s physical location.
But the question is how to calculate just how much return a given business can expect on the investment of time, money, or both into a local search campaign. For many business owners, it’s that type of dollars and cents calculation that will drive them to decide whether or not to move forward with a campaign. Other metrics are important but ultimately secondary to the bottom line.
On the surface, calculating ROI is quite straightforward:
ROI = (Return – Investment)/Investment
So for example, if you invest $100 in a campaign and realize a return of $180, your ROI is (180-100)/100 or 80%. This metric is typically used for traditional investments, such as real estate and securities, in which context a good investment might have a much lower ROI. Losses are expressed in the form of negative ROI, so that a stock purchased at $100 and sold at $80 would have an ROI of -20%.
Financial analysts suggest, though, that ROI can be misleading if hidden costs are not taken into account. To take my last example, fees associated with the purchase and sale of the stock should be included in the ROI calculation, meaning that a more accurate ROI would actually be lower than -20%. There are also nuances in the calculation of returns, which can be summed up by saying that the estimated total return over the life of the investment is the best measure.
How can we apply these concepts to local search optimization? In order to do so, we must agree on methods for calculating both costs and returns. Costs are more somewhat more straightforward. Local search campaigns are conducted by business owners themselves, by company representatives, by third party consultants, or by means of professional services. Primarily when we are speaking of local search optimization, we mean activities that are ostensibly free; given sufficient time and expertise, business owners can claim their own Google and Yelp listings, optimize their websites for local search, solicit reviews from customers, and conduct most of the activities that third parties offer as services. However, time is money; time spent on activities not related to one’s core business carries an opportunity cost; and the expertise required to do effective optimization on all sites, keep track of changing requirements, and so on should be factored in to the calculation of what your investment is worth. Arguably, in order to perform your own local SEO at the same level of effectiveness as a qualified consultant or professional service, you would need to factor in the time required to gain the necessary expertise and the opportunity cost, as well as the time to do the optimization work itself.
Depending on the person’s level of experience and the range of activities being attempted, it would not be unreasonable to estimate that it would take 40 hours to learn the basics of local SEO and 40 more hours to execute the first phase of an effective local campaign. Based on such an assumption, one may put in a proper context the cost of third party services.
However, the calculation of ROI requires only that we know the cost of the service we have chosen to invest in. Now comes the tricky part. In order to determine a reliable method for measuring the monetary benefit of local optimization, we must take a range of variables into account. Some businesses are new and have no online presence; others may have a reasonably well-established presence in online directories as a residual effect of having been in business for a long time with no significant name, address, or phone number changes; others may be equally well-established but may suffer from the lingering effects of a name change or a move. Businesses do not begin local SEO campaigns on an equal footing.
What’s more, the value of optimization depends on variables such as the value of a lead given a particular business category, much greater in general for service oriented business than retail businesses and differing widely within those sectors; the popularity of searches for your business category in your region, which determines the number of leads likely to be generated; the relative competitiveness of the business category, which will alter the value of search rank positions; and even more fundamentally, the relative value of well-optimized listings on various properties. Even while we acknowledge the preeminence of Google, Yelp, Facebook and a few others, we cannot discount the contribution to positive ranking made by corroborating listings on other sites, nor should we disregard the traffic the long tail of local search generates in the aggregate. The proper calculation of local search ROI requires us to factor in these variables rather than attempting to find a one-size-fits-all formula.
We can assume that well-optimized presence versus absence in local search results in a 100% greater likelihood of generating leads. For convenience, we might decide on a scale of values as follows:
Value of Presence
Absence (new business with no listings): 0%
Few listings, variable quality: 25%
Many listings, variable quality: 50%
Many listings, consistent quality: 75%
Many claimed listings, consistent quality and consistently updated: 100%
This scale, though simplified, attempts to account for the relative value of all local properties as well as the value that multiple corroborating directories add to the larger publishers such as Google, Apple, and Bing. Thus the value added by the local SEO campaign is a function of the starting place for the business and the nature of the campaign itself. A business with no presence that conducts a campaign ending in multiple listings of consistent quality and claimed listings on high-profile sites will gain 100% of the potential value in a local campaign. A business with few listings of variable quality that conducts the same campaign will gain 75% of the value, and so on.
What remains is to factor in the value of the leads likely to be generated by such a campaign. Say we determine that the value of a converted lead for a particular business is $50, and that the popularity and relative competitiveness of searches for a business category in a particular geographic region (as given for example by Google’s Keyword Planner) causes us to expect that 10 potential leads can be generated for this business per day. There is a potential value in those leads of $500 per day, but the actual value is only realized upon conversion. The conversion likelihood of a visit to a local search listing is a matter of some debate, and indeed that likelihood has been shown to differ between desktop and mobile search, but for our discussion we can factor in a conversion likelihood of 25%. This gives the actual daily value of our example at 25% of $500 or $125.
Factoring in the scale of value discussed earlier, we can then say that a business receiving 75% of the full potential value of a local optimization campaign, whose daily converted leads equal $125, has realized a daily return of $93.75 (75% of $125). If such a business were to spend $500 on a local search campaign, it would realize a 100% ROI on the sixth day after campaign completion.
The formula can be summarized like this, if we assume Lead Value is the total number of converted leads for a given time period multiplied by the value of a converted lead, and Campaign Value is the differential between starting presence and ending presence:
Local Search ROI = ((Lead Value X Campaign Value) – Cost of Campaign) / Cost of Campaign
Though there is high variability in each of these factors, my example is not extraordinary, suggesting that the ROI of local search, if it can be reliably demonstrated, may be much higher than many other online marketing activities.
Damian Rollison is vice president of product and technology at Universal Business Listing, a company dedicated to promoting online visibility for local businesses. He holds degrees from University of California, Berkeley and the University of Virginia, where he worked at the Institute for Advanced Technology in the Humanities. He can be reached via Twitter.