“Constant connectivity has forever changed the way people live and shop, giving rise to new consumer paths and blurring the lines between digital and physical experiences. With a quick search on any device, we can locate nearby businesses or find product availability in a local store in just a matter of seconds.”
— Surojit Chatterjee, former global head of product, mobile search ads and AdSense for search at Google
Thanks to recent advancements in digital technology and the ubiquitous nature of mobile devices, the lines between online and offline are beginning to blur and become tied together.
In 2014, Google introduced store visits tracking and measurements to its AdWords platform as a way to help advertisers understand the impact digital marketing makes in the physical world. Google claims that since this feature was implemented, more than one billion store visits have been measured as a result of AdWords ads. This metric, now available to 1,000 advertisers across the globe, has seemingly led to a substantial uptick in conversions. According to an April 2015 blog post from Google, “Buffalo Wild Wings, a national restaurant and sports bar franchise with over 1,000 locations, used insights from store visits data to validate and adjust its bidding strategy and realized an 84 percent lift in conversions.”
The post also states that U.S. retailers are seeing, on average, “. . . four times more conversions overall and 10 times more conversions on mobile when including store visits data as part of their search ads performance.”
These are incredible insights for retailers to have at their fingertips considering that:
- Around 90 percent of global sales still happen in-store;
- 30 percent of all mobile searches are location based;
- Location- related searches have grown 50 percent faster than any other type of mobile search query.
Despite how exciting these measurements are, there is still one slight problem that leaves many hesitant to rely on the numbers; they are only estimated as they fall under the Estimated Total Conversions section in AdWords.
Surojit Chatterjee, Google’s former global head of product for mobile search advertising and AdSense, has commented on this by stating, “. . . store visits are estimates based on aggregated, anonymized data from a sample set of users that have turned on Location History. This data is then extrapolated to represent the broader population and only reported if it reaches a strict, highly conservative confidence level.”
But what exactly is the criteria to be met for this “highly conservative confidence level?”
Measuring In-Store Visits
When Google initially announced estimated in-store visits, it was explained that the estimated data was based on a user’s proximity to an advertiser’s location derived from Google Maps. As this kind of information may not necessarily constitute a store visit, many question the validity of the numbers.
Chatterjee did, however, expound on the nature of the technology and how it determines if an individual actually visited a store to instill more faith in the metrics.
The factors that evaluate if an actual store visit took place include:
- GPS location data;
- Google Earth and Maps Street View information;
- User query intelligence;
- Co-ordinate and boarders mapping of hundreds of millions of stores across the world;
- Measurements of a store’s Wi-Fi signal strength on devices;
- A user panel of more than one million individuals who have opted-in to provide on-ground location history;
- Visit behavior.
Google is excellent at gathering information and predicting likely outcomes. By mapping stores (and their surroundings) the world over, the company can make accurate assessments regarding if a user actually went in to a store when combined with the user panel. Additionally, Google does not simply count a person entering a store as a “visit.” Instead, the algorithm takes behavior patterns and search queries into account to determine a potential visitor’s intent and if they were driven by an ad click.
This isn’t the end of Google’s investigatory work when it comes to AdWords store conversion metrics. The organization has partnered with major third-party store transaction analytics firms to obtain intelligence from promoters that is then integrated into AdWords to pair sales data with ad clicks.
Additionally, the reason why most advertisers do not have access to this data as of yet is because Google simply does not have enough information to provide valid results. As the company continues to compile this knowledge, the feature will likely spread to more users. There have even been whispers of a more permanent, long-term plan to integrate store transition measurements into AdWords. While this possibility is still a long way from coming to fruition, the prospect is an exciting one nonetheless.
So when it comes to store visit reporting, should retailers and advertisers trust the numbers put forth? In my judgment, yes. Google has proven the accuracy of its algorithms time and time again, and that machine learning is a pivotal focus of the company moving forward. While these metrics may not be perfect or absolute, chances are they are pretty close to spot-on. Not only is Google Maps an extremely accurate service, but when the information gathered is combined with the factors listed above, Google is likely to draw some very solid conclusions about whether or not a store visit actually took place, and if that person was driven there by an ad found on the search engine.
When it comes to store conversion metrics, it’s probably safe to say that the dominant force in search knows what it is doing.
Do you think that Google’s AdWords store conversion metrics are accurate and can be trusted? How do you think the company could improve on this technology to make it more scientific and categorical?