There’s a reason many brands don’t track in-store attribution for local marketing: it’s hard. Really hard. I’m reminded of the old adage that says half the money you spend on advertising is wasted; you just don’t know which half. Similarly, half your customers walk into your store as the result of local marketing; you just don’t know which half.
Proving that someone visited your store because they saw your online local marketing efforts at some point is a complex undertaking. Most out-of-the-box attribution tools don’t make it easy to differentiate between local marketing traffic and a visit from someone who stepped out of a local restaurant and happened to see your store right across the street.
There’s also the challenge of seeing over the walled gardens of Google, Facebook, Bing and the other major platforms to compare notes. In a world of last-click attribution, it can be difficult for brands to determine which media influence had the biggest impact on their local efforts, especially when multiple touch points, both online and offline, national and local, blur your attribution model.
In truth, it’s impossible to get a perfect picture of your local marketing effectiveness. Nevertheless, there are ways to get a clear enough picture that you can form reasonable assumptions about the in-store success of your campaigns.
To help you make sense of it all, I’ve outlined some of the more effective methods for tracking local marketing in-store attribution. The most accurate method (and most expensive) would be to integrate all of the in-store attribution methods I’m about to list. But a smarter approach would be to pick and choose the right attribution models to fit your needs.
When it comes to tracking local attribution, start with Google. More people search on Google than anywhere else. So in terms of measuring your local marketing performance, Google will provide you with a solid glimpse of your local marketing effectiveness without having to cobble together additional sources.
The simplest way to get picture of your local marketing attribution would be to track keywords with local intent and site visits on your local pages, and then extrapolate for in-store visits. For example, according to Google, 76 percent of nearby searches on a smartphone result in a store visit within a day, 28 percent of which result in a purchase.
You can use numbers like these to estimate the impact that local should have had on in-store visits. Keep in mind that the percentages of store visits change across devices and across industries. For improved accuracy, you’ll need to refine your percentages based on your own brand-specific research.
But if you want to take your attribution model to the next level with Google and actually track in-store conversions, you’ll need to upload your Google click identifier data (GCLID) back into Google. Unfortunately, this process is complex and requires you to jump through multiple hoops. Many brands find this process to be such a hassle that they opt for the simpler solution of estimating in-store visits through keywords and site visits.
There are internal initiatives your brand can take that will provide you with insight into your local marketing campaigns and the impact they had on your brick-and-mortar locations — namely, coupon codes and app tracking.
Coupon codes are a great way to know if a customer saw an online ad and visited an actual location. By designating a specific local code on your coupons, if a customer shows up at that store with the online local code in hand, you can officially tally one in the win column for local.
Your app is another easy way to measure attribution for local marketing campaigns. Actions like looking up a store location, viewing an in-store map, check-ins, collecting rewards, or getting people to opt in to share their location data can go a long way to tracking concrete in-store visits. At the very least, you’ll have a good idea of how effective your app is at bringing in people locally.
There’s a downside with apps, though. You do have to be a big enough brand that people think to download your app. Additionally, your app also has to be useful enough that those who download it actually use it. For that reason, SMBs won’t reap the same benefits as brands like Starbucks and their app’s cult-like following.
Beacons are one of the more exciting local attribution technologies. By simply placing a beacon at your front door, you can gain a pretty good idea of who is walking into it. Beacons are in the early stages of adoption, but as more companies deploy them and customers get used to interacting with them, I’d expect this to be one of the primary ways of tracking attribution.
After all, getting people to opt in to constant location tracking will continue be a challenge. Getting people to accept beacon notifications only when they’re near locations and at times of their choosing is far less intrusive and therefore more likely to be adopted.
The problem with beacons is that you need to have the specific store app enabled or the user won’t see it. The good news is that Google Chrome on Android will soon be getting beacon support, and this should help break down app barriers and speed up adoption.
Expect Google Eddystone and maybe Facebook Bluetooth beacons to dominate the beacon space. I say Google because more people use it for search than anything else. I say Facebook because one should never underestimate the power of social.
Social is a sector that no local marketer can ignore. Fortunately, Facebook is working hard to help you with attribution through Store Visits and their Offline Conversions API.
Store visits, which you can find in Ads Reporting, measures the number of people who saw one of your Facebook campaigns and then visited a store. Meanwhile, the Offline Conversions API will help you link store sales to Facebook ad campaigns by matching transaction data from your customer database or point-of-sale system to Ads Reporting in real time.
The downside of these two methods is that Facebook makes their estimates based on the number of people who have opted in to share their location data. The upside is that people are far more likely to share their location data with Facebook than most other platforms, so it still provides you with a pretty decent picture of your local marketing performance on social.
Foursquare Attribution also has a similar ability to capture online-to-offline attribution through its pool of 1.3 million users who have opted in to constantly share their location data. Foursquare then tests the visit rate of those who have seen a specific ad versus a control group that hasn’t seen the ad to determine its effectiveness.
The advantage of Foursquare is that it tracks ads across the larger web and app ecosystem, helping you to see into some of these walled gardens. As with Facebook, the downside of Foursquare Attribution is that it’s limited by the number of its opt-in users.
A developing attribution method to keep an eye on is one that’s implemented through ride-hailing services such as Uber and Lyft. If a customer clicks on an ad or the link on your local landing page to request a ride to that location, you have a pretty good idea that the user actually went there.
The downside of this tracking method is that it gives you a fairly narrow view, even more so than Facebook and Foursquare, simply because your insights are limited to the small pool of customers who use Uber and Lyft. But as ride-hailing services grow in popularity and become cheaper through autonomous driving, expect this method of attribution to increase in importance and accuracy.
With so many attribution options, how do you go about determining which methods to employ for measuring local marketing success?
The truth is, even if you implement all of the above approaches, your view into online-to-offline attribution will still be incomplete. Clearer, but still incomplete.
My advice to you is, determine the metrics you wish to track, and then pick the methods that measure them best. This will undoubtedly require you to define what actually constitutes a store visit. Is it someone who simply set foot in your store because of a local marketing initiative? Is it a store visit that resulted in a transaction? And what about e-commerce? Should e-commerce be counted as a store visit if the sale was generated by a local ad on a store’s local landing page?
Once you’ve answered these questions, you can then move on to effectively and efficiently track local marketing in-store attribution.
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