As web analytics evolves, businesses are able to gather data and measure conversions with increasing depth and precision. E-Commerce companies can track every check-out, and match up this data with traffic acquisition costs to develop precise ROI models. Businesses that rely on lead generation can do the same – once you’ve figured out how much each lead is worth, analytics tools and some simple math will allow you to optimize your marketing programs down to the penny.
For brands with physical locations – like retailers and restaurants, the analytics picture is much more blurry. Consider the average quick-serve or casual dining restaurant chain. Such a company may have hundreds, thousands, or tens of thousands of locations. Around each one is a radius of potential customers that need to be reached. But since every transaction actually takes place offline, web marketing programs are often hard to measure, justify, and optimize.
As larger and larger marketing budgets are assigned to the web, local-national brands are realizing the tremendous value of digital marketing. But how can these business tie Internet marketing campaigns to in-store sales? In this post, we’ll cover some of the current options for making the online-to-offline connection, and explore the future of real-world analytics.
What’s Possitble Now: Web Engagement as a Proxy for Offline Success
Although it isn’t always possible to track exactly how many in-store sales a given web marketing campaign is driving, there are ways to measure which vehicles are most effective at engaging web users.
For example, the store locators that Where 2 Get It builds are often the closest point between a web user and an in-store shopper. Since the locator is so close to the conversion, actions that users take on the locator can be the best predictors of how likely they are to visit a store.
Some of the measurable actions we value include:
- Usage of the “Driving Directions” function
- Usage of either “Send to Phone” or “Send to Email”
- Interaction with map bubbles and bubble content
- Printing the page, or printing a coupon
- Interaction with social media
Users who interact with our locators in any of these ways have demonstrated, at least to some degree, an interest in shopping offline. Different actions can indicate higher levels of engagement – for example, a user who chooses to print a set of driving directions seems very likely to visit a store. On the opposite end, it isn’t reasonable to assume that every user who performs a search will visit a store – being too optimistic on action value will only skew performance estimates.
Another key consideration is traffic segmentation. Simply lumping all locator users into a single group is unlikely to produce many actionable insights. Rather, grouping local engagement by channel will allow you to gauge which activities are most effective at driving in store traffic.
While this “local engagement” analytics strategy is far from a perfect system, it can at least be used comparatively. By breaking out different channels, and comparing local engagement rates, you’ll know where your local ad dollars are best spent.
Call Tracking Tactics for Local Analytics
At Where 2 Get It, we leverage call tracking numbers to help measure direct-response based local marketing programs. A typical strategy involves setting up a store locator, but replacing standard store numbers with unique call tracking numbers. This strategy enables to measure exactly how effective our campaigns are, at a hyper-local level.
But using call tracking numbers like this brings up a few tough challenges. Firstly, managing so many numbers is both costly and time consuming. Aside from that, call tracking numbers create a specific challenge for local SEO. Because local rankings depend so heavily on consistent local data, such as name, address, and phone number, it can be very detrimental to apply a call tracking system to any organic search campaigns.
While we typically limit call tracking to paid campaigns, there are ways to work around the issue of data consistency. Mobile click-to-call functionality is a great way to capture call data without needing a special tracking number – simply setup click to call as a trackable analytics event, and you’ll be able to capture very precise mobile conversion data.
Another creative approach is to keep a store’s standard number on a page in plain text, but insert an image of a call tracking number on-page. In this way, Google will see the proper number, while users will get shown a more visible, trackable number.
Finally, it’s worth mentioning that call tracking in general isn’t an ideal solution for every business. While product manufactures or high-end retailers may see a high volume of calls prior to purchase, a QSR or mainstream retail chain is unlikely to drive many pre-sales calls.
The Future of Online-to-Offline
While online-to-offline analytics still isn’t an exact science, over the next 5 to 10 years, mobile adoption should provide marketers with considerably more precise local analytics.
Mobile commerce is a particularly promising area. As more consumers begin to pay though their mobile phones, local-mobile marketing messages will be much easier to tie to in-store outcomes.
For example, consider Google Wallet. If Google’s able to use GWallet to match specific purchases to individual Google accounts, this could open the door for truly accurate local analytics. Imagine a system where every in-store purchase can not only be tracked, but also matched to an AdWords keyword or display ad.
A few years from now, marketers may be able to login to their AdWords accounts, and see how many sales each keyword drove, and what products were purchased. And while the actual transaction would have to take place using a mobile device, because Google users are typically logged in to the same Google account across desktops and smartphones, even desktop searches and display clicks could be analyzed towards specific retail purchases.
Google isn’t the only company pushing innovative solutions into the online-offline world. A startup called Euclid has developed a system they’re calling “Google Analytics for the Real World.” Euclid basically installs a sensor within every physical location that’s able to detect smartphones. With this, it’s able to track shoppers, and provide familiar web-style dashboards and metrics surrounding number of visits, peak times, and so forth.
A final piece of the online-offline puzzle is SoLoMo. With location-aware checkin services, brands can measure local engagement volumes, compare to competitors, and generally leverage social media data to measure in-store success.
Both SoLoMo analytics, and the Euclid model, still seem to suffer from the same challenge: while they can measure in-store activities, they’re ultimately not able to tie specific web marketing programs to in-store outcomes in a truly granular way. For now, local-national brands will still have to accept some separation between the web and the real world. But the technology is coming – over the next decade, real-world analytics is poised to totally transform local brand marketing.