Online to offline – part 3: Finding the right measurement method for your strategy

Customer Experience 14 November 2019

The issue of online-to-offline measurement has been a key concern of CMOs and CDOs for a while. ‘Walled gardens’ (Google, Facebook, Amazon)—as well as many independent players—offer a wide array of solutions. How to know which one is right for your business? How can I actually use it?

While we went through ROPO challenges and existing probabilistic solutions in one article, we dedicated another to deterministic solutions based on the “exact” matching of online-offline data.

To find an on-off measurement solution that matches your digital marketing strategy, we believe two simple questions need answering.

Which optimization initiatives do you want to prioritize?

Two complementary offline optimization levers stand out in the pool of marketer strategies: drive-to-Store and digital strategy optimization on the basis of actual offline sales.

  • Drive-to-store—more in line with branding than conversion objectives—is mostly covered by previously mentioned probabilistic solutions (Google Ads Store Visits, Facebook Store Visits, Snap-to-Store).
    These work in silos: Google gives an estimate of in-store traffic generated by ads bought in Google Ads, Facebook in Facebook Ads, etc. Choosing the right solution for your business thus depends on the communication channels that form part of your predominant advertising budget ( media mix ), sometimes with the need to pair several solutions together for cross-channel campaigns.

A recent solution based on Google’s user data (aka ‘Google Graph’) makes it possible to obtain a first cross-channel measurement for drive-to-store campaigns: Store Visits in Google Analytics. Unlike Google Ads’ Store Visits, traffic from all channels are here recorded. To date, this solution does however present one major drawback: only your website’s past users are taken into account, so their exact matching rate remains unknown.

  • Your goal could also be to optimize your digital strategy based on on-off sales, for instance to improve your media arbitrations or identify the most efficient—or, on the contrary, ineffective—journeys. In this case, it’s about choosing the technologies that allow you to track the different possible paths (online lead, call, walk-in…).

Which online-offline paths should you prioritize when it comes to measuring ROPO?

To drive sales, deterministic solutions (developed here) come into play. They match personal data with online data thanks to a shared reconstruction key. Online and offline paths can be sorted into two different categories, with two types of digital marketing strategies and two areas of ROPO technologies:

Online paths resulting in contact via form or phone call

  • Online strategy: focused on lead generation or onsite calls
  • Solutions: webanalytics, CRM, data lake , call-tracking

This is the case for all sectors operating on a subscription basis (insurance, banking, energy, telecoms, media and certain B2B sectors in particular), or based on appointment bookings via online form or telephone (for example, in the automotive or luxury industries).

The advantage of these paths is that you can submit a unique identifier online which can be independently retrieved as first-party data to match the sale. This granular tracking method offers highly precise analyses, particularly for the reconstruction of user paths. Nonetheless, make sure the unique identifier you’re using is anonymized.

The incoming call path uses complementary call tracking tools, and therefore additional integrations (link between the call and online browsing, then link between the call and offline conversion steps).

“Anonymous” online discovery path and “walk-in”

  • Online strategy: focused on branding and product discovery
  • Solutions: walled gardens (Google/Facebook), onboarders

This is namely the case of leading consumer or retail brands and, once again, of sectors like the luxury or automotive industries. Indeed, the latter aren’t yet mature when it comes to reaching an actual purchase online, mainly because of the large sums at hand. In this case, no identifiable traces are left on the website—only anonymous actions (media exposure, on-site traffic or interaction…). This is why it is paramount to use third-party data—such as those provided by independent onboarders or walled gardens—in order to match them with personal data coming from sales. One should however be aware of the limits imposed on such tools by recent tracking prevention protocols, including Safari’s  ITP or Firefox Tracking Protection.

Therefore, the main criterion for choosing a ROPO tool that ultimately reaches a sale is the suitability for one and/or the other of these types of paths. Of course, the solutions have different levels of cost and complexity of use, so it is generally recommended to build a strategy upon the existing data architecture and then grow in maturity. For example:

  • Do you already have Salesforce and a well-implemented Google stack, which could thus be easily connected?
  • Do you already onboard audiences in Facebook for targeting purposes? Could these audiences thus be leveraged for ROPO measurement?

On the other hand, from a legal point of view, the consent required to reconcile one’s own data (sales data and identifiers left on-site) is easier to collect than if it is a matter of transmitting and sharing one’s data to third parties, even if they are hashed.

All in all, choosing an online-offline measurement tool that is adapted to your business mainly relies on:

  • The type of on-off optimization to be prioritized: drive-to-store or sale monitoring?
  • The purpose of the digital campaigns you intend to develop: rather branding or performance-oriented?
  • The digital maturity of your company, to manage tools with various complexity levels and analysis capabilities.

Finally, one of the key success factors of these projects is a good coordination and change management. They bring together teams (marketing and sales network) who are rarely used to talking to each other, and call for a major redefinition of digital management using more precise but unprecedented data!

Would you like another cup of tea?