Why Google leads Omnichannel Measurement ? | Articles

The launch of the Store Visits in Google Analytics

Big News! You might have heard it. Recently Google released a new beta feature: “Store Visits” for Google Analytics. What is it? Long story short, it allows to measure the link between website sessions and in-store visits.

How does it work from a technical point of view ? Google uses 3 streams of data. First they link sessions with users that are logged in any of the Google properties (YouTube, Gmail, etc.). Secondly with the linking of Google My Business - AdWords - Analytics, Google has access to every store’s address that belongs to an advertiser. Finally users share their location settings with Google. Those location data connected with very accurate measurement based on Wifi signals, GPS signals and other technologies allow Google to make sure that users have been in a store and didn’t just passed by. By connecting the 3 streams of data they can tell if a user first visited a website and then went in a shop. Obviously Google can’t measure this for every users. They do it for a large enough base of users and then extrapolate to the entire population with an accurate confidence interval.

On the screenshot below you can see how the report looks like in Google Analytics:

 

This new feature arrives in the context of heavy discussions on omnichannel and a few months after the release of two other features that also aim to link the online & offline world:

  • The Store Visits (SV) in AdWords
  • The Store Sales Direct (SSD) in AdWords

A few months ago we wrote another article explaining all the details on how Store Visits and Store Sales Direct were measured for Google AdWords.

What’s the difference between all of those ?

Well first, Store Visits only measures visits and don’t require any data to be sent from the advertisers while Store Sales Direct measures the link between clicks and effective sales and revenue generated in store. This second feature obviously requires advertisers to send specific data about users and in-shop sales behaviors in order for Google to do the matching.

Secondly, the main difference between SV in AdWords and in Google Analytics is that SV in AdWords are based on clicks while based on sessions in Google Analytics. More importantly, SV in Google Analytics allow to make the link between every source of traffic and in-store visits while AdWords only makes the link between a click on an AdWords ad and in-store visits.

This last element is the big news of the week. Indeed so far it was possible to measure links between in-store visits and advertising platforms such as Google, Facebook, Bing. Nevertheless, by summing up all the store visits that each platform attributes to its campaigns we were ending up with much more store visits compared to what really happened from a business point of view.

That situation was due to attribution. Indeed each of those platforms use a post clicks/views attribution model with cookie delays of several days. The good news with the store visits in Google Analytics is that it:

  • Homogenizes the measurement cross platforms
  • Deduplicates the store visits conversions between the platforms
  • Allows to have a closer picture of what really happened from a business point of view

And again, that’s the main purpose. We want to make sure we do things that impact the business and drive more sales/revenue.

Note that Google Analytics’ measurement has its limitations too. Indeed Google Analytics attributes by default store visits with a last click attribution model. This means that only the last interaction of a user will get all the credits. Moreover it’s sessions based measurement. This means we miss the whole impact of impressions and views !

However, with the release of this feature, Google is positioned very strongly in the omnichannel measurement dimension. They took more time than others to react on it but 2018 has already been definitely the year of the omnichannel measurement. This positioning makes sense at a time where most advertisers try to bridge the impact of online advertising on offline sales/revenue. Being able to understand how online influences offline through concrete data will definitely help convincing the one that did not consider it yet.

What’s next ?

This measurement is a strong plus in Google’s strategy as they take a central piece in the omnichannel measurement. Nevertheless, as explained above, the way Store Visits are measured today in Google Analytics has its limits. Consequently here are a few things we could expect in the coming months/years:

  • The possibility to play with different attribution model for SV measurements
  • The possibility to apply the data-driven attribution model (only valid model)
  • The measurement of store visits based on impressions/views
  • Integrating smart bidding options on store visits measurement

Finally here is an assumption, you probably all remember that Google tried to launch Google Attribution beginning of 2018 before stepping back. The main reason was the tool was not ready. My 2 cents opinion: Google Attribution had low added value compared to already existing solutions in Google Analytics. Nevertheless, integrating the whole omnichannel measurement approach within an updated version of Google Attribution would dramatically increase the added value of the tool. Could this be the main next step, probably in 2019 ? Let’s see in the months to come.


publication author julien de visscher
AUTHOR
Julien De Visscher

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