Online to Offline — part 1: First step to understanding ROPO with the probabilistic approach

Media Consulting 2 February 2018

Digital marketers today are haunted by one preoccupation: being able to tell their CFO “this is how much we’ve spent on digital advertising, and here’s exactly what it represents in sales”. But how does one prove the existence and measure the link between digital investments and in-store sales, between online and offline worlds?

Consumers’ purchasing behaviours constantly evolve, making it crucial for retailers to stay up to date. We have identified an essential one for you: the ROPO trend. ROPO (Research Online Purchase Offline) refers to consumers researching product information online before buying in-store. This is a complex one due to its many variants – such as the showrooming trend: examining products in stores before purchasing online. Nonetheless, understanding and tackling this increasing purchase behaviour (that is now reaching 88% of consumers) has become the new holy grail for marketers.

And no one is spared: whether you are in the luxury, automotive, or insurance industry, 55’s guide to ROPO is here for you.

Why you shouldn’t overlook the ROPO effect

Investing in digital advertising with a proper online measurement framework is a good start, but making sure your digital campaigns actually work for your bottom-line makes all the difference. Why? 77% US and 73% Chinese Luxury shoppers search for product information online, while still preferring offline channels for purchase. For China’s automotive industry, 83% of consumers rely on information online before purchasing a car, with 64% influenced by opinions shared on social media. This leads to a significant challenge for marketers: how to know whether a customer interacted with a digital touchpoint before purchasing in-store, and, ultimately, how to measure the impact of digital investments on offline conversions?

Until recently, retailers sorely lacked indicators to assess the performance of their online ads on in-store sales. Today however, the rise of innovative tracking technologies has allowed retailers to measure holistically across channels. The goal being simple: bridging the gap between point of sales and online touchpoints through the collection and analysis of anonymised customer data. How? Two approaches are available to you when tackling ROPO: probabilistic (our focus today) or deterministic (stay tuned to hear more about that very soon!).

Taking a probabilistic approach on ROPO through available advertising networks’ solutions

With consumers viewing social media on their mobile, browsing the web on their laptop, and reading the news on their tablet (sometimes all at once!), tracking their journey is not easy. Yet, as a retailer, knowing whether your customers saw your ads online before visiting your store is key. The probabilistic approach can help you track cross-device users to your store: probabilistic technologies utilise complex algorithms when collecting customer data (IP addresses, geolocations…) to identify consumers, and link in-store clients to online users.

As these probabilistic tools are rising due to their attractive appeal, we’ve selected a few interesting ones to share with you:

  • Google Store Visits: though only available with AdWords, this tool is especially effective for retailers. It matches users who clicked on your search ads with their mobile location from Google Maps, to determine if they visited your store after viewing your online campaign. Through mobile geolocation, this tools links in-store visits with online ads for your stores.
  • Facebook Store Visits: mostly aimed at businesses with many store locations (retailers, auto dealerships, restaurants), this tool also coordinates users’ geolocations with your online media touchpoints. Brands can promote their stores’ locations to consumers nearby by creating ads that target consumers based on their location, and better manage their digital media budget through narrow targeting.
  • Snap-to-Store: Snapchat designed Snap-to-Store for marketers to assess the performance of their ads on driving customers to locations such as stores and restaurants. It allows brands to track whether customers coming into their store have viewed their online ads, with the benefit of being frictionless for the consumer, automatically geo-localising its users in the app.

But if you’re looking for certainty, this approach might leave you hanging

While these tools seem very appealing, they heavily rely on probability (as the name suggests), and give you at best an estimate of ROPO effects… Let me elaborate: Google Store Visits tries to match your location with that of a specific store. But for stores located in dense areas (such as shopping malls), how does it know your exact location? It could think you are on the first floor when you are on the third. Its reliability is hence questionable for mall retailers.

Furthermore, with a closer look, the tools’ true purpose is not online-offline measurement; rather, it suggests a drive-to-store strategy. Indeed, they focus on driving consumers to stores from digital ads, as does Snapchat’s solution. By encouraging in-store presence, their simple implementation allows a first estimation and rough idea of the effectiveness of your drive-to-store campaigns, with sometimes the use of reliability surveys. Yet, their attractive and trendy aspect hide the fact that they are advertising tools, with restricted data measurement lacking precision – no dimensions outside of the advertising platform’s. Not only that, but the geolocation devices cannot actually measure in-store conversions – what if your customers just visited your store without purchasing anything?

In the end, implementing a probabilistic approach sounds quite similar to awareness investment. While a good first step to ROPO measurement, it lacks accuracy – which is why we will be introducing a second approach to data measurement in an upcoming article: the use of deterministic technologies. Stay tuned!

 

Big thanks to Victoire Dumas for her valuable help in writing this article!
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