Despite the fact that companies are gathering more data than ever, 85% of CMOs say they struggle to effectively access and utilize this data in a meaningful way. This is one of the findings from a survey by among 223 CMOs that spend over $5 million on digital marketing.
Stunted accessibility is partly caused by the usual suspects, such as a lack of appropriate technology and talent, but another major headache is that data is often locked up in silos. For example, desktop display advertising campaigns cannot be tied together with social media data, email campaign data, or mobile app data, and therefore, measuring cross-channel ROI is virtually impossible. The consequence is that when a consumer converts, the company doesn’t know how the different channels influenced this purchase decision, and is unable to optimize campaigns.
Today, many companies fall back to second-best approaches such as attributing 100% of a conversion to the first or last touch point, and a whopping 15% said they simply don’t know or don’t even try to measure cross-channel ROI.
The mobile effect
Research has shown that digital channels influence each other significantly. Most especially the inherent nature of mobile causes it to spill over to other channels.
For instance, in mobile shopping, almost $1 trillion (yes trillion; $1,000,000,000,000) of in-store purchases were influenced by mobile in the USin 2014 alone and this number is growing. This is an enormous amount. For comparisons, e-commerce sales totaled a “meager” one third of that, with just over $300 billion spent in 2014.
Naturally, brands and their advertising strategies are affected by these, what Google calls, “Micro Moments” on mobile as well. It is therefore more important than ever to deliver a uniform experience to your audience across all channels. Yes, despite being often degraded to a buzz word, cross-channel is the only strategy suitable to please today’s cross-connected consumer.
Cross-channel marketing is defined as “a strategy…in which brands plan, execute, measure, and optimize their efforts through every marketing touchpoint experienced by their target audience.”
Data silos and walled gardens
But as 85% of the surveyed CMOs found out the hard way, accessing and distributing data across channels is an arduous task that few manage to do right. And it’s safe to say that mobile is most problematic. To effectively obtain data from mobile, let alone combine it with data from other channels is simply a lot harder than on desktop. This is because the cookie has lost its power almost entirely on mobile as people spend 85% of their time in apps, which essentially form data silos.
Facebook is one of the few players that fixed this cookie problem through the rich 1st party data its users provide. It is also able to track people across devices and browsers which makes their ad platform Atlas extremely powerful. However, Facebook is a walled garden, i.e. the data stays in Facebook’s ecosystem and cannot be exported to your own data management platform (though you can import your own data to Atlas). Google offers a similar deal with its Display Network. These closed platforms hinder channel agnostic ROI tracking, despite their size and deep trench of cross-channel data. Advertisers that need a wide reach simply can’t rely solely on Facebook or Google. They want to be able to have their DSP(s) cast a wide net over the entire (mobile) internet to reach people in all corners while tracking cross-channel performance.
Getting mobile data right
In order to obtain quality 1st party in-app data, besides what your users pass through voluntarily, one has to turn to mobile analytics platforms. Traditionally, analytics were focused on app usage and later usage-based inferences, yet these failed to provide reliable demographic, interest, and intent data on mobile audiences. Also, data was always aggregated so no individual profiling was possible. Worst of all, the data was owned by the analytics company and therefore not exportable.
source: IBM Big Data & Analytics Hub
Today, mobile audience platforms finally close the gap and provide insights into audience demographics and interests that are individually accessible via API, allowing for seamless integration with other platforms. Clearly this is needed in order to give advertisers, app publishers, and retailers the means to measure cross-channel ROI effectively while staying (relatively) independent from advertising industry giants such as Facebook and Google.
Tying it all together
Creating and executing a superb cross-channel marketing strategy is like managing a Formula 1 racing team. Real-time data from a variety of sources pours in every second and the difference between winning or losing lies in optimizing every single parameter in harmony with each other. No Formula 1 team would accept that one of their systems refuses to share data with the others and advertisers shouldn’t either.
Despite the fact that cross-channel marketing has been around as a concept for several years, not many companies know how to do it right. Which is unsurprising, since there is not only an unprecedented need for data from a variety of sources, but this data also needs to be tied together and processed to become meaningful information. Just like the Formula 1 driver adapts his racing strategy based on the sum of all data that he and his team analyze, so too must companies adapt their marketing strategy in relation to the applicable parameters of all channels. Implementing this can be done an almost infinite amount of ways, as long as the most important condition is met: the brand must take a customer-centric approach. Only people based measurement can provide insights across all channels.
There are a few companies and brands that bet early on the growing importance of the customer’s journey across channels and now reap its rewards.
One of those early adopters is Macy’s. Macy’s no longer distinct different channels in their marketing budget, ad spend is allocated to wherever it provides most ROI which they can measure cross-channel.
A central database provides customers with product information whether they are searching and browsing on a desktop, in the Macy’s app, or through scanning items in-store. This ensures that branding, prices and other product info are always consistent across all channels. Customers can buy online and pick up their orders in a department store of choice (BOPS). Naturally, the same goes for returning items.
Customer sales data is captured from in-store and digital sales and combined with 3rd party data through its central database. This allows Macy’s to get to know their customers, and more specifically, they get to know how their customers move through different touch points.
This strategy has positioned Macy’s as leading cross-channel retailer which has benefited their bottom line significantly.
Not surprisingly, “Mobile Advertising” and “Harnessing Big Data” were the two highest ranked priorities in the survey among CMOs. The only way to successfully do so is to allow data to flow freely across marketing channels. Significant investments will need to be made in technology, people, and strategies but will surely pay off as customers disregard brands and retailers that fail to meet their expectations.
In 2015, a data platform equipped for mobile is essential for your company to succeed. If you would like to learn more about how Personagraph can help you effectively reach your audience and meet advertising KPIs, please contact us at: email@example.com for a demo.