A consumer clicks a mobile search ad to your tablet website and watches a few of your product videos. That day, she checks out your desktop site from her work laptop and again from her home computer. Days later, she downloads your mobile app and continues her research. Over the next week, she views or clicks multiple mobile and desktop banner ads. Finally, she buys your product at one of your retail locations, a transaction recorded by your CRM because she is a current store credit card holder.
As a marketer, how do you know which interactions helped to convert that customer? Once you know that, won’t you optimize, bid, message, and buy better?
For years, digital marketers have been tackling the online measurement challenge. Needless to say, for a channel that is supposedly “the most trackable” marketing discipline, it hasn’t been very easy.
The flaw in most measurement approaches (and it’s not just the last click)
The good news is that the industry has been slowly advancing on this issue. Marketing attribution has helped marketers understand that assigning all of the value of a conversion to the last ad or last click in the customer journey is not the right way to evaluate their marketing efforts. That fight is nearly won, and most marketers now understand that they must consider all the interactions in a customer’s path to conversion in order to properly measure marketing impact.
But while attribution evangelists preached their message over the last decade, consumer behavior evolved rapidly. The proliferation of channels and devices on which consumers engage with brands has forever changed the measurement game.
Ultimately, the best attribution approach includes the entire customer journey, which requires your analysts to have a single view of each customer’s journey, regardless of the channel or device — and offline interactions should be included in the dataset, if possible.
Getting a single view of the customer requires more than a methodology, or massaging the data at the time of analysis.
It requires a technology solution.
Achieving a single view of each customer is crucial for your measurement needs
Signal helps marketers by identifying each customer’s various device- and channel-speciﬁc proﬁles and merging all of their engagement into a single view of the customer. This is done by setting up and maintaining a match table that records every known identification type for each customer from their various device IDs, browser IDs, vendor IDs, advertiser website IDs, etc.
Over time the match table begins to fill, and as every new ID is collected, each customer can be identified wherever and whenever they interact with your marketing efforts.
Once all of the data is collected and connected within Signal’s Data Hub, your teams can easily deﬁne and distribute any and all of your customer engagement data in real time to any endpoint you desire, such as your measurement systems–but also to reporting and analytics platforms.
We’ve made sure that building the right measurement feed for each of your partners is simple and intuitive. Your teams don’t need to be data scientists or skilled in SQL or coding to manage how your data is distributed. Signal can handle whatever data you throw at it.