Most marketers know that being customer-centric is key. To accomplish that, brands need a single, unified view of their customer. But here’s the challenge: Most advertisers are using marketing measurement solutions that are not aligned with that view.
In fact, it’s pretty safe to say that most brands and media buyers actually have a disjointed view of their marketing mix. There are a wide variety of factors that are pulling apart their view of the customer, and that’s affecting their understanding of what is actually influencing them. And without that understanding, the personalization that empowers people-based marketing isn’t possible.
It has become a common complaint from brands. As the media landscape has increasingly become fragmented, they’re getting 10, 20 or 100 different performance reports because their media buys are going across that many different platforms. Each of these reports comes at the consumer from a different angle, using numbers and data that are not aligned. And because they’re seeing all these different aspects—how the customer reacted to a campaign on mobile, within a walled garden, on different social channels, on TV or even in store—they can’t determine what is driving their purchase behaviors and how marketing can effectively influence them.
Let’s put this more simply: Most platforms and reports measure the impact of a channel. But what people-based marketing requires is measurement that supports a customer-first strategy. You can’t be looking at things like upper funnel/lower funnel or above the line/below the line when what you really need to know is what actual customer success looks like.
So if you’re dealing with multiple vendors and getting analytics that tells multiple stories, what do you do? The answer is to move to a single, unified model with a single source of truth. Unified analytics blend data from marketing mix models and multi-touch attribution, providing a full, customer-first view of what drives a brand’s marketing performance. This unified model is more accurate and actionable and gives marketers what they need to know to support their customer-first strategies.
But even once you’ve made the move to embrace unified analytics, there are issues to consider. Many unified MMM/MTA approaches are still not based on identity and person-level data. That makes it impossible to map performance at the customer level.
What you want to look for are unified analytics that uses a blend of statistical techniques that assign business value to each element of the marketing mix at both a strategic and tactical level. This puts a brand on the path to full-funnel, full-visibility measurement.
To get that single view of the customer, you need to look at the problem on two fronts.
The first is the underlying data—you can’t measure what you can’t see. So your solution needs to have access to the data from all the different types of providers and vendors–social media platforms, marketing clouds, DMPs, DSPs, to name a few. Even leading digital platforms like Google and Facebook are increasingly motivated to share this kind of data to demonstrate their performance. The endgame here is to get a view of everything the customer was exposed to so you have that single, true view.
The other front is analytics. Brands need to have that single view analytically. This will tell the story of how all the different factors along the path to purchase are impacting a given customer. And that’s where a unified analytics approach comes in. It will be analyzing data from every conceivable interaction—PII from CRM, set-top box TV exposure data, direct mail activity, phone call activity, foot traffic based on location data—recording everything that is one-to-one trackable. At the end of the day, you need a single analytic approach because it’s a single customer.
Closely related to data and analytics is resolving identity. After all, people-based marketing requires accurate matching of the person to the device. That begins with the accuracy of underlying data. But it also requires you to take a holistic approach to eliminate data silos, bring everything together in one place and remove eliminate identity blind spots. Finally, unified analytics needs that accurate identity to provide actionable insights.
After all, when you’re starting down the path of a customer-focused strategy, you don’t want to find out later on that the measurement solutions you’re using are media-focused and don’t align with your goals. Real insights to people require people-based analytics. That’s how you turn mixed messages into the true view you can believe.
An earlier version of this post was published by Neustar here.