Omni-channel, Cross-channel, & Multi-channel Attribution, oh my!

Cross-channel attribution may sound complicated, but it’s easier than you think.

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Cracking the customer code shouldn’t feel impossible. We’re all customers, after all. Yet making marketing decisions can sometimes veer too far into Mad Men-style gut checks and intuition, or too far toward a clinical analysis of data that leaves out that emotional element. Attribution modeling — whether you call it omni-channel, cross-channel, or multi-channel — begins to solve this problem by blending data with common sense and human behavioral patterns.

Striking this balance is important in today’s fast-paced, always-on market, where consumers have limitless choices, and unfettered access to information about your brand and products. As Mark Braydon, the Content Marketing Director at Barclays UK explains, “I really like the concept that the modern day marketer needs to be part-artist and part scientist. That blend is what I look for in my team. You need to know all the things that drive short-term interest and intrigue but you also need to be able to understand what impact that is having on some of your ongoing trading and performance metrics, and that is where the deep analytical knowledge is required.” Braydon also agrees that cross-channel attribution modeling is one of the most important tools marketers have at their disposal when trying to solve for the customer journey. For us, there are three main reasons to invest in attribution marketing.

1. Attribution is the new digital currency: Traditional KPIs only reveal a piece of the puzzle as we explain in our recent blog post about how attribution unlocks your customer journey. While web analytics may reveal what your customers are doing, attribution helps you move beyond clicks and page views to a deeper, more intimate knowledge of your customers’ motivations and preferences. There are still some limitations when creating attribution models (specifically, linking multiple devices and online and offline channels), but these gaps are getting smaller every day. As more people lean in to attribution modeling as a way to support their analytics programs, these gaps will become smaller and smaller until they disappear and attribution is the new king.

2. Diving into big picture marketing: Even with gaps in attribution modeling, we already know customers are starting and finishing their shopping experience on different channels and across different devices. While this was occurring five or even ten years ago, the number of devices the average person has, and time spent on each of these devices, is increasing every year, making it even more important to understand the big picture customer journey rather than assuming that where someone starts their interaction with your brand is where you will earn their business. We predict that big picture marketing will be one of the fastest growing trends of 2017 and biggest drivers for success in 2018. And attribution is the way to understand that trend.

3. Breaking away from a one size fits all approach: Attribution modeling comes in many flavors: last touch, linear, decay, u-shaped, weighted … you get the idea. Because attribution modeling attempts to understand customer motivation, you can adapt your models to fit the actual behavior you’re seeing in real time. Attribution weighs and balances many variables, so, unlike static KPIs, you can adjust these variables to more accurately reflect what customers are doing and make decisions based on that information. It’s true that no model can perfectly capture each and every customer journey, but these models do present a more sophisticated and nuanced picture of the purchase path. You can even use a combination of attribution reports and models to get closer to a full picture of your customer experience.

You probably already have several tools in place that can inform the foundation of an omni-channel strategy. Let us take a look at your current data and we’ll help you link these to your customers’ motivations and passions, so your clients are always a name and not just a series of numbers.

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