Before the Internet, it was impossible for brands to understand what the customer’s journey to conversion entailed. We could not follow people around and observe what billboards they viewed, which people they talked to, or how they used the Yellow Pages to find service providers. In fact, if we had tried to accomplish that type of research, we would likely have been viewed as crazy and thrown in jail.
Now that the technology has made reams of data about our customers’ behaviors commonplace, brands are hyper-focused on analyzing customer journeys to understand how they can optimize their ad spend to increase the bottom line. They are collecting data on everything from call centers to email to social to offline sales.
These brands are spending tons and tons of time and money trying to track marketing attribution. While attribution still cannot incorporate all of this customer data, we are getting there. At least now you will only be viewed as kind of crazy for trying to take action on it. And although there is plenty of actionable information that comes from developing an attribution model that is right for you, it is important for you to look beyond basic marketing-attribution reporting to truly understand what your customer’s journey looks like.
Understanding the Customer Journey
Since we, as marketers, now receive an unbelievable amount of data, it can give us great insight into what the customer’s journey looks like. In the past, this was something that required a data scientist (or ten) to even try to accomplish — and that did not usually work out too well. However, now we have the ability to give a unified view of the customer and push that into the everyday workflows of marketers and analysts. This ability to democratize data allows users who do not have a statistics background to gain a better understanding of how customers interact with their brands.
It can also be important to have digital analysts who act as data storytellers. They play an important role in translating data about the customer journey in a way that is actionable for marketers. This role is so important because it helps people at every level of the organization to understand that there is more to using data than determining whether you have met key performance indicators (KPIs). Data can instead help us to understand how — and why — our customers are interacting with our brands in certain ways.
Go Beyond Reporting
Instead of seeing attribution-modeling results from a static report that might tell you to invest more in a specific display campaign, dig deeper to try to uncover the reasons why this display campaign might be more impactful. Overlay different audience segments to see if this holds true — or your higher-value customers versus your newer customers. Analyze deeper to see the different paths that a customer took to convert (or not convert). Understand the drivers and characteristics of these results to create brand new audience segments.
By using the advanced attribution features of Adobe Analytics, users can go beyond static reporting to start driving more customer-journey analyses. Attribution is a great tool to make your marketing more effective, but it is also only the beginning. Since higher sales and lower churn are things all brands hope for, it is high time that all brands start understanding what their customers’ journeys truly look like and what it is their customers truly value.