Driving personalized experiences through Customer 360
As a marketer, you understand how important it is to know your audience. Having a clear window into your customers’ behaviors and interests can make for incredibly compelling campaigns that drive loyalty and revenue. You probably even know that a whopping 78% of consumers report that they’re more likely to make repeat purchases and refer their friends and family to brands that offer a personalized experience.
This begs the question: If it’s so important to understand your customers, why do so many organizations seem to struggle with getting personalization right?
Imagining the Ideal State
Consumers interact with brands in a myriad of ways: purchasing products on the web or through a mobile app, placing a call to customer support, visiting brick-and-mortar stores, and reading product reviews before even heading to the store. For many teams, this data is collected and stored. When organized to create a single view of the customer, these interactions can tell a story about a customer’s likes and dislikes and their potential to churn or make future purchases. This data is typically housed in a data cloud and managed by a team of data scientists and engineers responsible for organizing and consolidating it for use across an organization.
Sounds wonderful, right? In an ideal world with the right tools, your data team would have this view built and readily available for the marketing team.
There are Two Main Hurdles Standing in the Way of Customer 360
First, the complexity for data teams tasked with developing a single view of the customer cannot be overstated. The process requires significant investments into centralizing the data into a single location, organizing the data and associating multiple records with a single customer, and then making the data available to the teams looking to take action on it.
Second, even if the data team is able to build this view, it can be extremely difficult–and impractical–to represent in third-party platforms. Many of the customer data tools that marketers know and love (like CDPs and CRMs) struggle to accommodate and organize such a large variety of data sources in a way that makes it accessible to the average user.
At this point, you’re probably wondering what can be done to combine the data collected by the marketing team with the organized data being housed by your data team–and how to access it. Keep reading to find out.