Why are so many marketers interested in customer journey analytics?
What if you knew exactly how a customer — scratch that, what if you knew exactly how all your customers were interacting with your brand? What if you were able to use all your data, from all sales and marketing channels, to determine what’s really driving people to (or away from) your business, with detailed insight into the most common and effective paths to purchase?
Sound intriguing? The results are compelling, too: Almost 60 percent of surveyed companies say they’ve experienced an increase in customer retention and loyalty after investing in customer analytics.
But it isn’t always an easy discipline to practice. And most of the challenges can be traced back to one problem in particular: data silos. In fact, when Adobe asked IT leaders to list their biggest obstacles to creating a comprehensive view of their customers, data silos were listed by 37 percent of respondents.
What Is a Data Silo? And Why Is It a Problem for Customer Journey Analytics?
A data silo is a collection of data that is kept separate and self-contained, making it difficult or even impossible for other users to access.
And that’s contrary to the whole idea of customer journey analytics, which brings together data from all channels and all customers to determine what’s leading customers to the point of conversion. By creating this comprehensive view of your customers, you obtain a more accurate assessment of what tactics are encouraging sales, leads, engagement and loyalty.
Customer journey analytics recognizes the reality that, for most companies, it’s not one marketing channel or message that generates business. Rather, your customers might need multiple touches across multiple platforms before deciding to make a purchase. So if you can’t see all your performance data, you could be missing an essential element in your analysis.
Data silos also slow down business insight. That’s another significant problem because, to be truly effective, customer journey analytics should be practiced in as close to real time as possible, so you can observe and respond to changes in consumer behavior ASAP.
What Causes a Data Silo?
Nobody decides to create a data silo. They usually just happen because different teams are using incompatible platforms or systems to measure their performance. Your sales team might rely on one piece of software, and your marketing team another. And neither system will easily integrate with the other.
At larger enterprises, the landscape can become deeply fractured, especially if outside contractors or agencies are handling a different section of your sales and marketing funnel. Your search, social and web teams might all employ their own favorite systems, which each produce datasets in their own idiosyncratic way.
Sometimes data silos are the result of culture. Teams aren’t talking to one another because they’re in different cities or buildings, and they’re each using their own taxonomies and data structures. Nobody feels the need to change because that’s the way things have always been done.
How Do You Prevent Data Silos When Analyzing Your Customer Journey?
Fortunately, data silos aren’t inevitable. With the right strategy and applied effort, you can break down the barriers that are keeping you from producing insight into what your customers really want.
It all starts with leadership, and a determination to create a centralized, holistic approach to collecting and sharing your company’s customer journey data. Your leadership — whether that’s your C-suite, your team leaders or you personally — must create the expectation that your entire organization, including outside teams or contractors, will coordinate efforts and operate from a common playbook.
You’ll want to build a complete picture of your entire data ecosystem. Your team needs to conduct a full audit of all the data sources that track customer interactions. What channels are you using to reach and interact with customers? How are you measuring those interactions now, and what do you want to know about your customers? And, most importantly, how does that advance your company’s strategy and bottom line results?
Once you know what you want to measure, and once you know which systems you’re using to do so, you’ll need to create a common strategy and naming conventions for assessing performance, and they must be faithfully observed by your entire team.
Single Source of Truth
And finally, you need to create a primary location for all this data. Even if individual teams keep their own storehouses, there needs to be a central data warehouse or a comparable data storage solution where your entire team (or at the very least, the people who need that data) can access it. Ideally, this storage solution should not lock you into keeping your data there. You should have the freedom to feed and share your data to any tool or location you choose.
If you’re looking for a solution like this, check out ChannelMix, Alight’s platform for marketing performance analytics. ChannelMix automatically aggregates sales, marketing or media data from any source, storing it in a fully managed data warehouse. ChannelMix supports a range of solutions, including marketing and campaign ROI, attribution and predictive modeling, marketing dashboards and, of course, customer journey analytics.
Tear Down the Data Silo
Do all this, and you’ll have taken a wrecking ball to your organization’s data silos, and made it more difficult for new ones to form.
There’s more to understanding the full customer journey, of course. You still have to interrogate the data, a process that usually involves more sophisticated techniques such as machine learning and attribution modeling.
But if you can tear down your data silos, you’ll have solved an important challenge, and built a foundation for creating an unparalleled experience for your customers.
Take the Next Step on Your Journey
Customer journey analytics is a core discipline for Alight Analytics, and our ChannelMix platform is uniquely suited to the challenge of managing the multiple data sources required for these kinds of insights, at the speed and scale you need. Our services team also can supply the expertise in data science and strategy necessary, freeing you from the need to hire full-time staff.