With growing adoption of single customer views and other data aggregation technology, it’s clear that consolidating customer data is a major concern for marketers. The challenge is that it isn’t easy to see data from every part of the business and how it affects different customers and their buying decisions. Not only that, but customer data is inherently imperfect. Customers are inconsistent and often contradictory. And a huge portion of customer activity is difficult to track. For example, In-store systems can’t capture a customer’s information when they pay with cash. Even so, customers expect you to be consistent, even when they are not.
For data-driven marketers and marketing technologists, these difficulties make getting all the relevant data in one place a challenge. With solutions everywhere claiming to do the impossible task of making your data perfect, marketers are disillusioned. Many are even considering cutting their overall spend to help keep the volume of customer data under control.
As we’ve discussed in previous blogs, the best way to answer these concerns is using customer journey orchestration. We’ve heard from many marketers that they feel hesitant to begin customer journey orchestration. Most say that the reason is that their data is not ready to leverage for orchestration. Many of our clients have felt this as well. What they found is that though data is the foundation of journey orchestration, it doesn’t need to prevent you from beginning to build your customer journey strategy.
What if there was a way to improve your customer data management without building a new database?
Make no mistake. Data Management is a crucial piece of the overall journey orchestration goal. Without data that’s accessible and accurate, effective journey orchestration is nearly impossible. But marketers needn’t be intimidated. You don’t need all of your data in one place to get started.
Instead, data integration and consolidation is a foundational element to starting your journey orchestration process. So often, your data starts in silos, with different information gathered by and accessible to different parts of your organization. Many of our best clients recognized this problem and built their data strategy to solve it. This approach is shared among successful customer journey data projects. Start by figuring out how to use customer journey data where it sits. To do this, you will need to coordinate between departments and teams to work towards a common goal: the CX journey.
Why not start with making your customer data perfect anyway?
Even if we can start without cleaning our data, surely it’s better to have it perfect before you begin to automate? We disagree. Data is NEVER perfect. This is largely why database projects or even implementing a CDP can take years. The results don’t match up the first time and never will. Even if you could have a perfect database, customers are unpredictable. Data management will always be an imperfect science. Gaps will always exist in the information you have, and its quality. Given this reality, businesses must instead choose compelling, quantifiable results over the elusive “perfect” data.
If you chase data-perfection down a rabbit hole, you aren’t influencing the customer journey. This means you are missing the opportunity to influence your customers. If you can match a prospect and decide what their next best action content should be, then you’re taking control of the journey, even if you haven’t perfectly connected every datapoint in advance. By using data where it sits, you can strategize across your in-person and digital touch-points. By being agile with your data, you can ignite new business opportunities in the near-term, long before you will ever have near-perfect data.
Customer Journey Data Vs. Noise
How do you know which data is valuable and which is accurate when it isn’t perfectly clean? Customers may do a hundred things on your website without buying anything, or they may follow an ad, click purchase now and immediately check out. Customer journey paths exist in every possibility space in-between. What you need to track isn’t the transactional data of every click, blur, and hover. This is not what is most valuable. Instead you need to think about which steps matter on the journey. Beginning with the most basic identifiable information like name, location, and age, you learn more about the customer as they complete key steps.
While more and more granular data exists, the fundamental data that makes up the customer journey is the journey step. A journey step is a useful piece of customer journey data. Just like a molecule is made up of atoms, and the atom is made up of quarks, there is data that makes up each journey step. This sub-step data is much too granular to be useful. A journey step is navigating from a landing page on your website to another. Marketers need to know this to better understand the journey. Marketers don’t need to see that the customer hasn’t updated their browser.
What journey orchestration lets you do is examine each journey step for each customer, while shielding you from irrelevant data and noise. By using a system that can record and analyze journey steps, you can actually get ahead of the curve and get value out of your data much more quickly.
Marketers need to get their data in a good place in do marketing automation. Instead of getting bogged down in years-long data projects, or purchasing a new database before you even begin to get value, begin thinking about your strategy now. If you’re interested in learning more about how you can use good data to personalize great experiences, check out our guide to personalization. The strategy section in particular will prove useful if you’re trying to determine the best way to get started.