With the proliferation of new tools and technologies, businesses are collecting, generating and storing data on more platforms than ever. Between marketing automation tools, CRMs, help desks, website analytics and beyond, businesses have been stashing data in pockets across departments. But while the specialization of tools is great for getting each team’s job done, this fragmented data makes analysis and deeper insights into your customers very difficult.
If you’re struggling to make sense of business data and piece together a single view of your customer, it’s likely that data silos are to blame. In this article, we’ll show you how to break down the walls, connect the dots and get more out of your CX program.
Data silo problems in the world of CX
If you struggle to utilize the data your company collects, you’re not alone: 80% of companies report moderate or high degrees of data silos. Much of this is because of how quickly data collection can expand - in fact, more than half (56 percent) of IT professionals cite “exponential data growth” as a major challenge.
Why is data siloing such a big problem? It dramatically impacts the way your business operates, especially at the strategic level. Companies experiencing data silos can have:
- Poor visibility into customer trends: Having a single view of the customer is critical to understand what your customers want. However, 69% of companies report that they are unable to create a single view of the customer. With disjointed data, it’s impossible to follow the customer journey and see what’s working - and what’s not.
- Flawed strategic decision making: Executives are basing 48% of decisions on intuition or personal/company experience rather than on quantitative information and analysis. Even when businesses are using data, there is no guarantee that it’s accurate and measured the same across every department.
- An inability to execute on the customer experience - At each touchpoint, the front line teams need access to customer data to provide a great experience. Whether it’s refunding a payment, seeing past interactions or just knowing who the customer is, front line teams can do their job better when departments work together.
4 strategies for breaking down data silos
One: Consider the customer journey
At any one point, the customer could be interacting with multiple systems. At every touchpoint along the customer journey, they could be having a marketing experience, a product experience or a service experience - each of which is generating its own set of data.
One way to break through the silos of data is to consider each touchpoint from a customer’s perspective, rather than from a department’s perspective. For example, consider a customer opening a new savings account at a bank. What systems are they interacting with? What data do they need to provide, and what data do you already have available?
When you consolidate data across multiple streams, you get a much richer view of the customer’s experience at each touchpoint. Plus, you can use multiple data sources to make their experience better - both through proactively suggesting next steps or not asking for data you already have.
Two: Appoint a data owner
If you do handle any data storage in Europe, the General Data Protection Regulations (GDPR) already require you to have a data protection officer (DPO) in place. That person is responsible for overseeing the security and privacy regulations and implementing GDPR internally. This person works cross-functionally to ensure that every department follows the regulations outlined.
Whether or not you have a DPO, having a cross-functional person accountable for your company’s data can help eliminate silos. When teams need a new data set or implement a new tool, consulting with a data owner can help identify opportunities for integration and prevent additional silos. The data owner can also help coordinate efforts to pull data together for a more holistic view of the customer journey. You might also call them a “data evangelist” but regardless of their title, this person can help you uncover and take advantage of opportunities within your data practices.
Three: Find tools that work across channels
While specialized tools can be great for providing the best possible experience for customers, channel-specific tools can cause issues when trying to put together a single view of the customer. Whether the data is stored separately, or in different formats, analyzing data from multiple channels can be quite tricky.
Some analysis tools are data agnostic, like Kapiche’s text analysis software. It doesn’t matter where the data was collected from (survey collection tools, customer support platforms, CRMs or external online reviews). As long as you have a mix of structured and unstructured data, Kapiche can pull out actionable insights.
A data lake is another potential solution for companies that store and analyze a lot of data. In a data lake, all data is stored in a raw format which is easily accessible to analysis tools. Tools that collect data dump all information into the data lake, and tools that utilize data dip into the lake to pull out what they need.
Image: 5 Questions to Ask Before Implementing a Data Lake, Sisense
However, a data lake can require more engineering knowledge (specifically in big data best practices) than a data warehouse. Consider carefully what your future plans are before investing in a data lake.
Finally, the use of Open APIs and integrations can help reduce silos. Building a “single source of truth” where every platform reports back to one central data system can effectively pull together disparate data sources and make them easier to manage.
Four: Combine operational data with business metric data
Ultimately the point of breaking down silos is to be able to make better business decisions. Combining operational data (like customer satisfaction surveys, customer feedback, and product usage) with business metrics (such as lifetime value and churn) helps inform strategic decision making.
One technique to break through data silos is to start by deciding what question you want to answer, and then pull together the data required to answer it. By finding the gaps in the data, you can start to build bridges across platforms.
For example, consider the process of evaluating customer feedback. Your product team wants to know what the highest spending customers are asking for. It makes sense - if your top customers are happy, they will be likely to stick around and recommend you to their friends. However, when customers submit feedback to your customer support team or talk about your product in reviews, they don’t tell you how much they spend with your company. Instead, you need to connect their feedback with their past purchases. Connecting text and qualitative feedback with your CRM data can help you make more informed product development decisions.
The wealth of information contained within your business data is incomprehensible. To access it, however, requires pulling together departments with competing priorities and incompatible platforms. In short - you’re going to need to put in some effort to find it.
But it’s worth it. When you’ve broken through the walls and pieced together a holistic view of your customer experience you can start to make decisions based on data - rather than on gut feel.
What comes next in the world of customer data Start putting it to work for your business!
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