Six Ways Data Silos Complicate Your Customer Experience
No matter the initiative or project, every effort you make to better your customer experience (CX) starts with data. Whether it’s omnichannel, transactional, relationship, loyalty, or feedback data, you need data to make informed decisions that positively impact your business.
Given it’s all-important status, it’s vital for your data to be accessible and stored in a way that enables your team to unearth insights efficiently and effectively. As with all things, however, this is easier said than done.
Unfortunately many companies still house customer data in silos, or in separate warehouses depending on data type or what vendor, app, or platform it was collected in. This practice can complicate your view of customer data, resulting in an incomplete, distorted, or even inaccurate view of your customer.
In the big picture of customer experience, this distorted view of data can be devastating, but there are even more ways that data silos can put your CX program in danger. In this post, I will break down six problems that stem from data silos, as well as the challenges they present.
1. Inability to Scale Your CX Program
As an organization grows, one would hope that their CX program would be able to scale with them. Unfortunately, if that organization is using multiple silos to store their customer data, this isn’t possible. Each silo would scale independently of the others, making navigating the CX program more and more complex as the company evolves.
2. Time-Consuming Process
The more silos, the more time it takes to compile and regulate data. In fact, a recent study showed that data scientists spend approximately 80% of their time preparing and managing data for analysis. This means that data scientists are using most of their time compiling data and only 20% of their time analyzing it for the insights that could make a big difference to their organization.
3. Excessive Costs
Multiple vendors require greater headcount to manage and operate those platforms. When the average enterprise marketing department uses 91 applications (even though many of those may not be CX-specific) supporting multiple vendors and their data silos can be costly.
4. Difficulty Sharing Information
A successful CX program depends on the ability to share data. Unfortunately, the evolving nature of CX software causes compatibility issues between different data platforms. Furthermore, any attempt at combined analysis of data silos can be difficult at best.
5. Disparate View of Customer
To get the best possible understanding of your customer and to understand how they experience your brand, it’s important to get a holistic view of your customer data. When your data is siloed, however, the insights you get will be specific to only one type of customer, area of the organization, or chapter of the customer journey, limiting the effectiveness and actionability of the insights. This segmented approach can then create a disconnected understanding of your customer journey.
6. Can’t Identify Higher Priority Issues
The segmented nature of data housed in silos also creates an inability to distinguish higher priority issues across the organization as a whole. It may be possible to determine the problems that need to be addressed within each silo, but any insights revealing issues will only represent issues for one type of customer or area of the business, not the higher order issues that affect the organization as a whole.
When it comes down to it, data silos can do more than complicate operations for your CX program. They can undermine your efforts by giving you ineffective “insights” that do not address the overarching concerns of your customer. It takes a company-wide initiative to refocus on what your customers need, and that means unifying your customer data so you have the best foundation possible for your CX vision.
To learn more about data silos, the complications that come along with them, and how a unified approach to CX could combat them, download InMoment’s newest white paper, “Customer Experience Management: The Danger of Data Silos.”