Proper interpretation of customer data is essential for your company to provide high-quality service. Multiple data streams dump high volumes of information into your enterprise systems every day, but you can only make use of it if you take the right approach to analytics.
Unfortunately, companies often make mistakes when collecting and examining data. The resulting strategies often fail, sending businesses back to square one with no idea of why their tactics aren’t working. If you find your company in a similar situation, analyze your approach to see whether you’re making these common errors.
Analyzing Without a Focus
You would never jump into a big project without a clear idea of what you want to achieve and a plan to make it happen. The same should be true of how you handle big data analytics. Companies often collect and analyze information simply because corporate leaders feel pressured to have a “data strategy.” They’re left with a collection of useless statistics they can’t apply because they don’t know how the numbers translate into actionable tactics.
To develop a profitable approach to data, revisit the main goals of your company. Choose to focus on one or two major points, such as signing on more clients or improving customer service, and work with data scientists to interpret incoming information in ways designed to point you toward success.
Not Connecting Data Streams and Systems
All the information your business collects is interconnected and should be treated as such. Sales data is tied to inventory management, supply chain delays affect inventory levels, order fulfillment depends on a clear knowledge of sales and the customer service department needs to know what’s going on across departments.
Look for ERP and CRM systems with the integrations necessary to collect customer data and pass it on to the correct departments in real time. Handling data this way cuts down on errors and ensures each department has access to the latest updates. Cloud-based services offer the best options for modern businesses, especially if you have remote employees.
Ignoring Data Security
Making the most of collected consumer data requires consistent access. If you don’t have a backup plan with redundant copies across multiple servers, you run the risk of losing massive amounts of information.
Setting up a VPN for employees to use when working remotely adds another layer of security. VPN services encrypt data as it is transmitted and provide alternate IP addresses, making it difficult or impossible for third parties to track online activity. Some VPNs offer additional tools to prevent unwanted tracking.
Big data is aptly named and very attractive to malicious third parties. Putting security measures in place is necessary to prevent the theft or loss of information on which you rely to run your business. Do everything you can to increase security, including:
• Analyzing potential points of vulnerability.
• Adding pertinent security and encryption to all weak areas.
• Hiring security experts to facilitate implementation.
Cleaning up your approach to big data analytics and aligning it with the goals of your company allows you to leverage all pertinent information from your target audience. Put the right data tools in place, work with skilled data scientists and follow a detailed plan to make data pay off for your business in a big way.