Why you should care about your data management (yes, you!)

Though trusting your gut can have advantages, some decisions require data to lead us to insight, then action. High-quality data enables confident decision-making, no matter whether you sit in the C-suite or marketing, sales, or service department. With access to the right information, you can assess current performance and predict future performance. 

This is where business intelligence (BI) platforms come in. They let teams extract insights out of complexity, simplify analysis, and speed up decision-making.

Following data management best practices will go far in protecting your business from unwanted data losses and data breaches. Data security is most important where data is sensitive, such as health or financial information, and where it needs to comply with HIPAA or GDPR laws, for example. Doing the right thing means you’ll never think twice about data security.

Quality data empowers salespeople to leverage data throughout the sales process. There’s actually a term for this: data-driven sales enablement.

For example, salespeople can refer to lead scoring and determine which prospects are most likely to close. Rather than wasting time and energy trying to convert bad fits, you can conserve resources and provide extra attention to your ideal customers.

Data-driven sales enablement also lets salespeople continuously track sales data, resulting in higher individual and team performance.

A surefire way to speak directly to your audience is with data-driven marketing. 

Say you’re running a lead-generation campaign. It will be far more targeted and impactful using data than basing decisions on assumptions. With ample data, you can personalize content and target audiences at any stage of the buyer’s journey. That’s a win for potential customers, who benefit from timely, relevant content, and for marketers, who can then refine their strategies.

Customers expect consistent and tailored experiences from the businesses they engage. Always. So any data previously shared with you should be used to meet their expectations. For example, customer service teams can deliver faster, personalized advice with historical data housed in one place. 

You can also delight customers with customized offers that grow CLV. Provided your business has data management in order, you should be able to log into your CRM to identify (and engage) the most profitable customers.

When teams’ decisions are powered by high-quality data, they work in unison to lift productivity and improve revenue. Over time, a data-informed culture forms, one that makes smart choices and optimal outcomes, leading to bolder growth.

Knowing how to “do” data management starts with knowing what not to do first. But without a strategy in play, the chances of your team knowing what’s best are slim. How would quality decision-making happen? Unfortunately, it wouldn’t — at least not accurately.

Siloed data stays out of mind. Most likely, team members will be unaware information exists by virtue of it living outside their business function and/or within a platform they don’t know about. This reduces data accessibility and visibility, prevents knowledge transfer, hampers collaboration, and creates friction between teams. Data is useless in isolation and its business value increases significantly once integrated.

Data governance defines the people, processes, and tools used to manage and protect an organization’s data. Think of it as one of the many essential ingredients of good data management. Businesses tend to go wrong by not defining the “who” and “how.”

Without data governance, no one is accountable for data-related decisions and risk mitigation. Which brings us to the biggest mistake of all...

Data privacy and security remains a hotly debated topic for enterprises and consumers alike. Take, for example, the recent string of data breaches in Australia. Customers tend not to forget the fallout, even after the dust settles (Cambridge Analytica, anyone?).

So it goes without saying that proactively protecting enterprise data in all forms is absolutely crucial. Don’t be complacent in your data security. The reputational cost of data misuse or a data breach is not a risk worth taking.

Were any of these mistakes relatable? Read on to find out how to create a data management strategy that everyone can stick to. 

When we talk about “data maturity,” we mean how well a business uses its data (more on that here). An assessment of your business’s level of data maturity will reveal your current problems and what might need to change.

You might like to ask yourself and other business functions questions like:

• What types of data exist in our business?
• Who currently interfaces with and manages those data?
• How are we using qualitative and quantitative data, and why?
• How do teams typically monitor and measure their versions of success?
• What problems do we repeatedly encounter when analyzing data?

Once you start looking for problems — and we mean really looking — you might discover more than you anticipated. Often, there are a number of reasons why things aren’t working.

If you realize your data or related practices aren’t up to scratch, don’t sweat. It’s fixable! Take a breath and move onto Step 2.

Next, consider your data needs per your objectives. We recommend balancing two data strategy frameworks as you create the new architecture: offense and defense.

Data offense involves optimizing your analytics to enhance decision-making. On the flipside, data defense emphasizes protecting data security and remaining compliant. Both have value in your data architecture.  

Here are a few questions to help you plan it out:

• Where will your data be stored?
• How should it be organized?
• How should it support decision-making?
• How will it be kept secure?

Knowing the answers will help you build a plan that’s bespoke to your business, including the systems you might need. Top-tier tools like HubSpot Operations Hub allow you to transform the complex nature of data management into something much more manageable. In an ideal world, that’s how data management should be. 


Source: HubSpot

Every business function has different data needs and means of managing it. Case in point: both sales and service benefit from contact records in the CRM, yet the reasons for using them are entirely different.

Consulting every business function at Step 1 will give you a clear picture of their needs and habits. Only then can you assign data ownership to keep team members engaged and accountable.

Lastly, establish a concrete set of policies that inform how data will be collected and stored to maintain quality. While documentation is crucial, we recommend putting your energy into coaching teams to adopt the new standards. If you demonstrate the benefits and practices as they relate to their roles, they’ll get on board. Then, it’s up to everyone to do good data management.  

Before you embark on formulating a data management strategy, understand that it isn’t a once-and-done event. You’ll need to regularly review the strategy to shake out any blockers or bottlenecks and replace them with practices that improve business outcomes.