Revenue Operations (RevOps) teams face an ongoing challenge to increase revenue and reduce costs while providing excellent customer experiences. But a critical challenge RevOps teams often face is maintaining accurate and complete data in their Customer Relationship Management (CRM) systems. CRM data leakage, where data is lost or incomplete due to incorrect data entry or system integration errors, is a significant problem that can hold back growth.

What is CRM data leakage?

CRM data leakage happens when poor data quality finds its way into your CRM. When that happens, every data-driven aspiration you had for your revenue organization simply disappears.  Sales reps loosen their data entry habits, executives lose trust in their data and eventually decisions are made solely based on gut feelings. It’s as simple as that –  bad CRM data quality costs you valuable time and money.

Missing sales targets due to CRM data leakage is more common than you think. If your CRM isn’t constantly checked for bad data and updated with new and enriched data – It’s just going to start working against you. 

If your team are not being trained on CRM data entry, if you don’t document CRM data entry playbooks and enforce those,  you’re most likely leaking revenue as much as you leak data. 

If you diagnose yourself with a CRM data leakage disease, treat it before it’s too late. It is urgent, and the longer you wait, the more your growth suffer. you don’t want to be like most companies that lose and average of $14M a year due to to data leakage, according to  Gartner survey.

Why is CRM Data Leakage Harmful to Revenue Growth?

Let’s face it, inaccurate data is like a ball and chain that’s holding us back from achieving our revenue goals. Let’s take a look at some examples of how bad CRM data impacts revenue operations:

Bad forecasting –  Imagine you have incomplete data on deal size or likelihood of closing, and you make revenue predictions based on that data. As a result, sales teams may focus on the wrong opportunities, and deals with high potential for revenue may fall through the cracks. This can lead to missed targets and lower revenue growth, throwing a wrench in your revenue operations.

Bad pipeline management – Suppose you don’t have the right data to prioritize deals effectively. In that case, you may miss opportunities or experience delays in closing deals, ultimately affecting revenue growth. For example, let’s say your data doesn’t reflect the correct deal stages, and sales leaders make incorrect assumptions about the progress of deals. This can cause difficulties in identifying and addressing potential bottlenecks in the sales process, leading to a less efficient pipeline and ultimately affecting revenue.

Bad reports –  Suppose you create reports based on incomplete or inaccurate data. In that case, you may make decisions based on misleading insights that can hurt revenue growth. For example, let’s say you have data leakage in your CRM system, and some data is lost or corrupted. This can lead to reports that don’t reflect the real situation in your sales pipeline, causing you to make decisions that negatively impact revenue growth.

The cost of bad CRM data –  Suppose your data is incomplete or inaccurate. In that case, you may need to spend more time and resources cleaning it up, diverting resources from other important initiatives that could drive growth. For example, let’s say your data is inconsistent, and you need to spend more time fixing data errors instead of optimizing sales processes or developing new sales strategies. This can lead to increased costs and lower productivity, ultimately affecting revenue growth.

Bad CRM data is the backbone of revenue operations. Inaccurate data can lead to missed targets, lost opportunities, and lower revenue growth. It can cause difficulties in identifying and addressing potential bottlenecks in the sales process, misleading insights, and increased costs for cleaning up and maintaining data.

“It’s important to tie data hygiene back to revenue and value. By focusing on key fields that are critical to specific initiatives, organizations can prioritize data hygiene efforts and generate better outcomes”.

– Sam Sweeney, Sales Operations Manager in his Sales Brew interview – 

How to Address CRM Data Leakage?

Addressing CRM data leakage requires a combination of data hygiene best practices and data automation tools that help ensure data is accurate, complete, and up to date.

Implement Data Hygiene Best Practices

Make sure your BI tools are not affected by CRM data leakage

BI tools rely on the data they’re being fed, but your data might be scattered across multiple platforms and systems, making it difficult to bring it all together. To overcome this, consider using data integration tools to streamline the process and ensure siloed CRM data is aligned and your data is accurate and up-to-date.

Another challenge is ensuring the security and privacy of your data. With so much sensitive information in your CRM, you need to ensure that your BI tools can access the data they need without compromising security. To overcome this, work with your IT team to ensure that you have the proper security protocols in place and that your BI tools are configured correctly.

Lastly, it’s important to consider the level of technical expertise required to implement and maintain BI tools. While these tools can provide invaluable insights, they also require a certain level of technical know-how to use effectively. To overcome this, consider partnering with a BI vendor or investing in training for your team to ensure that they have the skills they need to get the most out of your BI tools.

With these challenges in mind, integrating BI tools into your CRM can help you unlock insights that can drive revenue growth and improve your decision-making. So don’t let bad data hold you back, take the necessary steps to integrate BI tools into your CRM and get ready to see your business soar!

CRM data leakage is a significant problem that can hold back revenue growth. RevOps teams must prioritize data hygiene best practices, implement data automation tools, and invest in data analytics to maintain accurate and complete data in their CRMs. By doing so, they can reduce the risk of bad forecasting, bad pipeline management, bad reports, and increased costs, enabling better decision-making, and driving revenue growth.