Improving CRM Data Quality: Best Practices for Sales and Marketing

When it comes to business decisions, your outcomes are only as strong as your data. Whether it’s targeted lead generation, prospecting, personalized client engagement, market segmentation, campaign optimization, or predictive analytics for sales forecasting, CRM data quality is crucial to maintaining a competitive edge.  

But with vast amounts of data at your fingertips, how can you ensure it drives value rather than adding complexity? It’s not just about the quantity of data—it’s about managing and maintaining its quality to ensure it delivers meaningful insights. 

Earlier this year, Altrata COO Connel Bell and RelPro CEO Martin Wise discussed this critical topic, highlighting the growing impact of AI on CRM data management. During their conversation, Connel and Martin shared valuable insights on improving CRM data quality, and the real costs of poor data. ​​Here’s how your business success depends on data practices and why addressing bad data is more critical than ever. 

Why does data quality matter?

First off, what exactly does “good data” mean? According to Connel, it’s simple: “Good data is data that delivers value.” But there’s nuance here. Value doesn’t come from having more data. Instead, value comes from clear, trustworthy data that directly informs the decisions you make. 

For sales and marketing teams, investing in improved sales data quality directly translates into efficiency and better outcomes. If you’ve ever experienced a sales cycle stretched thin by outdated contact information, duplicate entries, or incomplete client histories, you know firsthand how poor CRM data quality drains resources. Quality data isn’t just nice to have; it’s critical infrastructure. 

In other words, improving your data isn’t simply a cleanup task; it’s strategic. When your CRM contains timely, accurate, and complete information, you can quickly identify your best opportunities, craft targeted outreach effectively, and build relationships with confidence. If you’re wondering how to improve CRM data quality, start by viewing it as a core component of your strategy, not an afterthought. 

The true cost of bad data

Everyone agrees good data matters, but the actual cost of bad data is often underestimated. Poor data quality translates directly into wasted time chasing incorrect leads, inaccurate sales forecasts, and ineffective marketing campaigns that miss the mark. 

Martin first mentioned this point during the conversation, noting that unreliable data can also lead to compliance risks (monetary costs), internal confusion (time costs), and even damaged client relationships (growth costs). The costs of not keeping systems clean and useful are clear and will always be more than the costs of doing it correctly. 

​​Later, Connel also brought up the importance of investing proactively, adding that good data practices aren’t just about avoiding losses, they’re about positioning your team for better decision-making and smarter growth. When you have accurate data, your team can confidently target opportunities, build meaningful relationships, and clearly communicate your value.​​​ 

Does AI play a role in data quality?

​​​AI’s growing influence is highlighting the cost of bad data, bringing it to the attention of business leaders and boards alike. As Martin explained, even minor inaccuracies can lead AI to generate flawed insights, resulting in misguided decisions and wasted resources, with Connell adding that poor-quality data wastes valuable computing power and time. If you want good outputs, especially when you’re using AI, you need to make sure your inputs are flawless. 

The golden rules of data quality

What defines good, high-quality data? 

​​A​t its core, quality data typically includes accuracy, completeness, uniqueness, consistency, relevance, and timeliness.

To start, focus on accuracy. Are names spelled correctly, titles current, and contact details up to date? Completeness is next. Does each entry include essential information for your sales or marketing teams? Then, consider consistency and uniqueness. Do you frequently encounter duplicates or inconsistencies in formatting? Finally, relevance and timeliness ensure your data is not only technically correct but also genuinely useful to your team. 

According to Martin, simply acknowledging these rules isn’t enough. “You need clear processes to maintain data quality proactively, not just fix problems as they arise.” Organizations that embed these golden rules directly into their workflows significantly reduce the risks of bad data and improve the outcomes of their strategic initiatives. 

Not just “clean data”, but aligned data

Improving CRM data quality is most effective when it aligns directly with your business objectives. It was heavily emphasized during the conversation that data should never exist in isolation.

Identifying the right data points is critical to ensuring high data quality for marketing and sales activities, aligning closely with your strategic goals. For sales teams, this might mean focusing on client purchasing histories and job changes. For marketing, it could mean prioritizing demographic data and behavioral insights. 

Connel recommends first identifying your high-priority data points. Once identified, clearly communicate their importance throughout your organization. Then, organizations should start small with manageable data-improvement projects tied to clear outcomes. As always, make sure you’re measuring the impact of these initiatives, so you know if it is actually working. 

The main takeaway is straightforward: effective data management is less about cleaning up databases and more about ensuring your data supports clear business goals. By directly connecting data improvement to desired outcomes, you can show clear results for continued progress along the “data improvement path.”  

Integrating data quality into your CRM and sales workflow

Maintaining good CRM data quality is not a one-time event, either. According to Connel and Martin, truly effective CRM data management integrates quality checks directly into your ongoing processes and workflows. For sales teams, this could mean regularly scheduled reviews of CRM entries, verifying new contact information at each client interaction, or automating data enrichment processes to keep records fresh. 

Martin explained the practical impact, emphasizing that better data means better relationships. Clean CRM data helps your sales team identify opportunities faster, understand clients’ needs better, and build meaningful connections without unnecessary roadblocks. Additionally, integrating CRM data enrichment tools is one of several CRM data quality best practices that significantly reduce manual entry errors and ensure accuracy. 

Data management tools make daily tasks easier. They boost your team’s success. They help you convert prospects. It sounds simple, but it’s incredibly effective.  

Leveraging strategic data partners

You don’t need to manage data quality alone. Connel and Martin highlighted that strategically partnering with reliable data providers can significantly improve your CRM data quality without overwhelming internal resources. Specialized partners can quickly fill gaps and make things much easier. 

Platforms like Altrata provide trusted, timely intelligence around executive roles, wealth indicators, and relationship insights, enabling organizations to enrich their existing CRM seamlessly. When choosing a data partner, organizations should look beyond a simple transaction and seek providers committed to delivering continuous value through data that is actionable. 

In short, leveraging strategic data partners allows your teams to focus on core business objectives instead of tedious data management.  

Ready to make data quality your advantage? 

Improving CRM data quality isn’t just about avoiding mistakes. It’s a strategic choice that directly fuels smarter decisions, deeper relationships, and sustainable growth. As Connel and Martin shared in the conversation, better data practices help your sales and marketing teams operate with clarity and confidence, letting them do what they do best: build connections and drive revenue. 

Now’s the time to evaluate your own approach. Are your current CRM and sales workflows as strong as they could be? Are you leveraging trusted data partners to stay competitive?

Prioritize your data quality today, and watch it become your most valuable competitive edge. 

Altrata doesn’t just give you better data. It helps you maintain it and put that data to use. By enriching your CRM records, discovering triggers for outreach, and leveraging your client networks and connectivity, Altrata helps your teams see real opportunities more clearly, connect with the right people faster, and understand clients better.

Whether you’re looking to find new prospects, build stronger relationships, or grow existing accounts, Altrata makes sure you have the right information to get the job done. Learn more by scheduling a free demo today.