The reality of CRM data quality is sobering. While most organizations know they have some data quality issues, few realize the true scope of their problem. You might run periodic cleanup processes or use basic deduplication tools, giving you a sense that your data hygiene is “good enough.” But here’s the uncomfortable truth: the obvious duplicates you’re catching are just the tip of the iceberg.
Let’s start with what you probably already know about. Simple duplicates are the obvious matches — records sharing the exact same company name or website domain. These are the problems that basic deduplication tools catch: two records for “Acme Corp” both using acme.com as their domain, or slight variations like “Acme Corp” and “Acme Corporation.”
These duplicates are annoying but straightforward to identify. Most CRM platforms, including Salesforce, have built-in tools to catch these obvious matches. You might even have a regular process for cleaning them up. But if you think this addresses your data quality issues, you’re in for a surprise.
The real challenges lurk beneath the surface, and they’re far more numerous and insidious than simple duplicates. Let’s explore three major categories of other problems that are likely plaguing your CRM right now.
Hidden duplicates are records that represent the same company but look completely different on the surface. Consider Gusto, the popular payroll software company. Several years ago, it was known as ZenPayroll. Traditional deduplication tools see “Gusto” and “ZenPayroll” as entirely different companies because there’s no obvious connection between the names.
This happens more often than you might think.
Companies regularly:
Your current tools miss these completely because they rely on simple string matching that essentially looks for similar text. But company identity isn’t about text similarity, it’s about understanding the actual entity behind the data. The result? Your sales team might be pursuing a “new” prospect that’s actually an existing customer under a different name.
Beyond duplicates, your CRM is filled with records that are just plain wrong or incomplete.
Common issues include:
These problems compound over time. When a sales rep can’t find a company’s current name in your CRM, they create a new record — often with incomplete information. Now you have multiple partial records for the same entity, fragmenting your customer data even further.
Perhaps the most costly oversight is the failure to map company relationships correctly. Modern businesses are complex, with parent companies, subsidiaries, divisions, and geographic entities all interconnected. Think about Amazon Web Services (AWS) — it’s part of Amazon, but many CRMs treat them as completely separate entities.
This lack of relationship mapping leads to:
The challenge isn’t just finding these relationships once — it’s maintaining this understanding as companies evolve, merge, and change over time
These data problems don’t exist in isolation — they cascade through your entire organization, creating chaos at every level.
Your sales teams find themselves wasting precious hours pursuing prospects that aren’t actually valid opportunities, while simultaneously missing expansion possibilities within their existing accounts. When they do connect with prospects, they risk losing credibility by making uninformed outreach due to incomplete data. Even worse, territory disputes and commission conflicts arise as multiple reps unknowingly pursue different divisions of the same company.
Marketing faces its own set of challenges. Without accurate company relationship data, they end up sending conflicting messages to different parts of the same organization. Campaign effectiveness becomes impossible to measure accurately when you can’t trust your company records. Marketing teams may embarrassingly treat existing customers as prospects — a sure way to signal that you don’t truly understand your customer’s business.
For customer success teams, the impact is equally severe. They struggle to build effective relationships when customer data is fragmented across multiple records. Unable to see the complete picture of customer relationships, they miss valuable upsell opportunities and risk providing inconsistent service levels to different divisions of the same organization. A customer success manager working with one division might be completely unaware of issues or opportunities in another division, leading to uncoordinated and potentially conflicting approaches.
At the executive level, finance and leadership teams find themselves unable to trust their most basic metrics. Forecasting becomes an exercise in guesswork when you can’t accurately count your customers or prospects. Strategic decisions about resource allocation and market focus are based on fundamentally flawed data. Market penetration analysis becomes unreliable when you can’t properly identify and map company relationships.
Organizations that solve these data quality issues gain a significant competitive edge. Their sales teams spend more time selling and less time managing data. Their marketing delivers precisely targeted messages. Their customer success teams can proactively identify and pursue expansion opportunities. Most importantly, their executive teams can make strategic decisions based on reliable data.
It manifests across multiple dimensions of your business, creating both immediate and long-term consequences.
The direct revenue impact is perhaps the most obvious. When your teams can’t properly identify and map company relationships, they miss valuable expansion opportunities within existing accounts. Sales cycles stretch longer than necessary as reps waste time verifying information and dealing with data inconsistencies. Uncoordinated or inappropriate outreach can damage relationships and lose deals that should have been won. All of this adds up to significantly higher customer acquisition costs and lost revenue opportunities.
Operational costs mount in less visible but equally significant ways. Sales operations teams spend countless hours manually cleaning and verifying data instead of focusing on strategic initiatives. Valuable management time is consumed resolving territory conflicts that shouldn’t exist in the first place. The problems compound when you try to integrate your CRM with other systems — bad data in one system creates chaos across your entire tech stack. Organizations find themselves repeatedly training and retraining teams on data entry protocols in a futile attempt to maintain data quality through sheer force of will.
But perhaps the most significant impacts are strategic. Poor data quality creates a ceiling on your ability to scale operations effectively. Leadership teams make crucial decisions based on fundamentally flawed data, leading to misaligned strategies and wasted resources. In fast-moving markets, companies with clean, reliable data can react more quickly and seize opportunities while others are still trying to figure out what’s really happening in their CRM. Over time, this translates into reduced customer satisfaction, lower loyalty, and a significant competitive disadvantage.
The first step toward solving these problems is acknowledging their full scope. Your CRM data quality issues likely run deeper than you realize, and traditional solutions only address the surface-level problems.
Real improvement requires a comprehensive approach that can:
The good news? These problems are solvable with the right approach and technology. The key is moving beyond simple string matching to truly understand company identity and relationships. Only then can your CRM become the strategic asset it’s meant to be, rather than the liability it often is.
Take the first step today: contact Magellan Data to conduct a thorough assessment of your CRM data quality.
You might be surprised by what you find lurking beneath the surface.