5 reasons your company could be dealing with a data quality issue
Data is a window into understanding not just how your business operates, but how consumers engage with, and select, your solutions. But according to this annual analyst report from Precisely and Drexel University, 67 percent of organizations don’t trust the data they are using for decision making. That means that your organization could also be dealing with unreliable data. When poor data leads to incorrect decisions, it can mean lost opportunities and wasted resources -- which costs your organization money. In uncertain times, a business's livelihood could even be on the line.
Data quality -- especially when it comes to Marketing, Advertising and Sales data -- impacts how teams assess and move forward in the marketplace. These teams lean on datasets to adjust outreach activities and awareness campaigns. The insights used from data are often the underpinning foundation for how a business not just orients itself for short-term quarterly goals, but also how an organization pivots to gain an edge on competition in the long term.
Chances are, your data could use a clean-up. Here are a few tell-tale culprits that could be leading to bad data quality in your marketing team, and what to do about it.
- You Are Creating Data Chaos Behind the Scenes
Every decision you make is only as good as the data behind it. Without strong data collection and governance, you’re building your entire strategy on a shaky foundation. Sloppy schemas, inconsistent segmentation, and disorganized repositories don’t just create technical debt -- they create decision debt that compounds over time.
When your data doesn’t fit the real needs of your business -- your industry, your size, your unique culture -- it starts to distort everything downstream. Your Marketing team may misidentify your ideal customer profile. Your sales strategies might target the wrong segments. Leadership could waste time chasing phantom opportunities.
In short: bad data in, bad decisions out.
If key details aren't collected accurately, governed properly, and made accessible at the right moments, they fall out of your decision-making trees altogether -- or worse, they lead you in the wrong direction. You can’t afford that kind of chaos when the margin for competitive advantage is razor-thin.
Good data governance isn't just a box to check off -- it's crucial to protecting the future of your business. Every clean schema, every well-structured dataset, every intentional segmentation choice stacks the odds in your favor.
- You Have a Data Drift Problem
It’s not just siloed teams that can be an issue for a business -- siloed datasets can be a problem, too. When sources for data collection change upstream, they could have rippling impacts on the quality of your data pipeline overall.
There’s a difference between having siloed datasets between business apps and platforms and having delineated, private repositories for those datasets. A multi-tenant environment for data storage may have implications on possible data exposure from a simple mistake created by an outside source, whereas a single-tenant environment is a private location that could be far harder for such data to be exposed. Here, setting up role-based access for a single environment location -- where only your organization has access -- can introduce cross-departmental collaboration without the risks of a shared storage space with other organizations.
In any case, it’s paramount that when changes occur in data sources upstream, your team also cross-checks that downstream data interpretation hasn’t been adversely impacted.
- Your Teams Are Struggling to Collaborate
If your developers and data teams seem to be speaking different languages when it comes to your datasets, you could have an underlying issue with the quality of your data. It’s also a chicken and egg situation because not having teams aligned could be a cause for poor data quality, impacting how data is deposited, tracked and assessed.
Aligning teams on the same understanding of terminology, testing, tracking and data repository actions could reap big rewards in driving your business forward. Plus, poor data could impact other important areas of business like regulatory and compliance readiness, preventing your security teams from properly preparing for audits. Data should enforce both day-to-day operations and your company’s long-term strategies. Not only that, having accurate data allows all business departments -- not just Marketing and Sales -- to align behind a single source of truth, which empowers collaboration.
- Your AI Implementation Isn’t Reaping the Intended Results
As more organizations harness the power of artificial intelligence (AI) to leverage speed in their business processes and tailor outreach to customers, it’s key not to neglect the need for a human feedback loop to ensure the data collected is being analyzed effectively. Having a human being occasionally assess and monitor the efficacy of your AI engine is essential to ensuring that systems aren’t running wildly off course. Plus, something like AI-generated marketing messages to prospective customers must always have a quality assurance step for brand verification.
The real-world impacts of AI are yet to be fully realized, and having consumer insights into how you could be using data to influence your AI usage will be invaluable to maintaining a competitive advantage -- but only if that data is accurate.
- Your Data Syncing Is Too Slow
Modern-day Marketing and Sales teams leverage several platforms and business applications to digest, assess and run their operations more smoothly. A complicated tech stack is just the norm for any business today. But sometimes these systems and apps might not be communicating with each other, due to connectivity or integration issues. This could mean data accuracy is at risk when systems aren’t syncing quickly enough. Real-time data processing and syncing is the answer to ensuring all systems are communicating for business needs. To do this, data storage and data handling policies need to be examined. Establishing end-to-end encryption for when data moves between systems and is at rest will, in turn, reduce the risk of cyber breaches.
The Future is Data-Driven, Which Means You Need Reliable Data
Poor data quality can be a silent killer for any business, costing millions and hindering growth. The culprits holding back your data must be addressed with effective and efficient precision. In an era of evolving data challenges, having a reliable, high-performance solution is paramount, which means actions like setting up isolated environments for your data, introducing real-time data processing and ensuring alignment between your teams can all have downstream effects on your business viability.
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As MetaRouter’s Head of Product, Greg Brunk leads our team in setting the strategy and building out our Customer Data Infrastructure platform. Greg has a diverse and rich history in leadership, driving innovation through product in several industries. He is now blazing a trail in the marketing, advertising, and data space. He is well-connected with the industry's emerging trends and is deeply involved with MetaRouter's sales, CX, and partnership teams.