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Have you ever worked on a campaign that you thought was perfect? Despite a strong creative and strategy, it missed the mark.
The culprit could very well have been your data.
According to Invoca, 35% of marketers say poor data quality impacts their ability to target consumers with the right digital ads.
The truth is, even the best campaigns can fail if the foundation—your data—isn’t accurate, complete, or actionable.
So, what exactly makes data “good,” and how do you spot it? Let’s break it down.
Why Data Quality Matters More Than Ever
Every campaign you launch, every segment you build, every KPI you report on; it all starts with data. But if that data is inaccurate, incomplete, outdated, or irrelevant, your strategy will fail before it ever gets off the ground.
According to Agility PR Solutions, poor data quality costs marketers 21 cents of every media dollar. That’s not a small problem—it’s a direct hit to your bottom line.
What bad data creates:
- Wasted spend targeting the wrong people
- Irrelevant offers that don’t resonate
- Broken personalization (e.g., promoting something a customer already purchased)
- Erosion of trust, which is hard to earn and easy to lose
The impact goes deeper:
- Inaccurate records cloud performance measurement
- Messy databases increase compliance risks (GDPR, CCPA)
- Brand damage and fines can follow when privacy laws are violated
Example: You launch an email campaign with great creative and a personalized offer.
Instead of conversions, you see:
- Low engagement
- High unsubscribes
- Complaints
A review shows the audience list was built on stale, incomplete, and unverified data—full of inactive contacts, miscategorized profiles, incorrect locations, and duplicates.
It’s a costly mistake. According to WifiTalents, organizations lose an average of 12 % of revenue annually due to poor data quality issues.
The 4 Pillars of High-Quality Consumer Data
Here’s how to evaluate whether your data is actually worth acting on.
1. Accuracy
If customer records aren’t correct, everything built on them is unstable. Targeting, personalization, and reporting all suffer if the underlying details are wrong.
Why it matters: Inaccurate data damages deliverability, hurts engagement, and breaks trust. Even small errors—a misspelled name, wrong segment tag, or outdated email address can lead to misfired messages.
According to CUtoday, 75% of organizations believe inaccurate data is undermining their ability to provide an excellent customer experience.
- Common causes: Manual entry mistakes, syncing errors between systems, lack of validation processes, and third-party data without clear sourcing.
- Fix it:
- Run regular audits and verification checks.
- Use tools that validate email addresses and phone numbers at the point of entry.
- Work only with vendors who provide transparent sourcing and quality controls.
2. Recency
Even accurate data loses value over time. According to Gartner, poor data quality—including outdated or stale data—costs organizations an average of $12.9 million per year.
Consumers change jobs, preferences, and behaviors faster than most systems update. That’s why recency is a critical and often overlooked aspect of data quality.
Ask yourself: When was this data last updated? Is it refreshed in real-time, weekly, or only occasionally? Is it current enough for the campaign you’re running? Are your triggers based on recent actions or outdated behavior?
Why it matters: Outdated information leads to irrelevant targeting—like sending a “welcome” email months late or offering discounts to customers already in an active buying cycle.
- Common signs of stale data: Declining open rates, poor click-through performance, and increased bounce rates.
- Fix it:
- Refresh records in real time whenever possible.
- For non-real-time systems, set refresh cycles—weekly for active customers, monthly for inactive.
- Use behavior-based triggers to ensure your outreach aligns with the most recent activity.
3. Completeness
Partial data only gives you a partial understanding of your audience. A study by MarketingCharts found that 57% of marketers feel they are missing important data points that could provide them with a more comprehensive view of their customer.
Do you know their lifecycle stage, purchase intent, demographics, or communication preferences? These details are essential for precise segmentation and personalization.
Why it matters: Incomplete records make it harder to accurately segment your audience or predict buying behavior.
- Key missing fields to watch: Lifecycle stage, purchase intent, demographics, communication preferences, and past purchase history.
- Fix it:
- Use strategic enrichment to fill only the gaps that will drive meaningful action.
- Integrate data from multiple systems (CRM, website analytics, email platform) to create unified profiles.
- Train teams to capture relevant details at every customer touchpoint.
4. Relevance
Collecting everything just because you can often leads to clutter, confusion, and wasted effort. Not all data is valuable—only what helps you make marketing decisions.
According to a report by Seagate, 68% of data available to businesses goes unleveraged, underscoring the need to focus on collecting only relevant data.
Ask yourself: Does this data influence who I target, how I message, when I engage, or which channels I use? If not, it’s probably not worth collecting or managing.
Why it matters: Collecting too much irrelevant data adds noise and complexity without improving results.
- Examples:
- In B2C retail, a customer’s job title might not matter, but their shopping habits and product preferences do.
- In home services, knowing a homeowner’s renovation history may be more useful than knowing their favorite color.
- Fix it:
- Audit regularly to identify fields that aren’t used in targeting or decision-making.
- Focus on the data points that directly influence who you target, what you say, when you reach out, and which channels you use.
How to Improve Data Quality
Improving data quality doesn’t require a huge overhaul. Small, consistent steps can make a big difference in consumer marketing.
1. Audit Your Key Segments
Look at your most valuable customer groups.
- Do they still reflect real behaviors and needs?
- Is the data fresh?
A segment built six months ago may already be outdated—refresh it before launching new campaigns.
2. Clean Your CRM and Marketing Lists
Hygiene matters.
- Remove duplicates
- Fix formatting errors
- Revalidate inactive or old contacts
This improves deliverability, ensures personalization works, and helps you avoid wasted spend.
3. Rely on Trusted Data Sources
Not all third-party data is equal. Work with sources that are clear about:
- Where the data comes from
- How often it’s refreshed
- What steps are taken to ensure accuracy
The goal isn’t more data, it’s better data that actually drives relevance.
4. Enrich with Purpose
Add only the details that help you connect with consumers.
- Demographics (age, household size, income)
- Property data (homeownership, value)
- Interests or lifestyle preferences
Focus on the fields that improve segmentation, personalization, and campaign performance.
Conclusion
Having high quality data isn’t just nice to have, it’s a necessity for marketers. Without it, we can’t properly target our customers.
The real edge isn’t having more data. It’s knowing how to evaluate the right data and ignore the rest.
Put your own data to the test. Audit it, clean it, and enrich it with purpose. The stronger your data foundation, the stronger your marketing results will be.
