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6 data management mistakes to avoid

Last updated: October 11, 2023

Data is the lifeblood of business: It gives you the information you need to to learrn about your audience, drive better decision-making, create personalized experiences and ultimately, earn more revenue. 

But mistakes in your data managment strategy can just as easily complicate your reporting efforts and make it harder to serve your audience. Make your data work harder for you by avoiding these key mistakes:  

1. Siloing your data management and compliance efforts  

Do you have customer data spread across multiple solutions? If so, run the risk of creating multiple profiles for each customer, making it more difficult to understand  For instance, your website analytics solution has one profile with Lisa’s browsing activity, but your email service provider has another one including all of her email opens and clicks. Without one place to view all of Lisa’s interactions with you, you can’t really know what she wants from you, much less give it to her.   

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Avoid this by eliminating data silos whenever possible. One of the best ways to do this is by using a customer data platform for your data management needs. CDPs take in customer data from every touchpoint — from email and website to print, events, offline, etc. — and centralizes it in one database. This gives you a single profile for each person that interacts with you, whether they’re coming from your website, email, events or multiple channels. 

CDPs also make it easier to complete compliance tasks as required by the GDPR, CCPA and other data privacy regulations. Because data from every channel is stored in one place, you only need to delete Mary Smith’s record once to fulfill privacy laws, rather than checking every platform to see if Mary Smith has a record there as well.    

2. Not tracking customers with a persistent ID  

If you track customers by their email address, someone’s profile will go dormant every time that they change that address. (With quit rates nearing all-time highs, expect to see a lot more of this.) From your perspective, that inactive email is a churned audience member, even if the person behind the email address continues to engage with you via their new professional email.  

Multiply that over hundreds or thousands of users and it really starts to distort your data. You might see a lot of highly engaged email addresses that suddenly went dormant — and no underlying pattern to explain it.  

At the same time, you might see some brand new profiles in your database that seemingly magicked your company out of thin air — they have no referral sources, no UTM codes, nothing that suggests how they found you.   

Besides making your data less accurate, this makes it harder to evaluate the real reason people stop engaging with you. And if you can’t identify the source of a problem, you definitely can’t solve it. 

The solution: Use a data management solution that tracks customers by persistent ID, not email or email. On Omeda, each profile is tracked with persistent ID tracking, so each profile stays active even when the underlying contact information has changed. This way, you can separate churned users from those who have switched emails — and more easily identify issuing causing churn.   

3. Collecting too much data  

If data gives you information about your customers, surely you want to get as much of it as possible, right?   

Not necessarily.  

Collecting unnecessary information about your customers wastes precious time and resources from your team. But more importantly, it also violates the GDPR, CCPA and several other state-level privacy laws. That opens you up to legal action (and expenses) that aren’t worth it from a cost-benefit perspective.  

Avoid this by periodically auditing your database to ensure that you’re only holding relevant information (rule of thumb: consider deleting data points that won’t help you reach tangible business outcomes). 

4. Not activating your data in the right way  

If you’re not using your data to improve your customer experiences, you’re missing opportunities to increase your customer lifetime value — and you’re not getting maximum ROI of your data management strategy.  

Below are some high-impact ways to use your audience data to improve customer experiences: 

• Identify upsell and cross-promotion opportunities: Use someone’s past purchase history to predict what other publications/products the person might be interested in buying next, then send them a promotional email featuring those publications/products.
   
• Recommend related content to website visitors: Content recommendation widgets — like we have on Omeda — serve each website visitor with related links and resources based on their website browsing history, thus increasing each person’s time on site and advertising revenue. On Omeda, you can track website activity for both anonymous and known visitors. That data feeds into our Content Recommendations algorithm, which you can use to provide this kind of personalization for each of your on-site visitors.
   
• Send renewal reminder and payment failure emails to at-risk subscribers: Your subscribers are your most reliable and important source of income. So you can’t afford to lose them to an outdated credit card or failed payment. On Omeda, you can avoid this by querying your audience data by credit card expiration date, then adding upcoming expirations to an automated email campaign reminding them to update their card information.
   
• Reward loyal readers and subscribers: To increase customer lifetime value, consider sending discounts, exclusive content or bundles to users that meet a specific subscription duration or order volume.

• Create more actionable marketing segments: Segmentation ensures that you’re sending the right message to the right person at the right time. But this strategy only goes so far if you’re using overly broad segments, like “all senior-level executives.”The more data you collect about your audience, the more narrow your segments can be. So instead of “all senior execs,” you might have “all senior execs in the tech industry who have visited the website in the last 30 days but not subscribed.” On Omeda, you can achieve this level of specificity by mixing and matching more than 100+ different behavioral, demographic and purchase-related filters. 

   

• Incorporate dynamic content in your emails: Even within the same marketing segment, no two people are the same. By using dynamic content in your emails, you can ensure that everyone gets content that is specifically tailored to their previous engagement, browsing and purchase history — and that they’ll continue to engage going forward. On Omeda, you can use your CDP data to create dynamic content, then incorporate it into your automated emails, all in one platform!   

5. Not aligning your data management strategy with business objectives 

Transforming your data management strategy isn’t just about getting your spreadsheets to say what you want them to. It also requires buy-in from all of the stakeholders collecting, transforming and using that data, from your developers to your marketing, sales and success teams.  

But busy professionals are often reluctant to add the “busywork” of learning a new software or adding a new data management process to their schedule. To get their support, you need to show them how your data management initiatives will help them meet their own goals.  

Be as specific as possible about both the inputs and the results. Imagine that you’re pitching your new CDP to your marketing team: Just saying that better data will help your marketing team know their audience won’t convince them to overhaul their data (and take on a lot of extra work).  

Instead, speak to how your initiative will help them hit their own KPIs. For instance, tell your marketing team that establishing a single customer view will help your marketing team create clean customer profiles in less time, freeing up more time to accomplish the actual tasks they’re being evaluated on. Also say that they can pinpoint each individual user’s preferences regardless of what platform they’re using, so they can create personalized cross-channel experiences more easily, drive revenue and increase customer lifetime value. That solutions-focused approach will go a long way toward establishing buy-in.  

6. Treating data management as a short-term task  

20 years ago, you might’ve been able to set up a few Excel sheets to track your customer data, then checked in six months later to see how it was working. But if you’re managing a digital business these days, that hands-off approach won’t fly.  

Businesses are constantly taking in data from an increasing number of sources — and with the advent of AI, data privacy regulations are evolving quite literally by the day.

So when it comes to data management, you can’t afford to set it and forget it. Instead, you need a dedicated team of cross-functional stakeholders to continually monitor, audit, and adjust your data management strategy as needed. Also consider having a dedicated privacy consultant or in-house staff member on hand to ensure regulatory compliance and guide best practices on data governance.  

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