How Sloppy Data Management Could Cost You Leads
In a world where we’re generating data at break-neck speed, bad data is becoming an increasingly common issue.
We’ve created 90% of the world’s data in the last couple of years alone. It’s little wonder that some of that content isn’t exactly up to snuff.
Unfortunately, bad data costs the US around $3.1 trillion annually.
Why? Because when we have errors and inconsistencies in our data, the assumptions that we make using that information are often wrong.
Used correctly, data can lead you right to your customer’s heart, giving you the context and insight you need to create loyalty and commitment.
Unfortunately, without a proper strategy to manage and refine the data that you get, that map’s going to be filled with contradictory and confusing directions.
It’s time to understand how bad data management costs you your leads – and what you can do about it.
Data management is the cure for bad data
The machines that we use to collect information today aren’t foolproof.
More often than not, data collection is an automated process. That means that your systems won’t differentiate between the information that’s crucial to your company, and the data you don’t need to know. At the same time, there’s a good chance that you could be collecting information on the same customer twice, which skews your numbers and ratios.
As companies strive to be more on-demand, data-powered, and customized, we often assume that every scrap of customer data is valuable.
However, when you collect information at random, it’s like dipping a big bucket into the ocean. Sure, you’re going to get some fish, but you’ll also end up with seaweed, plastic bags, and old boots too.
Combine all the inaccurate and unnecessary data in your collection process with the fact that most companies only analyze 12% of their customer information , and it becomes even less likely that you’ll end up with relevant insights.
It’s easy to forget that not just any data is going to drive your company’s success. You’re going to need to look at the right insights if you want to make the right informed decisions.
The importance of lead management for data-driven business
So, how do we cope with the issue of all this messy data?
Over the years, lead management software has become increasingly popular among industries that respect and value their critical data. Healthcare brands, financial sectors, and even retail companies use lead management solutions every day.
Lead management software is useful for customer engagement, automation, and ROI. It ensures that you can separate the good leads from the irrelevant data in your information bucket.
What’s more, with excellent lead management, businesses can ensure that they’re targeting the right audience, reducing their churn rate and creating a more efficient business.
At a time when around 79% of all marketing leads never convert, proper lead management is how you ensure that data is moving your conversations with customers in the right direction.
Investing a little time and effort into data management at the start of your campaigns ensures that you can reap far greater benefits in the future. Any campaign you start or improve with a basis of robust, reliable data is sure to help your company move in the right direction.
So, how do you use lead management tools to organize sloppy data?
1 Develop a plan for data quality
First, you’ll need to set some expectations for your data.
In other words, what kind of information are you trying to collect?
How are you going to manage the value of your data using KPIs like accuracy, relevancy, and actionability? Your data management tools will give you a better overview of your data hygiene so that you can put those KPIs into practice.
What’s more, with a data management tool, you’ll also be able to pinpoint the areas where data errors are most likely to occur. For instance, maybe you’re not updating your blacklist often enough, or you’re collecting duplicate lead information from a specific form online.
2 Standardize your data at the point of entry
Before you can begin cleaning up the data you’ve collected, it makes sense to ensure that you’re gathering that information appropriately. Ultimately, this means coming up with a standard operating procedure (SOP) with your team about the kind of information you’re going to gather and where you’re going to collect it from.
If you’re just throwing your net out over any old information, then you’re bound to end up with some inconsistencies and irrelevant data. With a standardized process in place, you can take a more focused approach to getting the information you need.
3 Identify duplicates
Duplicates are a common problem for data hygiene.
The more you collect the same information on a customer, the more you waste your effort and send your insights spiraling in the wrong direction. You might assume that the majority of your customers prefer contact through SMS, for instance.
However, if you’re dealing with duplicate data, there’s no guarantee that the numbers you’re working with are correct.
Dupes give you an inaccurate single point of truth, which means that every assumption you make using your data is slightly less accurate than it should be.
Fortunately, you can use your lead management tool to search your database at record pace and scrub those pesky duplicates and avoid adding leads that don’t need to be added.
4 Maintain a good blacklist
A blacklist is a selection of data that you can add to your management system to tell your tools what not to search for. Keeping an updated blacklist helps to reduce the time you’ll need to spend going through your data regularly and getting rid of any inaccurate information.
It avoids collecting the data that you don’t need from day one, so maintenance is less of a headache.
As AI’s impact on the data management world grows , blacklists will also help intelligent assistants to sort and understand your data for you. Ideally, you’ll want a data scientist in place that can check through your information for you regularly and update your blacklist when needed.
5 Validate the accuracy of your data
Finally, your database is only helpful to your business if it’s accurate.
You’ll need to ensure that you’re tracking your wins and losses correctly, analyzing customer preferences properly, and collecting appropriate insights. If you don’t, then you’re just making assumptions based on what you think you know – you can do that just as well without data.
The best lead management tools come with solutions in place that help to validate the accuracy of your data for you. These systems triple-verify the information collected, reducing your risk of misleading results.
Sloppy data creates messy customer management
Whether you love it or hate it, data is becoming the foundation of everything that businesses do.
Now that customers are more demanding, expecting more personalization and relevance from the companies that they work with, data is the only way to deliver a truly excellent consumer experience.
Used correctly, data will help you make the correct decisions for your business, designing experiences that are meaningful and relevant for your clients.
However, if you don’t have a data management strategy in place, then it’s impossible to know for sure whether you’re making decisions based on authentic insights, or you’re being led in the wrong direction.
- Minimizes your risk of errors and gives you the power to make real, informed decisions.
- Improves your business efficiency by ensuring that you can make essential choices quickly.
- Protects you from issues caused by data loss and duplication, which could harm your data security.
At first, a few inaccurate records or poorly standardized content might not seem like a big deal. However, as your business continues to scale, and information becomes increasingly fragmented, lack of proper data management leaves all your insights fraught with issues.
It’s time to clean up that sloppy data once and for all.