By Michele Stillwell, Director of Marketing and Accounting at MEDiAHEAD
Research suggests that on an average, companies across the globe feel that 26% of their address data is inaccurate. This contributes to enormous loss. In fact, bad data costs the average business 15% to 25% of revenue and in the US economy over $3 trillion annually.
There are two things that really irritate me when looking through the mail. At home, it’s getting mail addressed to my previously married name. I mean come on, that was 16 years ago. When I get something that has that name on it, guess what? It immediately goes to the trash!
Then, when I go through the mail at work, what really irks me is getting mail for people who have not been with the MEDiAHEAD for more than 20 years. And it happens regularly. I’m consistently thinking, “Where do these lists live, and why is no one looking at them? Why has no one updated them for 20 years?”
Data cleansing is so important.
Improving your data quality increases overall productivity. After your data is cleansed, the outdated information is removed, and you have good, clean information to move forward. Today, nearly 67% of businesses rely on CRM data for growth of their bottom line. However, an amazing 94% of B2B businesses suspect inaccuracy in their databases.
So how do you manage this?
What is the value of marketing analytics these days? It’s so high apparently, that companies plan to increase budgets for marketing analytics over the next three years by 198% according to a recent CMO survey. Marketing analytics offers a treasure trove of customer information and performance insight to overall business success. Which is why you would think that managing marketing data with tools like a CRM database and other analytics systems would be a more agile and rigorous process than it actually is.
Since 70% of marketing leaders expect to make the majority of their decisions using data for everything from building, personalizing and executing the next campaign to targeting, reaching and forming deeper customer segments – there should be a way to overcome the data cleaning roadblock. There are data cleansing tools/software applications that will help to clean and correct lists and databases by identifying incorrect, inaccurate, irrelevant data and clean your data accordingly.
Here are some best practices when it comes to creating data cleansing processes:
- Standardize Your Processes
- Validate Accuracy
- Scrub for Duplicate Data
- Use it to Analyze – for business intelligence and analytics
- Communicate with the Team – Keep it clean
- Get Your ROI from your Data
When managing your data, keeping on top of it consistently and accurately are two underlying jobs you have to deal with every day. The steps above should help make it easier to create your daily protocol. Once you’ve completed your data cleansing project, you can move forward using that data for deep, operational insight now that your data is accurate and reliable.
Large corporations invest so much into advanced information systems that collect, store and analyze their data. Collecting data isn’t the goal… it’s the means to the end. The real opportunity is the customer intimacy. How well can you get to know your customer? How will you leverage this knowledge to improve their experience and satisfaction?
Quality over Quantity
There must be some method to the madness, right? To be of service to an organization, data must be more than just prolific; it needs to be useful. It should provide strategic insight and support data-driven decisions. And the quality of the data is crucial. You should be able to measure everything from the number of views to the number of clicks. This helps your sales team as well as providing customer success stories.
Clean data is of utmost importance. Without it, leadership can’t make strategic decisions. Dirty data inevitably leads to dissatisfied customers, and that’s a dangerous slope to start down.
Keep your data clean!