3 Strategies for Getting and Keeping a Clean Pool of Data 

Would You Dive Into Your Data?

If you think about the pool of data you have at your disposal as if it were an actual swimming pool, what comes to mind? Do you smile to yourself as you imagine its pristine waters beckoning you to enjoy a refreshing dip? Or do you shudder thinking about what lies beneath its murky depths, knowing good and well it hasn’t been properly cleaned or had maintenance check-ups in ages.

Come On In, the Data’s Fine

Much like a real pool, the various pools of data that exist throughout your organization and martech ecosphere need to be monitored, cleaned and maintained on a regular basis. If not, you run the risk of drowning your best marketing efforts in a cesspool of dirty data. Because data is the most important variable in determining the performance of your campaigns, the genius of your insights and decisions, and your organization’s ongoing success, you must be unabashedly obsessive-compulsive when it comes to keeping it in a perpetually clean state. In today’s blog, we’ll cover simple actions you can take now to ensure your data is so clean, you can swim in it without needing a round of antibiotics immediately afterward.

1. Demonstrate the Value of Clean Data to the High C’s

Before you can revolutionize the data situation at your workplace, you’ll need to get buy-in from the people who determine your budget. Making the case for clean data to those in power often requires insights gathered from—wait for it— the latest data. Of course, nothing motivates the C-suite quite like revenue, so let’s begin with data’s impact in that realm. For example, did you know that:

• Corporate data grows at an annual rate of 40%, and 20% of that data is filthy
• Dirty data costs the average business 15% to 25% of revenue
• Dirty data reduces lead conversions at a cost of $83 per 100 records
• 2% of the information in your leads database goes bad each month

In short, data that is home to duplicates, inaccuracies, errors and inconsistencies is the number one cause of campaigns missing their target audiences, marketing budgets being wasted, and great opportunities being missed. Don’t let this happen to you.

Tout the Power of Positive Data

When your data is clean, complete, current and enriched with information and insights from leading third-party providers you are able to accomplish a number of mission-critical goals with remarkable ease. In fact, research shows conversion rates are 25 percent higher between the inquiry and marketing qualified lead (MQL) stages for companies that have clean data. When your data is clean, you can scale personalized campaigns and create engaging customer experiences that boost brand loyalty and customer lifetime values. You can ensure the right people get the right message at just the right time, and on their preferred channel. In truth, you can make it rain.

2. Prepare to Come Clean

Now that you’ve got the stats you need to persuade those in power to support your quest for clean data, let’s talk strategy.

Perform a Data Quality Audit

The benefits of conducting a marketing data quality audit are manifold, from identifying gaps in your data processes (tools, integrations, shareability, etc.), to ensuring the accuracy and reliability of your data, which impacts the whole organization. A basic data quality audit includes these steps:

• Make a checklist of all data storehouses, entry points and exits and note which data sources are well-integrated and which ones need to be integrated
• Create a to-do list for the data quality standards that need to be implemented (validation, standardization, normalization, etc.)
• Identify all opportunities to automate data cleansing processes and prioritize their implementation

3. Implement Data Validation Enterprise-Wide

Establishing daily data cleansing processes in every system that houses data is critical to your ability to respond quickly to market changes, new opportunities and promising customer insights. Naturally keeping data this tidy requires the magic of automated data validation. Automation enables you to validate data at the point where it enters each system, and this enables you to ensure that only clean data gains entry into your “clean machines.” Other data validation processes you will want to implement include:

• Detect and delete duplicate contacts
• Identify and correct data errors, i.e., spelling, syntax, blank fields, etc.
• Set and enforce a standard for how data appears across all systems
• Fill in missing datasets by using reputable third-party vendors

Let’s Prepare Your Data for World Domination

At Sureshot, we have a team of experts and a portfolio of data solutions that are fully committed to helping you maximize the potential of your data. If you are ready to harness the power better data can bring to your marketing strategy and initiatives, contact us, or start by taking our FREE Martech Assessment.