Remington BeggDid you know that 29% of companies believe that their current customer or prospect data is inaccurate in some way?
Are you part of the 89% of companies who face challenges in how they manage data?
Is your company like 95% of organizations who see impacts in their organization from poor data quality.*
Yikes!
In today’s rapidly changing marketing landscape this is a huge problem for marketers and CMOs.
Bad data has a severe effect on everything from customer service, compliance, marketing, ROI, and revenue for all companies.
In order for all of the data you’ve gathered to be useful to you and your company, you need to ensure that having a good data cleaning strategy is a priority.
The Importance of Good, Clean Data
Data is at the core of your company and the quality of that data underpins the success of your business initiatives. Strong data quality efforts lead to accurate and standardized data which allows you to gain greater insights and help you make decisions with confidence.
Quality data is the backbone to your data management efforts that will help you deliver a superior customer experience, gain a competitive advantage, and move your business forward.
Data quality, as you are probably well aware of, has a direct impact on the conversion rate from lead to customer.
With dirty data, companies are unable to access the insights needed to inform smart business decisions, which results in fewer leads and more money wasted. Not to mention it can also lead to a poor customer experience. Ever gotten an email with wrong information in it?
“Don’t spend good money on bad marketing.” - Josh Ames
What is Data Cleansing?
Data cleansing is the process of going through all of the data within a database and either removing or updating information that is incomplete, incorrect, improperly formatted, duplicated, or irrelevant. Data cleansing usually involves cleaning up data compiled in one area. For example, data in your HubSpot portal, so you're left with only the most relevant, high-quality data available to run your campaigns.
Why is data management and cleaning important?
- Establishes trust in your data now and moving forward
- Allows you to make accurate business decisions
- Delivers a strong and positive customer experience
- Boosts your bottom line by eliminating manual data tasks
- Using tools to cleanup data will make everyone more efficient since they’ll be able to quickly get what they need from the data.
- Fewer errors means happier customers and fewer frustrated employees.
The data cleansing process is usually done all at once and can take quite a while if information has been piling up for years.
Unfortunately, most marketers rely on manual clean up efforts either before they hit send on an email or retroactively before reporting on campaign effectiveness.
Sadly, "not at all" is often status quo.
A successful data management/cleaning plan cannot focus only on preventing incorrect data from entering the system. It must also periodically revisit database information to fix outdated information, as well as repair mistakes introduced in the input and storage of data.
By ensuring your data collections are routinely cleansed of useless information, you can simplify data analysis, build a more effective marketing campaign and know that you are making informed decisions based on accurate data.
That’s why it’s so important to regularly perform data cleansing.
How often you should cleanse depends on a variety of factors, such as how much information you have, whether you are importing data regularly and whether you are using data enrichment services (something we highly recommend adding to your tech stack).
It’s also important not to cleanse too often – or you may waste money by performing unnecessary actions.
The aspect of maintaining data quality will continue to grow in importance, as digital marketing continues to rely on customer and sales lead data as the engine that drives effective marketing efforts. The quality and integrity of your data can be the determining factors in how well your company is able to maintain enough competitiveness over time.
Do you feel better equipped to think about the quality and health of your data? How about getting a better ROI on your database?
Next Steps for Data Cleansing
What now? What action can you take to get healthier data?
The most important step to take next is to identify the sources of dirty data in your database. That way you can prevent inaccurate or duplicate data from piling up. We are big fans of using a tool like Insycle to help make this process easier so that it’s not a tedious manual process.
If you need help cleaning up your database and implementing a strong data management process, learn about our data cleaning services and let’s get you on the road to making better, more informed decisions that lead to greater ROI from your marketing efforts.
Cleaning photo by JESHOOTS.COM on Unsplash
* Source: Top 10 data management stats for 2018