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DQ Blog Data Quality 4 Simple Steps to Healthier Data in Your CRM System

4 Simple Steps to Healthier Data in Your CRM System

Martin Doyle January 28th, 2014 Data Quality, Master Data Management
Healthier data

How To Keep Your CRM Data Clean

Businesses rely heavily on their customer relationship management (CRM) software. It’s the hub around which many essential processes are clustered. Yet the CRM system can easily be undermined if the data it contains isn’t up to scratch.

Through January, we’ve looked at some of the resolutions businesses are making to improve their data quality by matching and merging records using deduplication software. But what are the essential steps you’ll need to take to cleanse your CRM system?

1 Decide Your Data Quality Priorities

Tackling poor quality data can be a daunting task. There’s no harm in identifying quick wins and starting with those. We suggest defining a quick win as an area where a data quality improvement would yield the biggest return. In a CRM system, this might be consolidating information about leads so that your sales team has better information to work from. If you send out direct mail or catalogues, you may feel a greater benefit when you cut down on your duplicate records to reduce waste.

2 Think Tactically About Data Quality

Once you’ve completed the quick wins, it’s time to rank the rest of your data quality challenges in priority order. Again, look at the potential outcome and the value that you would obtain from a data quality improvement.

Value may be measured in several ways, and all are equally valid if there is a significant impact. You might choose to rank by customer benefit, productivity boost or some other metric relevant to your business.

3 Identify Weak Processes

Data quality tends to decrease the longer data is held. We are all constantly growing, changing and moving around, so our data is never static. But there’s another potential cause of poor data quality: a poor process.

Single out processes that are causing your data quality problems. If you can nip the problem in the bud, you will eliminate the ‘correction and corruption’ cycle and cut down on the amount of ongoing maintenance for your CRM.

4 Research CRM Data Quality Software

You’ll need data quality software to correct data in your CRM system. In fact, the only businesses that don’t need data quality software are those working with small spreadsheets that can be handled manually. Every other user of data needs a tool to help them do the job properly.

For best results, choose a tool aimed specifically at improving CRM data quality. You should be looking for direct integration with your CRM, a shallow learning curve and the ability to automate part of the process. When your employees need to intervene in the data cleansing process, the software should support access from more than one person at the same time.

Planning a Long Term Strategy

When working to improve CRM data quality, plan your attack logically. First, identify your biggest pain points, correct them. Then, put measures in place to prevent as much data corruption as you can realistically prevent. Data quality should be an ongoing concern in business, but with the right data quality software, it need not be a drain on your resources.


Written by Martin Doyle

Martin is CEO and founder of DQ Global, a Data Quality Software company based in the UK. With an engineering background, Martin previously ran a CRM Software business. He has gained a wealth of knowledge and experience over the years and has established himself as a Data Quality Improvement Evangelist and an industry expert.