CRM Data Cleansing & Enrichment - Data Management Best Practices

Your CRM data is probably one of your organization's most valuable assets. Companies can go to great lengths to protect and secure their CRM data but just how much emphasis goes into the quality of the CRM data? Everyone is well aware of the value of their organization's CRM data and if there was a straightforward way to put a financial price tag on them perhaps it would put things into perspective better. However CRM data is a perishable asset left on its own it doesn't appreciate like an antique with time, its value will diminish unless you look after it well. Although data quality management may rank among the most neglected area of CRM management and definitely one of the major pain areas for administrators and managers, following a strict CRM data cleansing and data enrichment  regimen is what will help maintain and enhance the value of your data.    

Here are some practices to keep your CRM data quality at its best:

Identify A Drop In Data Quality Quickly: Bad data is often ignored until it really starts to affect daily work by which time it needs a lot of work to get it back in shape. It's important to identify whose responsibility it is to monitor the data quality and keep the maintenance process going on an ongoing basis. Whether it's a weekly scan of records to see if outwardly everything looks alright or a periodic email or contact sample check, keeping an eye on your data will help you identify changes in quality earlier rather than later. Sometimes your sales persons or marketing department who frequently use the data to call or email prospects or customers using the data will be the first ones to experience any change in the quality and keeping a regular and close feedback loop will help you know how up-to-date your data is or what issues they face while using it.  

Have An Organizational Policy On Data Standards: Bad data in. Bad data out. While CRM administrators and managers are demanding about ensuring any data they upload into their CRM is checked and entered exactly how it should be, most CRMs are accessed by several end users across the organization and there is very little control over what data is entered or edited and how it is entered or updated. This is where it can start going wrong. Educating the end users or the company's data standards and making them aware of healthy data updating practices can help standardize what goes into the CRM. For example, if one user enters contact names in the form of initials with currency values in dollars and another enters them as full names with currency values in increments of a thousand dollars there is bound to be data that is not standardized. Coming up with a well-defined data standards policy that is made available to all end users can help considerably.

Put In Stringent Quality Checks At Your Data Sources: CRM data usually comes from several sources from conference lists, whitepaper downloads, website form fills, purchased business contact lists, online ad clicks, business contacts databases, and more. Common practice is to upload them to the CRM straight away assuming they can be normalized or filtered later. It's a good practice to manage, normalize, format, qualify and filter out your leads outside your CRM and then have it uploaded so that what is not valuable or quality data does not get added. We've covered more on this in an earlier post titled 'Data Management - Manage Your Leads Outside Your CRM'. If you check and clean your data right from the source, it will save you a lot of trouble later. 

Check For & Tackle Incomplete Records: Despite most CRMs having validations to check for mandatory data fields it's not always easy to ensure a value for every field at the time when a record is generated. For example, if your contact source is a conference list of attendees with only contact names, job titles, and phone numbers, although it's been added to your CRM, it has very little value if it needs to be used in an email campaign or a direct mail reach out. Appending missing data is not always easy to automate and often does involve a lot of manual effort which will seem time-consuming. However, it is a necessary evil and a periodic data append effort for missing data is important.

Check For Duplication And Redundant Data: Duplication of records and having large amounts of junk data is a sign of a sick CRM database. While putting in software checks for validating records and ensuring an entry is unique is a preventive measure that's good to have in place, there are a number of software or technology-based deduplication services which can help weed out duplicates some of which are mentioned here in a previous post. With a growing number of leads coming through sources like form fills and online sources where leads can often fill up gibberish values, doing regular scans for such junk records will help you keep your data free of what should not be in there. It is important to note that having a lot of duplicates and other redundant data can result in your analytics and reports reflecting false results so it has to be kept in check.

Periodically Filter Out Expired data: Companies and organizations merge, get acquired or shut down, contacts change addresses, change jobs, move within an organization ...CRM data does expire. This is an area that is not easily automated and again does require a considerable investment of time and energy. The more regularly you can carry out a check for expired data, the healthier your CRM will be. A database that remains untouched or unchecked for an entire year can see as much as 30% expired data and the longer you have between checks, the worse it can get so making sure it is checked periodically is paramount. While being able to run through the entire data once every quarter is ideal, twice a year should be the minimum.

Enrich Your Data, Increase Its Value: If data cleansing is what helps you maintain your database quality then data enrichment is what will help you enhance your data quality and make it more valuable to the end users. Ask yourself what additional data points in each record could help your users do more with the data and give them a better insight into each account. Would it help to have the annual revenues listed in multiple currencies? Would it help to have a list of all countries each account operates in? Would it help to have a link to the press releases of each account to stay updated on recent events? These additional data points can be added with a data enrichment effort after identifying what additional data would help provide value. If you practice good data management practices and implement a constant cleansing and enrichment process for your CRM you will be able to actually realize its full potential. That's when your CRM data is really an asset!               

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FAQs

What are the consequences of having inaccurate CRM data?

Having inaccurate CRM data can lead to missed opportunities, wasted resources, and poor decision-making. It can also harm the overall customer experience by providing incorrect or outdated information, which can lead to frustration and dissatisfaction.

Can data cleansing and enrichment be automated?

Yes, there are several software tools available that can automate the data cleansing and enrichment process. However, it's important to ensure that the data is being accurately and effectively managed, even when using automation tools.

How often should data cleansing and enrichment be performed?

Data cleansing and enrichment should be performed on a regular basis, with the frequency depending on the volume and complexity of the data. Some businesses may perform data cleansing and enrichment on a daily basis, while others may do it quarterly or annually.

How can businesses ensure compliance with data privacy regulations when enriching customer data?

Businesses can ensure compliance with data privacy regulations by obtaining consent from customers before collecting and using their data, and by only collecting and using data that is necessary and relevant to the business.

How can businesses measure the effectiveness of their CRM data management efforts?

Businesses can measure the effectiveness of their CRM data management efforts by tracking key performance indicators (KPIs) such as data accuracy, completeness, and timeliness. They can also conduct regular audits and surveys to assess the quality of the data and identify areas for improvement.