30% of Your Company Data is Outdated. Here's How to Clean Up Your CRM


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Monday, April 18, 2022

Bad data can have a negative impact on your marketing campaigns and overall brand perception, so what measures should you take to clean your CRM data?

Article 4 Minutes
30% of Your Company Data is Outdated. Here's How to Clean Up Your CRM

Just like all areas of your working life, your customer relationship management (CRM) software can become cluttered and inefficient. It can result in a lack of organization and can lead to everything from a drop in productivity to an inability to operate with agility, all of which can affect your bottom line.

Studies suggest that 30% of data becomes outdated each year, so it’s paramount you keep on top of changes. After all, if a contact has a new email address or changes their job title, you’ll want to be confident your database is reflecting these changes.

Functioning with a clean CRM is vital to ensure the marketing department is performing at its best and helping to reach business goals. A standard process should be put in place for regular data cleansing so that simple steps can be taken to keep on top of the issue.

How does data become bad?

In today’s marketing landscape, it’s inevitable that there will be an accumulation of errors in your data over time, due to a number of inherent factors. These include:

  • Inaccurate information inserted by leads on your web forms
  • Contact data uploaded based on the best information sales reps can find at the time
  • Data gets appended as leads are nurtured
  • Multiple calls with leads mean sales reps make duplicate entries

Not inputting data in the right format or in the correct place within the CRM after each interaction can lead to bigger problems. This can make optimizing marketing campaigns impossible and limit the success of your operations.

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What are the effects of bad CRM data?

Customer interactions based on bad data will always be intrinsically flawed, whether they're carried out by the marketing department or sales reps. The issues can range from incorrect email addresses meaning you can’t reach your leads, right through to communications being marked as spam because you’ve addressed the recipient by the wrong pronoun after they made an error on a form.

Research from IBM suggests bad data costs the US economy $3.1 trillion annually, while Experian found it impacts the bottom line of 88% of American companies. The latter study put the average loss of total revenue down to bad data at 12%, making a significant impact on company profits.

Incorrect data can lead to:

  • Less successful marketing campaigns
  • Negative perceptions of your brand
  • Ineffective optimization or personalization of marketing materials
  • Inefficient use of employees’ time

How do you clean up your CRM database?

CRM data cleansing is an ongoing process that should be carried out regularly to ensure the task doesn’t become too unwieldy and time consuming. Breaking it down into simple steps and keeping on top of CRM cleaning will mean your database is valuable and relevant to your business goals.

1. Consolidate contact records

Organize your contact records so all interactions with the same company can be found together within your CRM. Then use filters to categorize each individual based on their job title and their status as a lead. Consider also removing any contacts that don’t respond to your emails and remember that while this may feel counterintuitive, it’s actually enriching your valuable data.

2. Implement a standard process

Utilizing your CRM on a daily basis should be combined with cycling through your contacts and seeing if emails are successfully delivered. Putting a standard process in place to verify the data, generate lists and delete contacts when they’re no longer viable will ensure you’re constantly cleansing your CRM of bad data.

3. Create clear segmentation

Segmenting your data is vital in making it as usable as possible and you can implement workflows and standard fields within your files to avoid too many variations of the same answer.  For example, drop-down menus are a great way to group individuals with similar job titles together under one searchable term.

4. Audit your data

Once you’ve brought a certain amount of order to your data, you can start to look at it to see what you have and any noticeable trends that could inform your marketing decisions. This is a good point to create new personas, as a data audit will offer greater insights into who you should be targeting with your campaigns.

5. Remove duplicates

Duplicate contacts is a common form of bad data and a deduplication tool can help you to identify similar contacts with slight anomalies. To merge the two records together, you’ll need to test which information is correct, by sending an email and seeing if it bounces, for example, and update the contact to reflect the most relevant entries.

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