Four Ways Dirty Data Is Hurting Your Marketing Results

Like it or not, you’re spending marketing budget on programs that bring poor or no results.

Research shows that on average, 12% of an organization’s annual income is misspent due to bad contact data.

And it’s not just the money. Dirty data, such as duplicates, results in inaccurate lead scores. Score sharing between duplicate leads means neither record gets a high enough score to move further down the sales pipeline.

Poor marketing results along with time wasted following up on the wrong leads dramatically reduce sales and marketing productivity, increase marketing software costs, and can damage company reputation.

 

startup-photos.jpg

Here are four ways bad data is hurting your marketing results and what you can do to fix them:

1. Duplication

Customer data is gathered through a number of sources, including web forms, tradeshow lists, webinars, or third party sources. Duplicate records easily end up on most marketing lists.

Marketing automation and CRM system charges are often based  on the amount of data stored. Retaining many duplicates in your system inflates such costs. Duplicates also skew performance reports, make it difficult to base decisions on accurate results.

The fix:

  • Enhance your CRM with a duplicate prevention tool

  • Make sure the most likely duplicate entry places, such as data imports and manual data entry, are duly covered

  • Create a duplicate-free workflow for all teams, not just Marketing

2. Lead scoring

Prospects often use more than one email address or interact with your organization in different ways (email opens, downloads, trial request, etc), causing the marketing automation tool to create duplicates.

Duplicates affect lead scoring by:

-  score sharing between duplicate leads; neither score is high enough to qualify the lead.

- treating each email address as a unique record; a score referring to the same lead can be split between different email addresses.

- shared email addresses; if an email address is shared by members of the same organization, all is saved to one unique lead.

The fix:

  • Assess the quality of your CRM data on a recurring basis and be persistent in tracking down new duplicates

  • Be thorough in cleaning your data; make sure no duplicates get left behind

3. Inaccuracy

Data quality changes over time. In fact, data is estimated to degrade at a rate of 30% per year.

Organizational changes, outdated contact information, errors during entry, and even external data sources can affect the quality of your CRM data.

Such data unnecessarily increases storage costs and can have devastating effects on marketing. Wrong targeting or multiple communications to the same contact can have a severe impact on company reputation.

The fix:

  • Verify and enrich existing customer data

  • Verify data from third party data sources before adding it to the CRM

4. Limited visibility

Most organizations rely on more than one system for their customer data. CRM is just one of the sources marketers use in building customer profiles that they use in their targeting.

To access customer information across cloud, on-premise, and even third party systems, marketers need to be able to find data quickly and easily, regardless of differences or errors in form (such as misspellings, acronyms, or nicknames).

The fix:

  • Get a 360 degree view of the customer profile for better targeted and more personalized campaigns

  • Integrate all available customer data into a unique workflow

  • Make data easy to locate no matter where it resides

Are your campaign response rates dropping? Evaluate the current state of your data with our free assessment, the Data Quality Report.

Need guidance with specific actions you can take to improve your data quality? We’re here to help!