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A 5-Point Data Hygiene Plan for Your B2B Contact Leads Database

posted by Margaret Spencer on August 26, 2017

A 5-Point Data Hygiene Plan for Your B2B Contact Leads DatabaseYou may not know it, but you’re wasting at least 12% of revenues due to bad marketing data. That’s according to a review from Econsultancy that says bad data tend to directly impact profitability in as much as 88% of companies.

That’s why proper data hygiene is as important as ever, since practically every marketer today makes decisions based on insights extracted from the data sitting in their CRM or prospect lists. In today’s post, we’ll go over the five key points you need to carefully consider in order to come up with an actionable data hygiene plan for your B2B contact leads database.

 

  1. Develop a thorough data maintenance routine.

Inaccurate data occupies just one segment    in the Venn diagram of bad data. There are other data quality issues—such as missing data, inconsistent data, duplicate data, and unsynchronized data—that you also have to watch out for.

So, you need data maintenance initiatives that both prevent and fix data quality issues at different stages of your data life cycle—from data collection all the way to data removal.

 

  1. Remove data barriers and silos.

In a typical B2B organization, it’s not uncommon to find multiple instances of the same piece of prospect data housed in separate locations (e.g., marketing automation platform for marketing and CRM database for sales). This increases the possibility of having unsynchronized, inconsistent, and misaligned information used by different teams.

A good data hygiene plan also needs to take into account potential barriers to the free flow of data across users, teams, and departments. There should only be one version of a piece of prospect information at any given time.

 

  1. Supplement manual with automated processes.

For best results, data hygiene should be carried out with the right mix of manual and automated data cleansing methods. While tools like AI and machine learning have now streamlined data hygiene tasks, there’s still a clear need to keep humans in the loop.

Take, for example, data deduplication. Most commercial data scrubbing packages come shipped with powerful deduplication capabilities, which are especially helpful for scrubbing a large B2B contact leads database. But the deduplication process still requires human input to correctly identify which redundant records to keep and which ones to discard.

 

  1. Rethink your entire data quality approach.

Another key point that your data hygiene action plan needs to address is to make data quality everyone’s concern. While you need to define clear roles and assign specific tasks for maintaining data quality, it’s equally important to make sure everybody’s onboard.

Also, keep in mind that you can’t manage what you can’t measure, so you need to choose a relevant set of KPIs and benchmarks to gauge how well your data hygiene initiatives are performing.

 

  1. Know when and how to look for expert help.

In some cases, outsourcing part of your data hygiene program to a data quality solutions provider is a more practical option than doing it yourself. For instance, enriching your prospect data for improved segmentation is best done with a third-party data provider, since doing this in-house can take up time and resources which could be better spent elsewhere.

So, take stock of your current data hygiene capabilities, and let a reputable data quality solutions provider handle those activities that you’d have a hard time carrying out in-house.

Now that you’ve nailed down what a data hygiene action plan should contain, it’s time for you to flesh out concrete ideas for maintaining data quality. Use these five points as guidelines, and be sure to track, test, and tweak your strategy.

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