For B2B marketers, customer data is everything. But bad data is everywhere. And it can be a nightmare, creating a bottleneck in your marketing and sales efforts, and destroying ROI.
Nearly every marketer is affected. In our recent Demand Generation Report, we found that over 90% of B2B teams report that they are challenged by inaccurate or incomplete data on accounts and buyers.
5 Steps for Eliminating Bad Data
Your sales team doesn’t have the time or resources to manually scrub invalid leads. And even if it did, manual efforts can’t catch everything. Bad prospect data always slips through. This fosters mistrust––sales team members begin to wonder if marketing can even generate qualified leads.
Poor data quality can also negatively impact your relationship with the buyers you’re trying to reach. When bad prospect data enters your database, it skews performance analytics, resulting in erroneous decisions about messaging, content distribution, target parameters, and much more.
That’s why it’s imperative that you eliminate bad data before it enters your marketing database and hurts your brand image. Here’s how to do so:1. Solve lingering mysteries––determine where data-quality problems arise and implement a basic filtering process. When it comes to customer data collection, quantity and quality aren’t interchangeable. Whatever the nature of your business, poor leads in your database present long-term scaling inefficiencies for the entire organisation. To clean out those skeletons in your closet:
- Centralise all data sources into a common repository before uploading the data
- Audit every lead for missing, incomplete and duplicate fields
- Check for false information, such as fake names and email addresses
- Check for untargeted values, such as geographies or company sizes you don’t want
- When applicable, construct lead-return files for each lead provider
- Append enhanced lead data where necessary
- Standardise lead file formats
- Upload lead files to relevant lead nurture track(s) in marketing automation systems, where applicable
Keep in mind that your filtration strategy must be adaptable to your sales department’s in-the-field knowledge of what constitutes a promising lead.
2. Shout for help––crowdsource your lead-elimination efforts. After you’ve determined the inefficiencies affecting your database, reach out to your peers. It’s likely they’ve experienced similar issues in their data collection efforts. Quora is a great knowledge-sharing platform where marketers exchange a wealth of marketing expertise and hacks. LinkedIn is also a great resource for troubleshooting industry-specific challenges.
3. Escape the monster––create a strategy to grow and support qualified leads. Prioritise your lead-quality challenges and lead elimination strategies to focus on quick results. Approach top-of-funnel issues first: They’ll have a trickle-down effect and quickly impact the sales pipeline.
4. Shake the cobwebs from your database––perform lead quality checks, even if it requires a manual process. Manual efforts can be fatal to efficiency, affecting productivity, morale and revenue. Still, there's one thing worse: no lead quality governance at all. Consider using this lead-data integrity checklist:
- Filter as many bad leads as possible
- Track the lead sources that provide the highest quality leads
- Document the time and resources spent manually processing leads to make more informed calculations on campaign ROI
Wake Up From That Nightmare
Bad lead quality, poor database integrity, and manual clean-up efforts don’t have to keep you up at night. By improving your data collection and filtration processes, you can eliminate poor leads before they enter your database. By embracing solutions, such as the DAP, you can streamline your processes, and ensure your database will be filled with fresh, accurate, marketable, and compliant data.