Many marketers know that good data management is critical to the success of their lead generation programs.
Data is at the heart of every email campaign, webinar invitation, whitepaper download, form completion, and sales follow-up. It can turn marketing strategy and tactics into marketing triumph—helping marketers target the right audiences with the right messages at the right time.
However, although most marketers are aware of the benefits of good data management, many fail to ensure that their contact databases are as accurate, complete, and up to date as possible. In fact, more than half of US companies are working with unreliable marketing data (2013 NetProspex Marketing Data Benchmark Report).
Because tens of millions of Americans changing jobs each year and the vast majority of buyers submit incomplete information on registration forms, data can be difficult to manage. And although there are ways that marketers can ensure that they are using more reliable and comprehensive contact databases, some of the best data management practices also happen to be the ones most commonly overlooked.
To make sure you avoid overlooking those best-practices, here are five tips to keep you on track to reaching the people you want with the content that drives engagement and creates qualified leads for your sales team.
1. Establish standards
Work with your marketing and sales teams to ensure that all constituents have the same expectations for data quality. Clarity for what is expected and agreement on goals as an organization are critical to your go-forward strategy.
2. Monitor your data health
Assess the state of your marketing database regularly to understand email deliverability, phone connectability, and record completeness. Doing so ensures that you are not wasting cycles chasing outdated contacts.
More important, it will uncover whether your outreach efforts are aligned with your go-to-market strategy. For instance, your data profile may not fully support newer offerings that appeal to different types of organizations or buyers. It's critical to understand those gaps and work to address them before they create bigger issues with pipeline generation—or (gulp!) revenue.
3. Fix what's broken—or partially broken
Consider data the fuel of your marketing engine. If you make sure the fuel is clean, you will generate greater productivity from the engine. When cleaning your database, look at ways to enrich the good records you already have to spur better segmentation and targeting at the contact and company level.
According to research from the Aberdeen Group, companies that actively manage their marketing data for hygiene and improved segmentation require just 64 marketing responses to generate a customer. Those that do not... require 329 (industry average) or 622 (laggards) touches.
Run those numbers against your average CPL. I guarantee it's a dramatic difference in your cost of customer acquisition metrics.
4. Be proactive
Look at new methods to improve net-new data that flows through your marketing channels. Use dropdown sections on Web forms and progressive profiling with repeat customers. Enrich inbound records with contact and company details to complete profiles not originally captured (for example, at a tradeshow or an online form). Adopting this proactive approach will help guarantee that you are working with the largest database of relevant contacts possible.
5. Build a routine
Establish a process to assess, cleanse, and enrich your marketing data regularly throughout the year. Our research shows that marketing data decays at approximately 3% per month—and your inbound channels introduce hundreds (or thousands) of new records over the same time frame. It's not an everyday activity, but it is a continuous effort that you must maintain.
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Take some time to assess where you are and how some of these tips can make you better. Small improvements in your contact database will drive dramatic improvements in your lead generation machine—and create better alignment with your sales organization.
Don't let dirty data be the sand in your engine.
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