As business-to-business marketers craft their fiscal 2020 budgets, it’s important that complex issues such as analytics, automation or AI do not distract from a core investment for achieving ROI: clean data. Certainly, AccuList stresses to all its list hygiene and management clients, whether for house lists or rental prospecting lists, the importance of data quality for targeting and response, and a recent blog post by b2b data management firm Synthio confirms the basic steps for data hygiene.
Start With a Clear Data Plan
When 94% of B2B companies suspect inaccuracy in their databases, any marketers who do not prioritize data hygiene have their heads in the marketing sands. That starts with a data plan. A good data plan will decide on the data-quality key performance indicators (KPIs) needed to achieve business goals. The plan will survey existing contact and account data and determine how to measure health in terms of data accuracy and completeness and how to maintain data hygiene tracking on an ongoing basis. It will look to see if there are important parameters for KPI success that the existing data does not address.
Standardize, Validate and De-Dupe Contact Data
What are the basics of data health and hygiene? Before cleaning data even begins, marketers need to check that important contact data at the point of entry or download is standardized. This will make it easier to catch errors and duplicates and to merge data from multiple sources. There should be a standard operating procedure (SOP) that defines fields, formats, and entry or upload processes to ensure that only quality, standardized data is used. The next step is to validate the accuracy of the data. Although a manual process might work for a small database, and there are tools and imported lists for cleaning data, advanced data hygiene is probably best handled by experts like AccuList, which can match contact addresses against USPS verification standards and change of address databases as well as update e-mail address changes. With standardized, validated information, data sets can be seamlessly merged and purged of duplicates. Why worry about duplicates? Duplicate records hobble CRM efforts, waste dollars in marketing campaigns, undermine the Single Customer View essential for targeting and response tracking, damage customer relations and brand reputation, and result in inaccurate reporting that can mislead marketing strategy.
Append Missing Data Parameters
Most b2b house databases have data for each record, such as contact first and last name, e-mail, company name and business address. But complete data for all records may be spotty, and some desired data may be missing altogether, such as title, phone number, company annual revenue, tech stack, purchase history, etc. Wouldn’t it be great for targeting and response to fill in the blanks? Data appending can enhance a house file with hundreds of variables from outside lists, including business “firm-ographics” on revenue, industry, employee numbers, etc.; opt-in e-mail, and telephone numbers. Self-reported LinkedIn data is another source that can be used. For more detailed data cleaning tips, see Synthio’s full article.