Make Your Data More Effective with Data Normalization
Data is the fuel that runs your marketing automation engine. It drives all the major initiatives of marketing automation, including lead scoring, segmentation, nurturing and measuring marketing’s contribution to revenue. Without accurate data, all your marketing initiatives miss the mark.
Data normalization means ensuring the consistent capture of the data points you care about as a marketing and sales organization. Although similar to good data hygiene, normalization tackles “dirty” data up front, saving time, effort and problems down the line.
Data normalization should be applied to all incoming data sources, including form-fill data, purchased lists and tradeshow contacts. Data such as job title, industry, state, country, or platforms/technologies impact lead scoring and nurture messaging, so accuracy and consistency are vital.
Ensure Clean, Meaningful Data
DemandGen’s Data Normalization Service includes the following activities to ensure your data is as consistent, clean and usable as possible:
- Familiarize ourselves with your business situation and work with you to identify which data fields matter to your organization.
- Evaluate your database setup for each field to determine what clean values should look like.
- Help you understand data entry points, including forms, list uploads and other sources. Understanding where and how this data is collected helps us determine what type of normalization you need.
- Define the look-up matrix that maps all possible variations of dirty data to your new standard data values.
Data normalization should take place at the very beginning of the lead management workflow, and should continually run in the background. That way, you can ensure every action taken against your data is worthwhile, because the data is clean, complete and meaningful to your business processes.