Demographic attributes
Explore available household and demographic characteristics, such as age bands, household composition, homeownership, or estimated income ranges, to understand audience patterns.
Data enhancement & enrichment
Your customer file holds the starting point. Add relevant attributes, connect what you already know, and build a clearer picture of the people or businesses you want to reach.
A focused approach: useful information, chosen for your marketing goals.
A RECORD IS JUST THE BEGINNING
Illustrative examples, not an actual customer record. Attributes and matches depend on the file and available sources.
What is data enhancement?
Data enhancement adds relevant information to an existing customer or prospect file through matching. Combined with cleanup and organization, it can make your records more useful for profiling, segmentation, and campaign planning.
We begin with the decision you need to make, then identify which attributes could help. The goal is a file you can use with a clear understanding of what the added information means.
Choose the dimensions that matter
These are categories to consider when defining your project. The right selection depends on your file, your audience, and the information available for matching.
Explore available household and demographic characteristics, such as age bands, household composition, homeownership, or estimated income ranges, to understand audience patterns.
Group records by location, service area, or market. Use geographic detail to support regional campaigns, local targeting, and audience comparisons.
For business files, explore characteristics such as industry, company size, or revenue ranges where available. Build segments that better fit your intended business audience.
Explore available interest and lifestyle indicators that may add context to an audience profile. These can be inferred or modeled and should be interpreted accordingly.
Organize purchase or response history you supply, and assess relevant external indicators where available. Use defined activity signals to support meaningful customer groups.
For relevant business projects, assess the availability of information about technologies or platforms a company uses. Scope and coverage are confirmed before inclusion.
From information to action
Enhancement is most useful when it answers a practical question. Start with one audience, one campaign, or one decision you want to improve.
Compare shared attributes across customer groups to identify patterns worth exploring.
Combine available attributes with your own customer information to define audiences around clear criteria.
Apply agreed geographic, household, or business criteria to prepare a more focused audience file.
When campaign and response records are supplied, compare audience groups to help inform your next selection.
How the work comes together
Discuss the intended use, source files, requested attributes, and output requirements. Confirm scope, pricing, and timing.
Review the file structure, standardize relevant fields, and address duplicate or incomplete records as agreed.
Apply the agreed matching and enhancement work. Keep unmatched records and limitations visible in the result.
Return the agreed output and explain the appended fields, processing results, and any exceptions that need attention.
A usable deliverable
We agree on the deliverables before work begins. That may be an enhanced CSV or Excel file, a set of audience selections, or a processing summary to support your next step.
The format should fit your workflow, and the results should make it clear where the data is complete and where gaps remain.
Before we begin
Start with a description of your file, approximate record count, available identifying fields, and intended use. We can then agree on the appropriate next step for reviewing the data.
Yes, projects can involve consumer or business records. The available attributes, matching requirements, and relevant sources differ, so each is scoped accordingly.
Not necessarily. Cleanup can be included in the project. Inconsistent names, addresses, and other identifiers can affect matching, so we review preparation needs before enhancement.
No. Results depend on the identifiers supplied, source coverage, and requested attributes. Unmatched records and incomplete fields are normal possibilities and should remain clear in the output.
No. Some attributes are reported or observed; others may be estimated or modeled. The distinction matters when interpreting and using the data, and we discuss relevant limitations for the selected fields.
Pricing depends on volume, preparation work, requested attributes, available sources, and delivery requirements. We establish the scope and provide a project quote before processing.
Start with a useful question
Tell us about your file and what you want to accomplish. We'll help define the next step.