Consumer Demographic Append Overview

Strum Platform regularly enhances clients' consumer data by supplementing a variety of demographic data elements via the Epsilon TotalSource database. These enriched fields are then made available across Strum Platform and Strum Voice for deeper analysis, tracking, trending and communication, offering a more holistic view of the membership base. Clients can leverage regularly enriched demographic data to improve customer segmentation, analytics, targeting, and personalized marketing efforts. The following documentation outlines the included data elements, and the process used to ensure the most accurate data is added.


The following fields are appended to the client's data and can be accessed across various Strum Platform modules such as the Filter Engine, Persona Builder, and visualizations:

  • Lifestyle Niche Code
  • Presence of Children
  • Income Tier
  • Occupation
  • Likely Credit Card User
  • Likely Homeowner
  • Length of Residence
  • Age of Residence

Match Tiers Overview

A tiered matching approach is used to update customer demographic data – further detailed below. The system starts by matching records at the highest level of detail and proceeds to lower tiers if a match is not found. The following match tiers are used:

  • Match Tier 1: First Name + Last Name + Address (or Lat/Long)
  • Match Tier 2: Last Name + Address
  • Match Tier 3: Address
  • Match Tier 4 (for Lifestyle field only): Dominant Value by Census Tract (match based on the most common value within a specific geographic area)

Each tier progressively uses less detailed information, ensuring that the matching process starts with the most accurate and comprehensive approach.


Demographic Data Enrichment Process

This is the step-by-step process Strum Platform follows to update demographic data for consumer records, via Epsilon TotalSource:


1. Data Preparation

The client’s raw data often includes customer addresses that may be in different formats. To ensure consistency and maximize match accuracy, this raw data is processed through geocoding.

  • Geocoding: Customer addresses are run through a geocoding system that standardizes them into a consistent, structured format (e.g., proper abbreviations, correct formatting, matching postal codes). This ensures that addresses are accurately recognized by the Epsilon TotalSource matching system.

Once geocoded and standardized, the processed data is ready for matching against the Epsilon TotalSource database. The standardized fields typically include:

  • First Name
  • Last Name
  • Address (standardized street address, city, state, ZIP code)

It is important to note that the Epsilon TotalSource database is hosted within Strum Platform’s environment, ensuring that no client data is shared with external parties.


2. Demographic Append Cadence

To ensure that data is always up-to-date, Strum Platform runs the geocoding and matching processes daily for any new or changed records. This cadence supports ongoing, relevant communication and analytics. Here’s how it works:

  • Daily append: is applied to
    • Any new customer record found within the daily client’s data.
    • Any existing records with modified name/address elements.
  • Quarterly append: is applied to
    • All customer records to update market data from the latest Epsilon database.

This ensures that your marketing and leadership teams have access to the most accurate and current data, allowing for informed, data-driven decisions.


3. Data Match Tiered Approach

The demographic enrichment follows a tiered matching process, beginning with the highest level of data detail and moving to more generalized matches if needed. Here’s how the matching process works:

  • Match Tier 1: The system first attempts to match records using First Name + Last Name + Address (or Lat/Long). This provides the highest level of accuracy for enrichment.
  • Match Tier 2: If a match is not found in Tier 1, the system attempts to match using Last Name + Address. This is a less detailed approach but can still yield valuable results.
  • Match Tier 3: If no match is found in Tier 2, the system attempts to match using only Address. This broader approach uses address fields to find demographic data.
  • Match Tier 4: If no matches are found in any of the previous tiers, the system will use Dominant Value by Tract. This approach uses the most common values within a specific Census Tract area (geographic area). Note: Match Tier 4 is exclusively used for the Lifestyle field and is not applied to any other demographic fields.

4. Transparency in Matching Process

Strum Platform offers greater transparency into the matching process by allowing users to filter and view records by Match Tier. In the Filter Engine, List View, and List Export, users can:

  • Filter records based on the match tier (Tier 1, Tier 2, Tier 3, or Tier 4), providing more visibility into which tier was used for each record.
  • View/Export insights on which match tier was applied to each record, helping users understand the accuracy of matches and identify areas where less detailed matching (e.g., Tier 4) was used.

This transparency feature helps track the success of each match tier and gives users deeper insight into the data enrichment process.