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Smart Focus |
Segmentation and Propensity Modeling Profiling and segmentation processes allow like-minded consumers to be grouped into manageable cells, and to be targeted with communications that speak specifically to them and address their needs and interests. Affinitas’ regimented segmentation process employs a phased approach to build an initial propensity model, test its accuracy in the mail, and refine it for more efficient future mailings: Phase 1: Prepare Data for Profile * Process customer and prospect data through postal verification software - Customer data will include subscription and account information - Former customer data may include reason for disconnect and account or subscription data * Append demographic and behavioral data from multiple in-house and licensed sources Building the Model and Strategy Development Phase 2: Build Propensity Model Based on Current Customers * Develop profiles of current customers through analysis of demographic, behavioral data, products/services and value (revenue/tenure) * Build a Propensity model based on profiles of current customers for each product or service * Test the accuracy of the model against the entire market including current customers * Refine the model as necessary Phase 3: Direct Mail Strategy Development * Segment and score former and non-customer records by propensity to subscribe based on their matches to each modeled profile * Create a test plan based on targeting records within specific ranges of propensity scores Creative Development and Refining the Model Phase 4: Creative Development * Develop messaging that speaks to each target segment in a relevant way * Incorporate graphic elements that resonate with each target segment Phase 5: Metrics * Calculate response rates and ROI of each mail cell * Evaluate results of each cell with respect to others to verify the model’s predictive ability * Determine which cells should be excluded from future mailings based on low ROI Contact us today to speak with our analytic experts and to learn more about Smart Focus.
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