Find which prospective customers are most likely to respond positively to campaign outreach strategy and tailor campaigns around their preferences
Use Case
Marketing Campaign Success Modeling
Truly effective marketing campaigns are optimized based on what will get prospective customers to buy. To predict which customer will respond positively to campaigns, organizations must efficiently associate customer demographics and behavior with the right outreach at the right time.
Top-Line Growth
Customer Experience
Uncover the factors that most negatively impact campaign yield and use those insights to optimize customer experience
Efficiency Gains
Test multiple different modeling techniques simultaneously and operationalize the best predictor
Business Problem
The most effective marketing campaigns are the ones that are fully optimized to what prospective customers will respond to. To optimize a marketing campaign, certain types of questions must be addressed:
- Messaging: Is the content touching on the right value drivers for the customer?
- Format: Is the outreach too long or does it contain too little information?
- Audience: Are you reaching out to the right customers?
Without knowing these questions, marketing teams risk not hitting the mark in messaging, not reaching out to the right customers, or using their time inefficiently. Teams must go beyond simple conversion metrics and look deeper into demographic data that impacts what makes prospective customers convert.
Alteryx Solution
By connecting demographic customer data with campaign metrics like type of outreach and campaign success, marketing teams can predict which customers will convert and uncover what features most impact campaign success. A drag-and-drop analytics platform like Alteryx enables marketing teams to test multiple different modeling methods automatically and use the best predictor to drive campaign strategy and uncover what kind of customers they should focus on.
With Alteryx, you can:
- Import campaign results in any format and use the Browse tool to get a good understanding of data quality
- Perform robust data cleansing with the Preparation toolkit to remedy issues with your data and perform feature exploration with the Data Investigation toolkit to understand which modeling techniques best fit the current problem
- Simultaneously test different hypotheses on what factors have the greatest impact on likelihood a campaign touchpoint converts
- Test multiple different models and then operationalize the one that best predicts campaign outcome
Marketing Campaign Prediction Designer Workflow
1 – Data Import
Attach a browse tool when you import data to get an immediate view of your data
2 – Data Exploration
Run multiple exploratory data analyses simultaneously to optimize data investigation
3 – Model Testing
Sample data for input into one or multiple Machine Learning modeling tools
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