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In 2012, Southern States Cooperative entered into a case study with Alteryx to utilize the new predictive tools available. The goal was simple: utilize predictive analytics to improve the response rate and ROI on a direct mail campaign. A year later Southern States Cooperative has fully integrated predictive modeling into almost every direct mail effort that goes out and the results have been staggering. Response rates have increased from an average of 3% to over 10% after modeling and the ROI averages nearly 200%. In this presentation Greg will walk you through how they use predictive analytics to improve marketing ROI as well as other ways in which Southern States Cooperative understands their customers better with advanced analytical tools made possible through the use of Alteryx. Greg Bucko, Manager of Customer Insights, Southern States Cooperative
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Improving Marketing ROI with Predictive Analytics
Greg BuckoManager, Customer InsightsSouthern States Cooperative
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Introduction
EvolutionApe Like Approach
Advanced Analytical Approach
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Big Data vs. Usable Data
X
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Biggest Challenge?
TECHNICAL CULTURAL
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Marketing Channels
Social Media
TV
Direct Mail
Happy Customer!
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Marketing Channels
Social Media
TV
Direct Mail
How do we improve Return on
Investment?
Happy Customer!
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“The Shotgun Approach”• The budget dictated the size of
the customer list• Sorted by spending and size• Wimpy return on investment
Where We
Were
“The Targeted Approach”• Focus on propensity• Smaller lists• Bigger return
Where We
Wanted to Be
Setting Goals
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How We Got There
Recognized the Need
Worked With Dr. Dan on Case Study
Began the “Buy-in” Process
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How We Got There
Built Our First Model
Analyzed Results
Communicated
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How We Got There
Iterated
Communicated
Iterated
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Technical Aspects – Building Modeling Set
Identified customers who responded to past direct mail
Calculated statistics like recency, frequency, and monetary value for customers
Appended Experian household demographic data
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Technical Aspects – Modeling
Looked for relationships in the data
Oversampled the responders
Tried different modeling types
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Technical Aspects – Scoring
Chose the best model
Scored the database
Sorted by score high to low
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Technical Aspects – Analyze Results
Calculate response rate, unique SKUs per transaction, ROI, etc.
REPEAT
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Cultural Aspects
#1 Objection to Overcome:
“Wait…what? We are no longer sending to all of our customers?”
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The Answer…
…is in the results.
Drop 1 Drop 2 Drop 3
Sent To
Drop 1 Drop 2 Drop 3
11% 11%
24%
Response Rate
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The Answer…
…is in the results.
Drop 1 Drop 2 Drop 3
Margins
Drop 1 Drop 2 Drop 3
136% 116%
479%
ROI
We have now applied target modeling to all direct mail over the last year and have seen significant incremental lift.
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In Summary
Usable Data > Big Data
Cultural Change
> Technical Change
Test. Adjust. Scale Up. Show Results. Repeat.
Any Questions?
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THANK YOU!
