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Utilizing Recommendations & Relevance Marketing Tools To Drive eCommerce Innovation
Matt [email protected]
@matthewraines
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Quick backgrounders
About Bluefly Online retailer of high-end designer and contemporary fashion and accessories Launched in 1998 $89m net revenue in 2010
About Me Bluefly for 9 years Running Tech for last 6 years Internet companies for 15 years MC5 (remember this for later)
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And a little about you …
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What we’re going to talk about
Exploratory Data Analysis (EDA) as a process
How Bluefly went about this process
Suggestions on how you can do this in your company
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What we’re not going to talk about
Programming languages Coding Data mining Hadoop
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What is EDA?
Exploratory data analysis (EDA) is an approach to analyzing data for the purpose of formulating hypotheses worth testing … -Wikipedia
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We set out to learn more about our customers behavior
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Visualizing the Data
Extracted our purchase data for last 4 years
Imported into visualization tool - Gephi
Similar to “social graph” app on Facebook
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What did learn
Customers stayed within their brand category preference Customers who bought designer continued to buy designer brands Customers who bought contemporary continued to buy contemporary brands
Customers stayed true to their gender Customers didn’t buy for others (spouse, significant other, etc.) Very low gifting business (gift wrap numbers reflect this)
We created a “Customer Behavior Value” (Gender)(Category)(Intensity) WD5 = Womens Designer 5 MC1 = Mens Contemporary 1
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Targeting based on buying preference
The test:1) Target homepage content based on
prior buying behaviorWomen’s Designer homepage #1
Women’s Contemporary homepage #2
Men’s homepage #3
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Women’s Designer
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Women’s Contemporary
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Men’s
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Targeting based on buying preference
The test:1) Target homepage content based on
prior buying behaviorWomen’s Designer homepage #1
Women’s Contemporary homepage #2
Men’s homepage #3
Targeted email campaigns based on Customer Behavior Value
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Targeted email program
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Realized Benefits
1. Increased open rates Open rates increased 50% of targeted segment
2. Increased user site engagement Browser – more pages browsed Shopper – more add to carts Purchaser – more orders
3. Reduced opt-out rates Increased customer relevancy "finally, bluefly got my email gender preference right"
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Where do you go from here
1. What’s your business objective?2. Are you collecting the right data?3. Do you have the right team?4. Can a pattern be identified in the data?5. What is a potential treatment to test the pattern?6. Test the optimal treatment.
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