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Big data email case studies
1.
2.
3. Improving Traditional Email Marketing
• Make every email count
• More data equals better targeting predictive power
• More channel data variety equals better targeting predictive
power
4. Results: Increased Click-Thru Rates
Original Big Data and
Campaign Machine Learning
3.3M emails 3.4M emails
60%
35K clicks 57K clicks
5. Opportunity Analysis
Emails Clicks
Original 3.3M 35K Traditional data mining and intuition
Campaign based rules
Big Data 1.5M 37K 55% fewer emails for same clicks
Optimizing for
email volume
Big Data 3.4M 57K 60% more clicks for same emails
Optimizing for
Revenue
6. Optimizing Daily Deal Email
Model propensity to convert for each user on each category
Matrix of Scores: 3.1 Million Members x 568 Categories
Offer 1 Offer 2 Offer 3 … Offer N
User 1 0.01 0.05 0.02 0
User 2 0.2 0.01 0.03 0.4
User 3 0.03 0 0 0.01
:
User 3.1M 0.02 0.5 0.1 0.01
7. Optimizing Daily Deals Email
Offer 1 Offer 2 Offer 3 … Offer N
User 1 0.01 0.05 0.02 0
User 2 0.4 0.2 0.2
0.01 0.030.03 0.010.4
Offer N Offer 1 Offer 3 Offer 2
User 3 0.03 0 0 0.01
:
User
0.02 0.5 0.1 0.01
3.1M
8. Email Marketing as a Strategic Asset
• Strategically define KPI goals
• Use data to transform your process
• Integrate email marketing into overall multi-channel strategy
9. Optimizing Daily Deals Email
Offer 1 Offer 2 Offer 3 … Offer N
User 1 0.01 0.05 0.02 0
User 2 0.4 0.2 0.2
0.01 0.030.03 0.010.4
Offer N Offer 1 Offer 3 Offer 2
User 3 0.03 0 0 0.01
:
User
0.02 0.5 0.1 0.01
3.1M
13. Take Aways
Improve Traditional Email Targeting
• Make every email count
• More data equals better targeting predictive power
• More channel data variety equals better targeting predictive power
Strategically Use Data and Analytics
• Strategically define KPI goals
• Use data to transform your process
• Integrate email marketing into overall multi-channel strategy
Achieve Incremental Value
