CNX16 - Learn How Data Science Can Power Smarter Customer Journeys
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The document outlines a presentation on how data science can enhance customer journeys, focusing on strategic services, journey forensics, and predictive modeling. It discusses various challenges faced by businesses, such as subscriber retention and data integration, and presents solutions including analytics dashboards and tailored customer engagement strategies. Key insights include using statistical models to predict customer behavior and optimize marketing efforts, along with the introduction of a subscriber early warning system.
CNX16 - Learn How Data Science Can Power Smarter Customer Journeys
- 1. #CNX16 Learn How Data Science Can Power Smarter Customer Journeys Schuyler Wareham Sr. Manager, Data Science (Services) swareham@salesforce.com
- 2. What We’ll Cover Today… Overview of Data Science Strategic Services Journey Forensics + Customer Stories Exercise: Maturity Modle review | Identify how you can use Data Science to Power Smarter Customer Journeys 1 2 3
- 3. Data Science Illuminating The past & present of your business with data insights Modeling Future marketing strategy with statistical tools
- 7. The Science of Strategy Connecting data-based insights to value-driving actions Unifying & transforming datasets from every touchpoint at massive scale Extracting insights from data via statistical models and lenses Technical Statistical Strategic
- 8. Predictive Modeling Future behavior-focused analysis and action Analytics Dashboards Custom, interactive visualizations Journey Forensics Data-based customer experience gap analysis • Custom, sharable data visualizations • Drill down & filter in real time • KPI consulting and performance trends • Data landscape audit • Behavioral analysis and key moment definitions • Data-driven journey optimization • Align strategy and insights to create desired outcomes • Model behavioral drivers & predictive scoring
- 9. Predictive Modeling Predicting the future to retain customers and revenue Analytics Dashboards Connecting teams with program performance Journey Forensics Decision making moments that truly matter Journey Forensics Pivoting a communication paradigm to the customer
- 10. • Challenge: Understanding subscriber brand affinity across multiple brands • Salesforce identified personas based on engagement, rather than explicit opt-ins • More accurate and expanded targeting, sending the right content to the right consumers Identifying Audiences Based on Implicit Preferences
- 11. • Challenge: Disparate systems and performance data stalled journey planning • Salesforce developed key data views into an aggregated interactive dashboard • Single view of program performance, flexible enough to customize in real time Charting Performance with MasterCard
- 12. • Challenge: Customer retention challenges despite robust renewal messaging • Data Science evaluation scored behaviors, revealing key personas and actions • Increased engagement & renewals by refocusing on events & customers vs renewal A Customer-Focused Communication Paradigm
- 13. • Challenge: Transform business rules into journeys emphasizing decisive moments • Salesforce connected the customer experience dots across offline & online customer marketing data and disconnected departments to create a unified plan • Predictive model showed key conversion moments and improved program performance Finding the Moments that Matter
- 14. • Challenge: Predict segment and individual-level risk of purchase or list attrition • Salesforce created a predictive statistical model using multiple datasets to predict and evaluate behaviors, then matched tactical mitigation programs to risk factors • Increased retention as high-risk customers move into new course-correcting journeys Predictive Modeling Retains Customers
- 16. Where are your subscribers today? Where will your subscribers be tomorrow? The List Health Spectrum Point of No Return UnsubscribeAt-RiskHealthy Where are your subscribers today? Where will your subscribers be tomorrow? Know where your subscribers are! Predict and take action on where your subscribers will be!
- 17. The Standard Approach Point of No Return UnsubscribeAt-RiskHealthy Subscriber Health When Most Companies Realize a Subscriber Is In Trouble: • Subscriber Hasn’t Engaged in 6+ Months • The Subscriber Unsubscribed
- 18. How SEWS Can Protect Your List Point of No Return UnsubscribeAt-RiskHealthy Subscriber Health The Subscriber Early Warning System (SEWS) Identifies At- Risk Subscribers BEFORE the Point of No Return SFMC: Mr. Jones behavior is consistent with eventual unsubscribing. Mr. Jones has been placed in an automated re-engagement campaign.
- 19. TBD Raw Data Access and Hygiene In-app Reporting Custom Analytics Predictive Modeling Machine Learning Data Science Maturity Model Level 0 Level 1 Level 2 Level 3 Level 4 TBDList GrowthAdmin Deliv Log SQL Extracts Transformation and Delivery Subject Line Analysis Dashboards Standard Battery Propensity to Purchase Subscriber Early Warning System (SEWS) Cross-channel/ Connected Devices IoT
- 20. #CNX16 Where is your organization on the Maturity Model?
- 21. #CNX16 What Data do you Have Ready Access to?
- 22. #CNX16 Typical Challenges in your Business? …and what are the Data Science methods that can address them?
- 24. Join Us For Dreamforce 2016 October 4-7, 2016 | San Francisco, CA