The document discusses reducing customer churn by mapping the customer journey. It notes that churn can happen due to unmet expectations or business changes like going out of business. To reduce churn, the document recommends extending customer lifetime value through a customer-centric approach and gaining actionable insights. It provides a 5-step process to identify problem areas in the customer journey using data analysis: 1) select a process to examine, 2) analyze data, 3) find drop-off points, 4) measure customer sentiment to understand thoughts, feelings and actions, and 5) ensure data analysis informs marketing improvements through testing hypotheses.
15. PICK ONE PART OF THE OPERATION OR END TO END
• Email onboarding
• Funnel
• Support tickets
• Calls
• Departments
• Fulfillment
• Upsell / downsell sequence
STEP 1 //
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16. STEP 2 //
START WITH YOUR DATA
• Analytics
• Feedback
• Support tickets
• Social
• Ratings & review
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17. STEP 3 // IDENTIFY DRILL SITES
• At what stage do they stop taking all action and fall off the grid
• At what stage are customers not taking the expected action
• At what stage do you see support tickets coming in
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18. STEP 4 // MEASURE SENTIMENT
WHAT ARE THEY THINKING?
• IQ
• Skills
• Reasoning
• Knowledge
• Experience
• Education
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19. STEP 4 // MEASURE SENTIMENT
WHAT ARE THEY FEELING?
• Desires
• Motivation
• Attitudes
• Preferences
• Emotions
• Values
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20. STEP 4 // MEASURE SENTIMENT
WHAT ARE THEY DOING?
• Are they moving as predicted?
• Are you managing their expectations?
• Are you asking too much or too little?
• How high are you asking them to jump?
• Is what you’re asking in alignment with their perceived value?
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21. STEP 5 // WHERE DATA ANALYSIS
& MARKETING MERGE
• If data collection is the goal, confer with Marketing to ask if this
data set is substantive to their work
• Begin with a hypothesis that you can test out
• Ask your team to provide 2 questions as to how you can improve
the copy
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