THE SITUATION
Participants are difficult to recruit post-churn.
Prior to full churn (abandonment), user behavior can be unpredictable.
Why Omnichannel?
Humans are unique. We can divide them into segments.
Yet as your company grows or evolves the variety of voices, each deserving of their own time being assessed, grows as well.
Look at the data streams below.
Which is more important than the others?
When do you leverage one or the other?
When do you combine a variety of them into a decision?
Behavioral Metrics
Analytics collected from customer interactions with your product or service.
Custom Support Queries
Transcribed calls, chat comments, or formal tickets.
Social Media Comments
Reviews left on websites or social media engagement.
Quantitative Surveys
Attitudinal surveys, Concept Testing, post-launch KPI outreach, etc.
Qualitative Sessions
Observational field research, in-depth interviews, usability testing, etc.
Longitudinal Values
Synthesis of previous reports, benchmarks, or multi-week diary studies.
THE QUESTIONS I WAS TASKED TO ANSWER
What are the leading causes of churn from our ecosystem?
What behavioral and purchasing metrics actually correlate with retention?
How can we better design our user journey to balance spending and session goals while reducing burnout (churn)?
BEHAVIORAL DATA
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Historical Analytics
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Last 3 Months of Behaviors
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Model for Churn Likelihood
CUSTOMER SUPPORT DATA
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Support Call notes
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Chat / Ticket tags
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Email logs / tags
SURVEY
SAMPLE:
> 50% Churn Probability
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Importance/CSAT
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Attitudinal KPIs
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Frustrations / SUPR-Q
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Trust & NPS
INTERVIEWS
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Switching Behaviors
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Perceived Value
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Service Experience
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Brand Perception
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Future Intentions
DELIVERABLE
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Predictive Model
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Buckets of Churn Probability
DELIVERABLE
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Sentiment Analysis
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Cluster Analysis
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Prioritization Matrix
DELIVERABLE
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Consolidated Report
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Updated Customer Service Triage
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New Purchase Packages
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Design Recommendations
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Push Notification Updates
EXCERPTS
