AI From Doing To Review
I recently spoke on AI to a group of senior Marketers, below is my deck on the current state of AI. I shape the deck from:
How we could think about the next phase of AI as Department and business leaders
With my 4 step process of writing good prompts — Example: (1) Help me (with x) from (2) (y data) to take (3) (z) action for (4) (outcome))
Prompts set up to help you
Better understand user behaviour
Reduce friction in the product
Better understand when need to ramp up CS (Customer support)
Improve performance of campaigns
Optimise web flows and app flow/nudge
Better targeting on CRM flow
Improve communication and nudges with customers (& stop sending emails and SMS pushes at the same time)
So if you need help to analyse and improve user journeys, reduce churn and identify Growth and Product Growth opportunities this deck will help you (with supporting materials underneath)
If you prefer video watch below
The Links From The Deck & Video
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The two most discussed areas of the presentation
My Prompt Dummies Guide:
1. Prompts are like highly effective searches helping you get the best results for your problem
2. Think of prompts like recipes you can edit and add or remove different flavours you prefer, same applies with prompt
How To Shape Better Prompts Guide
Example: Help me (x) from (y data) to take (z) action for (outcome)
1. Start with the problem you have or experiencing, convert into prompt
2. Ask what you are looking for
3. Help to guide the AI tool to analyse data (expected issue to outcome)
4. Tweak like a recipe until you find the output useful.
The Prompts
If you prefer to view on Google Docs click here
I need a comprehensive churn pattern analysis. Here's our data:
Customer Data:
[Insert monthly churn rates]
[Insert customer segments]
[Insert lifetime values]
Behavioural Indicators:
- Usage patterns: [data]
- Feature adoption rates: [data]
- Support ticket frequency: [data]
- Payment history: [data]
Customer Journey Metrics:
- Onboarding completion rates: [data]
- Key feature adoption timeline: [data]
- Engagement scores over time: [data]
Industry Context:
- Industry average churn rate: [%]
- Competitor retention strategies: [details]
- Market conditions: [details]
Please analyse this data to provide:
1. Primary churn indicators ranked by predictive strength
2. Segment-specific risk patterns
3. behavioural sequences that typically lead to churn
4. Time-based patterns (seasonal, usage-based, contract-based)
5. Recommendations for:
- Immediate intervention points
- Process changes
- Monitoring improvements
- Resource allocation
Help me analyse our customer feedback to identify retention risks and opportunities.
Data Provided:
- NPS Responses: [Paste Data]
- Support Tickets: [Paste Data]
- Exit Surveys: [Paste Data]
- Customer Interviews: [Paste Data]
- Social Media Sentiment: [Paste Data]
Please analyse this feedback to:
1. Extract key themes, categorised by:
- Product issues
- Service complaints
- Price concerns
- Competition comparisons
- Feature requests
2. Score each theme by:
- Frequency of mention
- Emotional intensity
- Revenue impact
- Ease of resolution
- Competition advantage/disadvantage
3. Identify:
- Immediate red flags
- Quick wins
- Strategic issues
- Competitive threats
- Customer ad
Help me develop data-driven retention strategies based on this information:
Current State:
- Retention Rate: [X%]
- Target Rate: [X%]
- Customer Base: [Number]
- Average LTV: [$X]
- Churn Cost: [$X]
Customer Data:
[Paste segment data]
[Paste behaviour data]
[Paste value data]
Please create:
1. Segment-Specific Strategies
- High-value accounts
- Growth potential accounts
- At-risk accounts
- New customers
2. For each segment, detail:
- Engagement tactics
- Success metrics
- Resource requirements
- Timeline
- Expected ROI
3. Design intervention programs for:
- Onboarding optimisation
- Usage activation
- Value demonstration
- Relationship building
- Account expansion
4. Create measurement frameworks for:
- Leading indicators
- Lagging indicators
- ROI tracking
- Resource allocation
Format as:
1. Strategy Overview
2. Segment-Specific Plans
3. Implementation Roadmap
4. Success Metrics
Help me design a comprehensive early warning system for customer churn.
Available Data Points:
[List all metrics you track]
[List all customer touchpoints]
[List all system triggers]
Please create:
1. Risk Scoring Model
- Define risk levels (Low, Medium, High, Critical)
- Weight factors by importance
- Set trigger thresholds
- Create scoring algorithm
2. Trigger Events Framework
- Usage decline triggers
- Support ticket triggers
- Payment issue triggers
- Engagement triggers
- Feature adoption triggers
3. Response Protocols
- By risk level
- By customer segment
- By trigger type
- By resource availability
4. Escalation Procedures
- Response timeframes
- Team responsibilities
- Communication templates
- Success metrics
Format as:
1. System Architecture
2. Implementation Guide
3. Response Playbooks
4. Measurement Framework
Help me design targeted win-back campaigns for churned customers.
Churned Customer Data:
[Paste churn reasons]
[Paste customer segments]
[Paste value data]
[Paste time since churn]
Please create:
1. Segment-Specific Campaigns
- By churn reason
- By customer value
- By time since churn
- By industry/vertical
2. For each campaign:
- Messaging strategy
- Offer structure
- Timing sequence
- Success metrics
- Resource requirements
3. Design:
- Email sequences
- Call scripts
- Offer templates
- Follow-up protocols
4. Create:
- Success metrics
- ROI targets
- Resource allocation
- Timeline
Format as:
1. Campaign Strategy
2. Tactical Plans
3. Resource Requirements
4. Success Metrics
Help me analyse our customer journey data and identify optimisation opportunities:
Current Journey Data:
[Paste touchpoint data]
[Paste conversion metrics]
[Paste time-to-value metrics]
[Paste engagement data]
[Paste feedback data]
Please analyse:
1. Map critical moments by:
- Conversion impact
- Customer satisfaction
- Drop-off rates
- Revenue impact
- Resource requirements
2. Identify for each journey stage:
- Pain points
- Friction areas
- Delight moments
- Missing touchpoints
- Automation opportunities
3. Compare against:
- Industry benchmarks
- Customer expectations
- Competitor experiences
- Best practices
4. Prioritize improvements by:
- Impact potential
- Implementation effort
- Resource requirements
- Expected ROI
Analyse our customer friction points:
Data Available:
[Paste support tickets]
[Paste feedback surveys]
[Paste behaviour analytics]
[Paste abandonment data]
[Paste time-on-task metrics]
Please:
1. Categorize friction points by:
- Technical issues
- Process complications
- Communication gaps
- Resource limitations
- Knowledge gaps
2. Score each friction point by:
- Customer impact
- Revenue impact
- Resolution complexity
- Resource requirements
- Competitive disadvantage
3. Recommend solutions for:
- Immediate fixes
- Short-term improvements
- Long-term transformations
- Prevention measures
4. Create implementation plans with:
- Timeline
- Resource needs
- Success metrics
- ROI projections
Help optimise our journey personalisation:
Current Data:
[Paste segment data]
[Paste behaviour patterns]
[Paste preference data]
[Paste response rates]
[Paste conversion data]
analyse:
1. Segment-specific journeys by:
- Customer type
- Value potential
- Industry/vertical
- Use case
- Maturity level
2. Identify opportunities for:
- Content personalisation
- Timing optimisation
- Channel preferences
- Feature recommendations
- Support customisation
3. Create personalisation rules for:
- Welcome sequences
- Onboarding paths
- Feature adoption
- Expansion triggers
- Retention programs
4. Define success metrics for:
- Engagement rates
- Conversion lift
- Time-to-value
- Customer satisfaction
- Revenue impact
Help optimise our customer touchpoints:
Current Touchpoint Data:
[Paste channel data]
[Paste engagement metrics]
[Paste response rates]
[Paste conversion data]
[Paste customer feedback]
Please analyse:
1. Each touchpoint's:
- Effectiveness
- Cost efficiency
- Customer preference
- Technical performance
- Resource utilisation
2. Identify opportunities to:
- Automate interactions
- Improve timing
- Enhance messaging
- Add value
- Reduce friction
3. Recommend:
- Channel optimisation
- Content improvements
- Timing adjustments
- Resource reallocation
- Technology upgrades
4. Create a measurement framework for:
- Touchpoint performance
- Customer satisfaction
- Business impact
- Resource efficiency
Help me create a comprehensive journey analytics framework:
Available Data:
[Paste current metrics]
[Paste tracking capabilities]
[Paste business goals]
[Paste technical constraints]
Please design:
1. Key metrics for:
- Journey progression
- Stage conversion
- Time-to-value
- Customer satisfaction
- Revenue impact
2. Tracking framework for:
- Customer behaviour
- Journey efficiency
- Resource utilisation
- Business outcomes
- ROI measurement
3. Reporting structure for:
- Executive updates
- Team insights
- Customer communications
- Stakeholder alignment
- Performance optimisation
4. Implementation plan with:
- Technical requirements
- Resource needs
- Timeline
- Success criteria
BONUS PROMPTS
Performance Marketing Analysis Prompt
I need help analyzing and optimizing our performance marketing campaigns with a focus on Customer Acquisition Cost (CAC). Please analyze the following data and provide strategic recommendations:
Campaign Data
[Include your campaign data in this format]
Time period: [specify dates]
Channel breakdown: [list channels with spend and results]
Current CAC by channel: [list CAC figures]
Conversion rates by stage: [list conversion rates]
Customer LTV data: [if available]
Campaign creative performance: [if available]
Analysis Requirements
Please provide:
Identify channels with lowest and highest CAC
Analyze CAC trends over time
Compare CAC against industry benchmarks
Find correlations between creative performance and CAC
Identify conversion rate bottlenecks
Calculate ROI by channel considering LTV
Spot seasonal patterns affecting CAC
Optimization Requests
Please recommend:
Top 3 immediate actions to reduce CAC
Channel budget reallocation suggestions
Testing priorities for creative and targeting
Specific optimization opportunities by funnel stage
Budget scenarios for scaling efficient channels
Output Format Requested
Key findings summary (max 5 bullets)
Detailed analysis by channel
Prioritized recommendations with expected impact
Suggested testing roadmap
Risk assessment for major changes
Additional Context
[Add any specific business context, goals, or constraints]
Industry: [your industry]
Primary KPIs: [list beyond CAC]
Budget constraints: [if any]
Seasonal factors: [if relevant]
Competitor context: [if available]
Think like
Think like a CFO of a <company size> and help to qualify my argument for <topic> example additional investment for <topic / channel> example customer acquisition and refer a friend campaign
Example “think like a cfo and help to qualify my argument for additional investment for customer acquisition and refer a friend campaign”
If you’d like to watch the full webinar with Katie, Adam & Luis enjoy below
