Company Name:

TaskHive

 Company Overview:

TaskHive is a growing SaaS startup that provides a collaborative productivity platform for individuals and small teams. Its freemium product helps users manage projects, create task boards, track deadlines, and integrate with popular tools like Google Drive and Slack.

Core Features:

• Task Boards (Kanban-style)

• Calendar & Deadline Reminders

• Team Collaboration Tools

• File Attachments & Comments

• Integrations with external platforms (Slack, Google Drive, Trello)
  
  

 Business Model:

• Freemium Tier:

  • Access to basic task boards

  • Limited file storage

  • 2 collaborators max

  • Limited integrations
    
    

• Paid Plan (TaskHive Pro):

  • Unlimited boards and storage

  • Up to 20 collaborators per project

  • Priority support

  • Advanced analytics and reporting

  • All integrations enabled
    
    

 Current Problem:

TaskHive is struggling with low freemium-to-paid conversion rates (~3%). Despite strong user acquisition and engagement with core features, most users remain on the free plan indefinitely. Leadership wants to identify:

• What behaviors or usage patterns signal a higher likelihood to convert

• Which features are most commonly used by paying users

• How to improve conversion with data-backed feature, pricing, or UX changes
  
  

 Main Business Problem

Low conversion rate (~3%) from freemium to paid users on our product.

 Key Analytical Questions

1. Conversion Overview

• What is the overall conversion rate?

• What is the average time to conversion for users who upgrade?

• What is the distribution of conversions by acquisition channel?
  
  

2. User Behavior Analysis

• What features are used most by paid vs. free users?

• Do paid users use more features or use them more frequently than free users?

• Is there a minimum feature usage threshold or pattern before a user converts?
  
  

3. User Segmentation

• Are there user segments that convert at higher rates?
  
  

4. Feature Impact

• Which features are most correlated with conversions?

• Do users who convert interact with premium features earlier or more frequently?
  
  

5. Retention & Engagement

• What is the retention rate for free vs. paid users?

• How active are free users who never convert vs. those who eventually do?
  
  

 Key Metrics to Track

 Conversion Metrics

• Conversion Rate = (Number of Paid Users / Total Users) × 100

• Time to Convert = Average days from signup to conversion

• Conversion Rate by Channel = Conversion by each acquisition source

 Feature Usage Metrics

• Feature Adoption Rate = % of users using each feature

• Average Feature Usage Count per user type (free vs. paid)

• Top Features Among Paid Users = Ranked by usage count

 User Engagement Metrics

• Daily/Weekly Active Users (DAU/WAU) by user type

• Avg. Usage Days Before Conversion

 Cohort Metrics

• Monthly Signup Cohort Conversion Rate

• Retention Curve = Percentage of users active over time by cohort

 Data Overview

 1. taskhive_users

This table contains user-level demographic and account data, including subscription status and acquisition information.

• Row Count: 2,200 users

• Paid Users: ~8% of total users

• Free Users: ~92% of total users
  
  

2. taskhive_feature_usage

This table logs interactions between users and various features within the app, tracking engagement over time.

• Row Count: ~13,000+ rows

• Features Tracked:
  
  

  • task_creation

  • file_upload

  • calendar_access

  • team_collaboration

  • integration_used

    

 SQL Analysis Findings & Insights

 1. What is the overall freemium-to-paid conversion rate?

 Insight:
Out of 2,200 users, approximately 8%(165) converted to paid plans — confirming TaskHive's concern about low conversion rates.

 2. Which acquisition channels drive the most conversions?

 Insight:

•  referral and social media rakes in the highest conversion rates

•  paid ads and organic brings in volume but low conversion showing a high friction between quantity and quality

  
  

 3. How long does it typically take a user to convert?

 Insight:
Paid users typically convert within 30–45 days after signup. This is a critical engagement window.

 4. What features are most used by paid users vs. free users?

 Insight:

• Free Users mostly use file upload, integration and calendar_access.
  
  

• Paid Users heavily use file upload,team_collaboration,  and calendar_access

 Suggests file upload,team_collaboration,  and calendar_access

are premium value drivers.

 5. Are paid users more engaged overall?

 Insight:

• Paid users are more active and take more actions per user.

• They exhibit higher engagement even before converting.
  
  

 6. Top features used in the 30 days before conversion

 Insight:
In the 30 days leading up to conversion, the most-used features are:

• team_collaboration

• Calendar access

• Task creation

  

  These can be emphasized in onboarding or upsell nudges.

  
  

 7. Which month had the highest conversion rate (Cohort Analysis)?

 Insight:
Recent cohorts (especially the last 3 months) are showing slightly improved conversion, indicating potential impact from ongoing experiments or organic growth.

 Key Takeaways

• High-value features like file upload,team_collaboration,  and calendar_access drive conversion.

• Referral and social media channels bring higher-converting users.

• Engagement in the first 30–45 days is critical.

• Free users who never convert tend to underutilize advanced features.

• June - July is the month with the highest conversion rate making it a crucial month to increase product awareness and engagement.
  
  

Business Recommendations for TaskHive Stakeholders

 1. Double Down on High-Impact Features in the Free Tier Experience

Insight: Paid users engage heavily with features like  file upload,team_collaboration,  and calendar_access prior to upgrading.

 Recommendation:

• Make these features more discoverable to free users through in-app nudges or tutorials.

• Allow limited access or trial usage (e.g., “3 free team collaborations”) to trigger value perception.
  
  

 2. Optimize Onboarding for the First 30–45 Days

Insight: Most conversions happen within 30–45 days of signup.

 Recommendation:

• Introduce goal-oriented onboarding workflows that push users to adopt premium features early.

• Launch automated email/SMS onboarding sequences with engagement triggers based on behavior.
  
  

 3. Reallocate Marketing Budget Toward High-Converting Channels

Insight: referral and social media users convert at significantly higher rates than paid_ads.

 Recommendation:

• Shift budget from underperforming paid channels to referral programs and SEO/content marketing using high converting social media platforms.

• Enhance referral rewards and incentivize power users to invite collaborators.

  
  

 4. Experiment with Pricing & Upsell Strategy

Insight: Some users show high feature engagement but still don't convert.

 Recommendation:

• Introduce usage-based nudges, e.g., “You’ve collaborated with 3 users – upgrade for more.”

• A/B test offering discounted trials, limited-time upgrades, or flexible pricing tiers.
  
  

 5. Build User Segmentation for Personalized Outreach

Insight: Not all free users are the same — some are more active and show higher intent.

 Recommendation:

• Segment users into buckets: low activity, exploratory, and high-intent based on engagement.

• Use targeted messaging: e.g., product updates for explorers, conversion incentives for high-intent users.
  
  

 6. Track Feature Impact and Conversion Cohorts Continuously

Insight: Feature usage and cohort performance vary over time.

 Recommendation:

• Set up automated dashboards to monitor:

  • Conversion rates by acquisition channel

  • Feature usage heatmaps

  • Retention curves by signup cohort

• Use these for ongoing optimization and product iteration.
  
  

 Summary for Stakeholders:

 Next Line of Action:  Analysis to Execution processes

 Immediate (0–2 weeks) — Quick Wins & Planning

1. Run a Feature Trial Campaign

   • Allow free users limited access to premium features (e.g., “Try 3 team collaborations”).

   • Measure engagement uplift and trial-triggered conversions.
     
     

2. Activate Onboarding Improvements

   • Add contextual prompts inside the app for high-value features.

   • Launch automated onboarding emails highlighting premium feature benefits.
     
     

3. Refocus Marketing Spend

   • Pause low-ROI paid ads.

   • Boost referral program visibility and double rewards for a limited period.
     
     

 Mid-Term (2–6 weeks) — Optimize & Test

4. Segment Users for Targeted Communication

   • Build engagement-based user segments (low, medium, high).

   • Send tailored upsell or reactivation messages per segment behavior.
     
     

5. A/B Test Pricing & Offers

   • Test: discounted first month, extended trial, or new mid-tier plan.

   • Analyze which pricing experiments yield better conversion and LTV.
     
     

6. Launch a Cohort Conversion Dashboard

   • Track signup cohorts, conversion timelines, and feature usage trends in real time.

   • Make this dashboard accessible to Product, Marketing, and Growth teams.
     
     

 Long-Term (6+ weeks) — Scale What Works

7. Product-Led Growth Loop

   • Encourage team invites and integrations to drive collaboration-led virality.

   • Incentivize invited users to explore premium features early.
     
     

8. Feature Usage Scoring Model

   • Use past data to score likelihood to convert based on behavior.

   • Feed this model into CRM to prioritize leads for sales or messaging.
     
     

9. Optimize Acquisition Channels

   • Based on cohort performance, invest in SEO, referrals, and influencer partnerships.

   • Reduce CAC while maintaining or increasing conversion rates.
     
     

view dashboard here

view project presentation here