Presentation from the 6th TestDome Product Talk, held Feb 1st 2023: https://www.meetup.com/iposao-ipivo/events/291139724/ *Description:* Managing SaaS products is hard. You need enough features to be competitive. But too many features make your product bloated and hard to use. There are always more feature ideas than time to implement them. How to select which features and in which order to implement them? In this talk Zel, cofounder of TestDome, discusses feature selection, prioritization, promotion, and feature audit. The first part detects common anti-patterns in product management. The second part proposes a data-driven approach led by customer feedback and analytics. The talk will mention Intercom's free product management book, which we highly recommend.

1. •Please turn off your cell phones.
•The talk will be recorded.
•Q&A will be after the talk.
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2. iPosao iPivo becomes TestDome Product Talks
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3. SaaS Product Management:
Features
Željko Švedić

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5. Outline
• Problem
• Feature selection
• Feature prioritization
• Feature promotion
• Feature audit
• Solution
• Data-driven approach
• Cost-benefit analysis
• Intercom on Product Management
• Frequency vs engagement chart
• TestDome live chart
• Q&A
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6. Problem
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7. Product management problems
1. Selection: What features to implement?
2. Prioritization: In which order to implement features?
3. Promotion: How will users find about the feature?
4. (implementation, deployment, and adoption)
5. Audit: How well the feature performs?
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8. 1. Feature selection decision-makers
A. Founders
B. Product Managers
C. Sales
D. Customers
E. All of the above
- How to weight inputs A, B, C, and D?
- Often gets influenced by office politics.
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9. Sales
example
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10. 2. Prioritization anti-patterns
• Oldest tickets first (FIFO) – “stick to the plan”
• New tickets first (LIFO) – “urgency bias”
• CEO’s tickets first – “boss knows”
• Small tickets first – “completion bias”
• Big customers’ ticket first – “money talks”
• Developers chose – “shiny object syndrome”
• Random – “just sort tickets alphabetically”
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11. Oldest tickets first (FIFO) – “stick to the plan”
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12. New tickets first (LIFO) – “urgency bias”
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13. CEO’s tickets first – “boss knows”
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14. Small tickets first – “completion bias”
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15. Big customers’ requests first – “money talks”
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16. Developers chose – “shiny object syndrome”
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17. Random – “just sort tickets alphabetically”
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18. 3. Feature promotion
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19. Feature
discovery
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20. 4. (implementation, deployment, and adoption)
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21. JIRA
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22. 5. Feature audit
• Is feature delivering value to customers as intended?
• Organizations are reluctant to remove features once they are added
to the product.
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23. Feature
bloat
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24. Solution
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25. Data-driven product management
• Get feedback from customers
• New features
• Existing features
• Estimate cost and benefit
• Frequency vs engagement analysis
• Change plans as new data arrives
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Planning looks at both past and the future

27. Customer
voting
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• UserReport.com

28. UserReport.com entry
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29. Voting results should be
taken with a grain of salt
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30. Cost-benefit analysis
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31. Estimating
• Developers can estimate the cost, but how to estimate customer
benefits?
• Number of votes is not a good measure.
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32. Intercom on Product Management
https://tinyurl.com/278bnpza
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33. Ideal vs typical feature usage
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34. For any feature with a limited adoption there are
four choices:
1. Kill it (remove from the product)
2. Increase the adoption (get more people to use it)
3. Increase the frequency (get people to use it often)
4. Significantly improve it for current users
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35. Feature frequency and engagement
• Frequency: How often customers use the feature?
• Engagement: What percentage of customers used the feature at least
once?
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36. Frequency vs engagement chart
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37. Improving features
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39. TestDome live chart
https://datastudio.google.com/reporting/d63643e9-0522-4a83-afca-57f1ab5c8dd6/page/WcvpC
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40. Summary
• Beware of product management anti-patterns.
• Use data from multiple sources
• Internal sources: founders, managers, sales etc.
• External sources:
• customer requests
• customer voting
• customer interviews
• A/B tests
• feature frequency & engagement
• Tools:
• customer voting system
• cost-benefit analysis
• frequency vs engagement chart
• Don’t be afraid to kill features that don’t perform.
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41. Q&A
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