Working on a New vs Existing product
Strategy block. Session 2.
1. What to build?
1.1.For existing product
Lots if inherit advantages:
Data: assuming feedback loop is in place — you have the full suite
Confidence on hypothesis: high
1.2. For a new product
Time is spent doing all above manually
Brainstorming and answering questions HOW is not systematic. Go through all below one by one.
ProTip: curiosity helps and saves. Always use 5WHYs technique
Sometimes you pretend that you don’t understand to get more insights. Then you learn that you actually didn’t understand it.
2. How to build?
2.1.Existing product
Scope
Much more defined as it has to be part of the existing system. This speeds up the process as assumptions / hypotheses to test and thinks to take into account are
Overheads: deploying, code review, tests, analytics (tracking)
Schedule
Everyone have to be aligned on v1 product:
- Sales & Marketing for PR, setting up campaigns (seasonal stuff)
- Testing for their input etc
2.2. New
Scope
Everything is unproven. Gotta answer:
- How is this related to the database?
- How is this talking to each other, do we have API set up?
- Think about integrating various features when putting them together: front, back, addons. Will the flow created in one thing will have an impact on another one?
Also, a lot of opportunities from solutioning session. Gotta prioritise and understand what to ship in the next Sprint. But confidence is low.
ProTip: define feature using SMART. Don’t scope down to a half of the bridge
When prioritising use the metric: learning from it.
Schedule
The sooner the better, as then you will benefit from data via Feedback loop
Launch = ship x N (keep shipping to learn!)
3. What to measure?
3.1. Existing
The Feedback Loop will give you both Qualitative & Quantitative to learn what’s happening and why. Ex: bounce rate was high, because label used on the CTA “beta” mislead and relucted people.
3.2. New
Goal:
- Tackle the Acquisition
- Once acquisition done, tackle Activation (fastest way to aha!)
ProTip: Try to spot what works for the majority (heatmap helps) and scale it
Again, use the metric: learning from the shipped item.
Credit: ProductSchool
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