Test annual discount at 20% off
Hypothesis: offering 20% off annual plans increases annual signups by 15%. Define target metric and cohort.
Product Startups
Pricing Experiment Board
Run Structured Pricing Experiments From Idea to Decision
The Pricing Experiment Board gives product and growth teams a repeatable kanban workflow for testing pricing changes. Instead of scattering hypotheses across docs and spreadsheets, every experiment moves through four clear stages: Backlog, Testing, Learnings, and Decisions. Each task captures the hypothesis, the live test details, the measured outcome, and the final call, so nothing gets lost between a pricing idea and a shipped decision. Whether you're testing discount tiers, usage-based add-ons, or new plan limits, this board keeps your team aligned and gives an AI agent a clear structure to help manage tasks via the MCP server.
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Template preview
Pricing Experiment Board
4 columns
Backlog
3Capture pricing hypotheses and experiment ideas before they are prioritized for testing.
Explore usage-based add-on pricing
Draft hypothesis for charging per-seat overage beyond plan limit; estimate revenue impact.
Evaluate free plan task limit change
Consider raising free plan from 25 to 40 tasks to boost trial conversion; outline risks.
Testing
2Track pricing experiments that are actively running, including variant details and duration.
A/B test $12/mo vs $15/mo pro tier
Running 4-week test on new signups; 50/50 split. Track conversion and churn by variant.
Trial-to-paid nudge email test
Testing whether a mid-trial pricing email increases pro plan conversion; 2-week window.
Learnings
3Record experiment results and key takeaways once data collection is complete.
Results: annual discount test
Annual signups rose 11%, below 15% target. Discount attracted price-sensitive users with higher churn.
Results: usage-based add-on test
Add-on adoption was low (4% of pro users); revenue lift minimal. Consider bundling instead.
Results: $15/mo pro tier test
Conversion dropped 8% at higher price point but revenue per user increased overall.
Decisions
2Document the final call on each pricing experiment and the reasoning behind it.
Decision: keep pro at $12/mo
Ship: revert to $12/mo pricing since higher price hurt conversion more than it gained in ARPU.
Decision: shelve usage-based add-on
Kill: low adoption doesn't justify added billing complexity; revisit in 6 months.
How to run this board
Step 1
Log every new pricing idea as a task in Backlog with a clear hypothesis and success metric.
Step 2
When ready to launch, move the task to Testing and note the variant setup, audience, and duration.
Step 3
Once the experiment concludes, move it to Learnings and summarize the actual results against the hypothesis.
Step 4
Review Learnings tasks to make a final call, then move the task to Decisions with a ship, kill, or iterate note.
Step 5
Periodically archive or delete completed Decisions tasks to stay within your plan's task limit.
AI agent usage
Run it with AI agents
An AI agent can use this board to run structured pricing experiments end-to-end: logging hypotheses, tracking active tests, capturing learnings, and recording decisions. Using the MCP server, the agent creates tasks in the Backlog column as new pricing ideas emerge, moves them through Testing as experiments launch, and files results into Learnings once data is in, finally updating Decisions with a clear next step (ship, kill, or iterate).
## Pricing Experiment Board
Columns: Backlog, Testing, Learnings, Decisions.
When asked to add a pricing idea, create a task in Backlog with the hypothesis and target metric.
When an experiment starts, move the task to Testing and add the test duration and variant details.
When results come in, move the task to Learnings and summarize the outcome in the task description.
When a call is made, move the task to Decisions and note whether to ship, kill, or iterate.
Use the MCP server tools (list_tasks, create_task, move_task, update_task) to manage this board; do not exceed the free plan's 25-task limit unless the project is on the pro plan.Add a new pricing experiment task to Backlog testing a $49/mo annual discount tier.
Move the 'Usage-based add-on test' task from Testing to Learnings and summarize that conversion dropped 8%.
List all tasks currently in Decisions so I can review what pricing calls were made this quarter.
Learn more about the board-centric workflow in Kanban for AI Agents or open the MCP guide.
Frequently asked questions
How many pricing experiments can I track on the free plan?
The free plan supports 1 project with up to 25 tasks total, so you can track roughly 6-8 experiments at once across all four columns before needing to archive completed ones or upgrade.
What happens if I exceed 25 tasks on the free plan?
You'll need to delete or archive older tasks (for example, completed Decisions) or upgrade to the pro plan, which removes the task cap, for $12/mo or $96/yr.
Can I manage this board using an AI agent instead of manually?
Yes. The MCP server exposes tools like create_task, move_task, and update_task so an AI agent can add experiments, update test statuses, and log learnings on your behalf.
Does upgrading to pro unlock more projects?
Yes, the pro plan ($12/mo or $96/yr) removes the single-project and 25-task limits imposed on the free plan, letting you run multiple pricing experiment boards.
Can I customize the column names for this template?
Yes, columns are fully editable on the kanban board. You can rename Backlog, Testing, Learnings, or Decisions to match your team's terminology while keeping the same workflow.
Is there a way to track this board without opening a browser?
Yes, you can use the macOS app or keyboard shortcuts and the command palette for quick task entry, in addition to managing tasks via the REST API or MCP server.
Related templates
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Sign in and use the template to create a project with columns and sample tasks.