Making a Recommendation

Leadership asks:

Should we build self-serve onboarding or keep routing every new customer through sales?

You have data.

You have opinions.

You have uncertainty.

Now you need to recommend something.

Do not begin with ten slides of background.

Start with:

I recommend testing self-serve onboarding for small customers while keeping sales-led onboarding for larger accounts.

Now everyone knows what you are proposing.

Then explain why the decision matters.

For example:

Small customers wait an average of three days for onboarding, and 22% never schedule the call.

That tells the audience what problem the recommendation addresses.

A useful structure:

Option A

Keep the current sales-led flow.

Option B

Move everyone to self-serve.

Option C

Use self-serve for small customers and sales-led onboarding for larger accounts.

Options make the trade-offs visible.

For Option C:

Benefits:

• faster setup for small customers
• preserves high-touch support for larger accounts
• lower risk than changing everyone at once

Costs:

• two onboarding paths
• more product complexity
• eligibility rules

Now the recommendation feels earned.

Strong recommendations do not hide uncertainty.

Say:

The biggest risk is that small customers may still need human help during setup.

Then explain how you will learn:

Track completion, support requests, and 30-day retention during the pilot.

A strong product recommendation usually contains:

1. decision
2. context
3. options
4. trade-offs
5. recommendation
6. risk
7. next step

You do not need a giant document.

You need clear thinking.

A PM recommendation should make the decision easier.

Say what you recommend, why, what you are giving up, and what could still go wrong.