Narada PMF

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Narada: Product Market Fit

Analyze feedback from Narada Users

Judiciously use feedback to deep dive into Narada's initial product market fit hypotheses and convert ambivalent users into people who love Narada.

As our segments and personas are defined, we can analyze the data to discover (1) why people love Narada, and (2) how you can help more people love Narada. We can then funnel these insights back into your

Roadmap development and feedback⁠

to decide where to “deep dive” and shift the "somewhat disappointed" to become enthusiastic advocates.

A. Segment to target personas

Examine the users who would be very disappointed without Narada — these are the people who most love Narada — and use their personas to narrow the market. We should see the very disappointed group fall into our persona groups which will allow us to do deep dives into those groups (and go find other users).This will eventually grow our product market fit score from our initial baseline

We can toggle the personas below to see how changing the market affects the product/market fit score. This is much more efficient than asking the engineering team to develop every feature that comes up in a feedback call. These are the personas from our Trello.

Instructions: Check the Is Target Persona boxes below to decide which personas to include in our target market. Then, look at the charts below to determine if we have product market fit within your selected basket of personas.

Is Target Persona?

Persona

% Very Disappointed

% of Responses

Open

🌻 Small/ Med Fund Firm Manager

15.00%

↗️

🪑 Startup Tech Founder (Sales Hat)

30.00%

↗️

✋ Tech Sales- BDR

0.00%

↗️

🚧 Tech Sales- Account Manager

10.00%

↗️

Real Estate Broker

0.00%

↗️

🤑 Tech Sales- VP/ Director of Sales

10.00%

↗️

Attorney/ Small-Med legal firm

0.00%

↗️

🧗 HR Recruiter

5.00%

↗️

Gig/ Concierge Service

0.00%

↗️

Non Profit Manager

0.00%

↗️

⚙️ Accounts Receivable (Braxton)

0.00%

↗️

🥼 Cyber Security Manager/ Analyst

0.00%

↗️

Healthcare Practice (not corp)

5.00%

↗️

There are no rows in this table

⁠

Survey Results

The important number to look at here is the “very disappointed” percentage. If it’s over 40%, we have product-market fit.

Product market fit threshold:

⁠

Selected personas above:

0

⁠

% very disappointed →

No product/market fit 😦

⁠

All survey respondents:

0

⁠

% very disappointed →

No product/market fit 😦

⁠

Segmenting to target personas may not be enough. In order to reach a 40% threshold we should also understand why these users really love Narada—and how we could help more users love Narada.

This is why we included additional key questions:

Why do people love Narada?

What holds people back from Narada?

B. Why do people love Narada?

Method: What benefits do very disappointed users enjoy?

To understand why people love Narada, we take the users who would be very disappointed without Narada, and analyze their responses to question #3: "What is the main benefit you receive from Narada? We can collect the data into word cloud like the one below to see what trends emerge.

"Main Benefit" responses from target persona users who would be
Very disappointed
⁠
if they couldn't use Narada anymore:

⁠

C. What holds people back from loving the product?

Method: What improvements do somewhat disappointed users want?

To understand what holds people back from loving Narada, we take the users who would be somewhat disappointed without the product, and focus on the subset for whom the main benefit of the product matches the theme we just identified in the previous step — (These are the users who are on the verge of loving the product, but something — and likely something small — is holding them back.) We then analyze their responses to question #4: "How can we improve Narada for you?".

We can use the keyword search below to explore how Narada’s benefits corresponded to areas of improvement.

Segment the "somewhat disappointed" responses by your main benefit keyword

Enter a keyword for the main benefit you would like to analyze:

salesforce

⁠

Segmented

Segmented score

Count of responses

Very disappointed

Not disappointed

Target: Somewhat disappointed (main benefit includes your keyword)

Non-Target: Somewhat disappointed (main benefit does not include your keyword)

There are no rows in this table

⁠

Word cloud of responses to "How can we improve Narada for you?" from somewhat disappointed users who found the main benefit

⁠

This might be evidence that we are missing a feature or quality of Narada that could enhance our product market fit, but we have limited resources and cannot develop every feature or fall into the Second System trap

that Amir identified as a startup risk⁠

. This leads straight to our next step: the

Roadmap development and feedback⁠

⁠

👉 Next:
`Roadmap development and feedback`⁠
⁠

⁠

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Analyze feedback from Narada Users

A. Segment to target personas

Survey Results

B. Why do people love Narada?

"Main Benefit" responses from target persona users who would be Very disappointed⁠if they couldn't use Narada anymore:

C. What holds people back from loving the product?

Segment the "somewhat disappointed" responses by your main benefit keyword

Word cloud of responses to "How can we improve Narada for you?" from somewhat disappointed users who found the main benefit

👉 Next: Roadmap development and feedback⁠⁠

"Main Benefit" responses from target persona users who would be
Very disappointed
⁠
if they couldn't use Narada anymore:

👉 Next:
`Roadmap development and feedback`⁠
⁠