Success stories or best practices for working with customer feedback at scale (B2C)

  • 23 June 2022
  • 3 replies
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Hi community,

I’m super curious if anyone has experience working with customer feedback at scale for making great products in a company with a B2C use case. A company that has 100’s of thousands or millions of end-users of your product.

Firstly, it would be great to know what processes you are using or tools that work really well to understand your users better. I’m not saying these methods would work really well but just thought I could jot down some questions to spark conversation:

Are you periodically posting a NPS survey or some other survey type to your customers with an in-product prompt for example?
Does your support team have an efficient process for sharing product feedback with the product team?

Do you run some type of community or forum to collect product feedback?

Do you have a mature data analytics team that can extract data from places where your customers talk about your product? e.g. social media, forums, support pages

Would you be focusing more on product analytics rather than reviewing direct customer feedback?

The next area I would think about is, what would be the best places to consolidate all that feedback data for analysis to help drive product decisions. I can imagine it could be a huge challenge to collect all this data in a single place and make sense of it.

 

Are you using any tools to consolidate all this feedback data in one place?

Is there any neat ways you are analysing the data? (e.g. just looking at particular segments or samples)

 

Thanks for reading & hoping we can get a conversation going!

 

All the best,
Daniel.
 


3 replies

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It’s been a few years since I’ve done a direct to consumer app, but here’s what worked for me …

5-point satisfaction scale using emoji’s. NPS is an annoyingly wide scale for users and I find that response rates will go down (true for B2B as well). Amazon’s championing of the 5-point scale probably means something.

Follow up with one or more of the following open text questions (be responsive to sentiment where appropriate):

  • Tell us more about why you answered that way?
  • What do you like about [ product ]?
  • What would you change about [ product ]?

Analyze the open text response with whatever tooling you have available (I had data scientists) and segment it at minimum by the sentiment.

Publish high-level metrics and trends over time with your analysis for the rest of the company and connect that analysis when communicating initiatives and objectives.

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Thanks so much for your response. These are really great notes. It does seem that having a data science team or product analysts to run analysis is common in this type of scenario.

 

Can you remember what tooling you used to capture the 5-point satisfaction score? Was this built in-house or something off the shelf?

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Can you remember what tooling you used to capture the 5-point satisfaction score? Was this built in-house or something off the shelf?

 

I was once forced to build a survey product against my will 😰 But you don’t need to go to that extreme.

The off the self survey solutions today are great. I’ve used Qualtrics, SurveyMonkey, Typeform, and even Google Forms for a small beta program.

Frankly, I thought they all worked out great. I like Typeform, but I don’t think the platform matters nearly as much as carefully crafting the questions and flow.

 

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