Don’t ask for customer “feedback”

… because it will get in the way of making the right decisions for your business.

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I recently received an email from the CEO of a company whose product I had signed up to and tried out once some time ago. This is the email – I have anonymised it for demonstration purposes:

Hi there,

How have you been finding [product]? Do you have any feedback for us? We’re a small team that relies heavily on customer feedback to improve the product. Simply reply to this email with your thoughts!

Thank you!

[Name]

CEO / Co-founder

Asking customers to share their thoughts can be useful if it serves a specific purpose and is targeted, e.g. when you are conducting a usability test in order to understand whether someone can or cannot use your product as you intended or whether they ‘get’ a new feature that you are wanting to release.

Vague questions will give you vague answers

Asking for feedback becomes problematic though when you are posing vague questions like “How have you been finding [product]?” and “Do you have any feedback for us?” as the CEO did in his email. Vague questions will give you vague answers. The data (answers) you get will be all over the place because inviting your customers to provide “any feedback” will get you all kinds of data, from bugs and feature requests to personal opinions. And having vague data will get in the way of making the right decisions for your business, e.g. deciding what to do or what to build next.

The ultimate purpose of taking data is action. Scientific data are not taken for museum purposes; they are taken as a basis for doing something. If nothing is to be done with the data, then there is no use in collecting any. The ultimate purpose of taking data is to provide a basis for action or a recommendation for action. The step intermediate between the collection of data and the action is prediction.

W. Edwards Deming (Source)

Instead of soliciting any feedback and asking vague questions, be clear – before you start your research – about what purpose your research serves and what effect you are trying to create, what data is and isn’t helpful for making decisions, who you need to address in order to get these data and how you collect these data.

Consider this example: As a CEO of a company, you would like to understand how you can get more people to buy your product (the purpose) because you want to create revenue growth for your company, i.e. generate net-new revenues whilst maintaining existing revenues (the effect).

Now, in order to get to an answer to “How can we get more people to buy our product?” and help you formulate an appropriate strategy for achieving revenue growth, you first need to understand how the demand (also known as Jobs to be Done) for your product or service is created in the first place. Specifically, the (helpful) data you want to obtain are your customers’

  • Desires, i.e. experiences they want or want more of but can’t get at the moment,
  • Constraints, i.e. things that prevent them from fulfilling those desires,
  • Catalysts, i.e. events that create or affect a desire, constraint or choice set, and
  • Choice Set, i.e. things that they can hire to overcome a constraint and satisfy a desire.*

You want to collect these data from existing customers who recently, i.e. in the last 2-3 months, bought your product or service and have used it at least once (it is ok if they have stopped using it). Recent customers tend to remember their struggles and the events leading up to a purchase better than customers who bought the product a long time ago.

The way I have found very helpful for collecting “demand data” from recent customers is through 1:1 interviews. Specifically, I ask interviewees questions such as:

“Since you have [product], what are you able to do that you couldn’t do before?”, How has your life changed for the better / worse?” and “Is there anything that you are still not able to do?” (Desires)

“Before you bought [product], what prevented you from achieving [desires]?” (Constraints)

When and how did these desires, constraints and choice set come about?” and “Tell me what happened.” (Catalysts)

“What other solutions (things, people, objects) did you buy or try out or consider buying / trying?” and “What was good and bad about each?” (Choice set)

Final point: even if you are a “small team” like the CEO cited above says, you can still do this type of research yourselves. It requires two people from your team or company (one for driving the conversation, one for asking follow-up questions) and usually takes about 15 customer interviews until you hit the point when you will no longer collect new data. I would also recommend involving your team members and stakeholders in the research so they get to experience the conversations first-hand. They can rotate in and out and actively participate – though I would keep it to 2 interviewers – or just listen in and observe.

Being clear about what purpose your research serves, what effect you want to create and what questions you need to ask whom is critically important for any research effort that aims to support better decision-making. If you want help with understanding your research question, collecting the right data to answer it and gaining actionable insights that help you make better decisions for revenue growth, get in touch with me.

*For more details on what these data types are and the data model that helps to explain and communicate demand for a product or service, see this article.

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