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“Good design is good business.” – Thomas J. Watson, IBM

Have you ever ordered a drink with sugar-free syrup from Starbucks, or instead comfort-eaten an inadvisable number of their red velvet loaf cakes? Maybe you’ve used Starbucks House Blend ground coffee to make coffee at home. If so, you’ve benefited from Starbucks’ consumer feedback.

Customers can be an endless source of great product ideas. Who else has a better sense of how to improve a thing than the people who use it every day? Think about it: How often have you said “Why don’t they just ...” when bemoaning an unintuitive feature or missing capability of a product you otherwise love?

Surveys are a great way to get user feedback as key input for product development. A quick way to collect consumer insights, surveys also fit easily into design and engineering sprints. People tend to be more honest in surveys than they are in focus groups, where they may hesitate to share their opinions or where they can be more easily influenced by the rest of the group.

This guide helps you quickly, easily and scientifically collect product feedback and transform it into information you can use to develop crowd-pleasing products.

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Over the last few years, product development has accelerated. Once upon a time, you’d come up with an idea, spend six months to a year working on it, prototype it and, if it worked well, go to market with it. In today’s app-driven world, increasingly, all product development moves at the speed of software. And with pretotyping now a widespread practice, teams are expected to quickly develop and test ideas – and either scrap or iterate on them – faster than ever.

Receiving product feedback while you’re in the early stages of development can help you get to a great market-ready product faster – or improve an existing product more efficiently. Here’s how you might use feedback for a product update, for example: If you work in two-week sprints, plan to use one sprint to collect and analyse product feedback; one or two sprints to develop high-level concepts or features; and another sprint to test them. If you’re looking for general feedback only and don’t want to test different solutions, a single sprint may be all you need.

Here’s a sample timeline for a new product feature research project:


Once you’ve developed your initial surveys, you can often reuse or automate them, with minor reworking or updates, and field them fast for near-instant insights.

You can’t (sanely) cover everything in a single survey, so you’ll need to prioritise. In general, if you want to get actionable insights, it’s best to focus on no more than a couple of specific areas of interest.

Here are some tips for defining the focus of your survey:

  • Test a few specific concepts (product ideas, new features, etc.) and ask respondents to choose a favourite. You could present concepts using simple descriptions, mock-ups or semi-detailed overviews.
  • Choose one or two specific aspects of a product to improve, asking questions like “What would make this feature more intuitive?” Find answers to a particular business problem, such as “Why are people dropping our service after only a few months?”
  • Choose a particular customer problem to demystify. If you ran a video conferencing company, for example, you might ask, “What is it about remote video conferencing that makes meetings feel less focused?” Your findings might include “background noise”, prompting your team to introduce a mute button.

Focused investigations can quickly give you a clear path forward. On the other hand, surveys that ask broad, open-ended questions such as “Do you like this?” or even “What don’t you like about our product?” can give you unspecific and unactionable responses that leave you no better off than when you started.

Above all, follow the golden rule of product research surveys: Don’t ask for feedback that you aren’t prepared to address.

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There are two key customer or prospect audiences you’ll want to prioritise for product feedback: customers and the market. With customers, your goal is to get detailed feedback without burning them out with lots of surveys or a survey jam-packed with questions. If you’re doing market research, you’ll need to find relevant respondents in addition to getting their feedback. In both cases, the same basic best practices apply.

To get a survey out fast, you can use templates as starting points for developing your customer or market research. Try this customer satisfaction survey template and this market research survey template to build your basic surveys, and then customise each with questions that get to the heart of what’s most important to you and your business.

Here are a few handy tips and tricks to help you build a great survey:

  • Decide who you want to get feedback from so you can craft your survey for your specific audience(s).
  • Include filtering questions you can use in later analysis.
    • For market research, ask filtering questions that give you:
      • Demographic information
      • Insight into respondents’ buying power (Are they a decision maker? A decision influencer? A user only?)
      • Previous exposure to your market
      • Use of competitors’ products
  • In all surveys, use clear descriptions and known market names. Don’t use product jargon (names for features, codenames, etc.) you assume your respondents will know.
  • Consciously or unconsciously, you’re likely to be biased and may be tempted to use surveys to “prove a theory”.
  • Avoid bias by including the option of “Other” with a comment box; randomise answer options; and give customers space to use their own words. Avoid leading questions like “How much did you enjoy this product?” (This assumes the customer enjoyed the product.) Instead ask, “On a scale of one to ten, how would you rate this product?” and then follow up with “Why?” and a comment box for a detailed response.
  • Ideally, keep your survey to 10 or fewer questions.
  • Although they can help customers prioritise or rank their needs/wishes/complaints, matrix-style questions take more time to complete. Keep it to one or two per survey.
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When you’re ready to send your survey to your target audience, these tips can make it easier and more successful:

  • Segment your audience so you can target them more specifically with tools like SurveyMonkey Audience and get insights for each segment. For example, your segments might include current customers; customers ready for an upsell; men or women of a certain age; people with full-time jobs, etc. Using segments will enable you to create an aggregate data set – with specific insights – for each group.
  • Use the SurveyMonkey sample size calculator to work out how many people you need to survey to get statistically significant results.
  • Send your survey via email, social media or a market research panel like SurveyMonkey Audience.

Once you have your results, you’ll want to surface the most impactful findings quickly. The best way to do so is to clean your raw data first and then analyse it.

Before you start analysing your data, make sure it’s as clean and tidy as possible. Here are seven things to filter out of your pool of responses:

  1. Respondents who only answer a few questions. Incomplete responses give you partial insights and can skew your results.
  2. Respondents who don’t meet your target criteria for feedback. Make sure you’re considering feedback only from those respondents whose feedback is most important to you.
  3. Respondents who speed through your survey. If they take just a few seconds to complete your survey, respondents are probably speeding through the questions, which means they might not be reading survey questions carefully or answering them thoughtfully.
  4. “Straightliners”, or respondents who choose the same response – like all “As” for every multiple choice question. As you might guess, straightliners’ feedback isn’t particularly helpful.
  5. Respondents who provide unrealistic answers. Unrealistic responses are outliers and will skew your data.
  6. Respondents who give inconsistent responses. Inconsistent responses call into question the validity of the respondent’s feedback and your overall data set.
  7. Respondents who offer nonsensical feedback. Enough said.

For more details on how to filter and clean in order to address these types of data issues, check out a longer article here.

When you’ve finished your data housekeeping, you’re ready to analyse. Here are a few ways you can refine your data.

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Filters - Filter rules let you break down your survey results and focus on specific parts of your data. For example, you can filter by question and answer to view respondents who answered a question in a certain way or filter by completeness to only see responses where nothing is missing.

For filtering to be really effective, you’ll want to think about how you might want to filter your results when you’re designing your survey. For example, if you want to filter responses by job roles, you’ll need to include in your survey a question about respondent’s roles. Get more detail here.

Compare rules - Compare rules let you choose two or more answer options from a single question and view them side by side. For example, if you include a question in your survey asking people their age, you can create a compare rule to view the survey results for each age range. This can help you understand how different age groups responded to questions in your survey. To learn more about using compare rules, check out our help centre article here.

Tags - Create tags to categorise open-ended text responses. You can create rule-based tags or tag responses manually. Once you add tags to your responses, they'll be visible in the survey's Question Summaries tab or when you view individual responses. See “Tagging responses” for more detail.

Sentiment analysis - Sentiment Analysis automatically categorises your text responses to reveal the emotion behind what people are saying. You can use this feature to analyse all open-ended text except for Multiple Textboxes. (Note that automatic Sentiment Analysis is only available on a paid plan and only works with responses in English.) If you include a general Net Promoter Score question in your survey, you can use that to analyse sentiment too.

Once you’ve refined your data a bit, analysing it will be easier – and yield more meaningful insights. With open-ended questions in particular, weeding out irrelevant responses before you start analysing could save you time and offer uniquely valuable insights.

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Once you’ve completed your analysis, you’re ready to share your findings with others. Your challenge here is to do so in a way that enables your stakeholders – including product, engineering and marketing teams – to act quickly on the valuable insights you’ve extracted.

Fortunately, sharing actionable insights is simple if you’re using SurveyMonkey. You can instantly export data-rich charts, graphs and crosstabs or, if you want to be fancy, use an analytics integration to create interactive dashboards. A few well-chosen customer quotes can also make a powerful point in a presentation or email. Even senior executives can’t easily disregard a point made from the mouth of a customer.

With your initial survey responses in hand, you’re ready to focus on exploring new product ideas. That’s your challenge, and we’re rooting for you. Once you have those new product ideas ready to go, though, surveys come back into play.

Concept testing is standard practice in data-driven marketing and market research, and it’s a great tool for product teams, too. The goal is to narrow down your two to three big ideas to one winner so that you can prioritise – and deliver – the most desirable product or feature first.

This product testing template can get you started. It’s structured with survey logic already built in, so you just need to customise it with the specifics of your concept product.

Here are some tips for building your product testing survey:

  • Choose a series of attributes for your respondents to rank your product against, such as innovativeness, usefulness, value for money, etc., in a matrix question.
  • Randomise the order of questions AND answer options. This is especially important for the attribute questions to avoid biasing your respondents.
  • Remember to include filtering questions so you can use them to sort your responses later.
  • If you’re including images, make sure they are clear and high resolution and display well on mobile devices.
  • Consider including a “forced choice” question asking respondents to pick a favourite if you’re evaluating multiple product ideas and want to prioritise one.

Our Ultimate guide to concept testing walks you through the process step by step.

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Plan to follow up on your product development efforts by using surveys to get feedback, track success and drive continuous improvement and innovation.

For example, you can use this simple NPS (Net Promoter Score) survey template for quick, painless check-ins that give you benchmarks over time. Make sure you compare the responses of people who are NOT using the new product/features/service changes with those who are.

Tracking success helps you track and evaluate the impact of the product changes you’re making over time and prove the value of your efforts. One SurveyMonkey customer, the data science company 4C, used surveys to track NPS when they implemented changes based on customer feedback, and they saw a 20% boost. It's hard to argue with results like that.

Tracking these metrics is the best way to make a case for investment in your projects and get recognition for your team’s hard work.

Surveys are a great tool to add to your agile product development toolset because they open a channel that lets you hear directly from your customers and the market while integrating easily into your existing workflows and processes.

Surveys are also a great way to crowdsource new features, products or services. And what better way is there to demonstrate that you care about your customers than to take the time to ask for customers’ feedback about the products and services they use and then act on it.

NPS®, Net Promoter® & Net Promoter® Score are registered trademarks of Satmetrix Systems, Inc., Bain & Company and Fred Reichheld.