Product Surveys: Gathering Customer Feedback and Optimizing Products
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Tel: (+234) 802 320 0801, (+234) 807 576 5799
Email: info@Stonehillresearch.com
Office Address: 5, Ishola Bello Close, Iyalla Off Street, Alausa, Ikeja, Lagos, Nigeria
Introduction
New product research gathers valuable information so that companies can better understand customer behavior and create products that meet their needs. This type of information provides vital and important information needed to improve products and services.
Product research gives you the inside information you need to design new products, grow your business, and succeed in today’s competitive marketplace. However, if your product research is properly structured, it will allow you to modify your product based on meaningful insights and improve customer satisfaction and customer retention. Whether you’re just starting a SaaS company or you’re an experienced product manager, getting feedback from your users is important. Creating systems that collect consistent customer feedback can ensure product success and product innovation, and avoid assumptions and misunderstandings about the user experience.
Product and user research is important for product managers to gather valuable information or confirm ideas and hypotheses and anticipate customer expectations.
Additionally, honest feedback from properly delivered product research can help you illuminate each step of the user story. By knowing what these users know, you can grow loyal customers. Product research is one of the best ways to find out if your company is growing your products. it’s almost like they’re forcing you to review the product. Sometimes it’s the way the questions are worded; they ask you questions that prevent you from expressing your feelings about the product. It helps to get feedback from many different customers. To ensure a reliable and fair result when testing a product, the survey questions must be carefully described.
If you do some product research, you may find that some are too rigid. Product research is an important part of market research because it helps you understand what your customers think about your products or services. So, it is very important to get it right.
Definition of key terms product research, customer feedback, AB testing etc.
What Is Product Research?
A product survey is a survey that collects comments and opinions about a product from different people. Its purpose is to find out how the market reacts to the product, what customers like best and what could be improved. In other words, a product survey is a survey you send to segments of your audience to gather their feedback about your product. Product research is a tool that allows a company to find out what their users think about their products.
Conducting a survey before launching a product means you can see what people really want and need.
Steps for Making A Product Survey
Define Your Objectives
Choose the Right Audience
Be Simple and Short
Use Open-Ended and Graphical Rating Scale Question Types
Consider Incomplete Responses
Use Tools and Resources
Analyze Results
Let Customers know their feedback is considered
Product Focus Product-related questions
Demographic questions
Product user experience questions
Graphical rating scales
Open-ended questions
Important Product Survey
Customer satisfaction: This a type of survey helps companies measure customer happiness and identify product or customer experiences for development purposes.
Competitive advantage: Companies can gain a competitive advantage by offering products that better meet customer needs and expectations through product research.
Product feedback: Companies use product surveys to get feedback from customers to identify product strengths and weaknesses.
Product development: This can help organizations find improvements and improvements that customers want.
Market Research: Product research can help companies understand their target market and make better product choices.
Types of Product Survey
Net Promoter Score (NPS) Survey
NPS surveys help you find out how likely a user is to recommend your product to a friend.
CES Survey (Customer Effort Score): CES surveys measure the effort users make to use your product or service.
Customer Satisfaction Survey (CSAT)Customer Satisfaction Survey helps you understand the satisfaction level of your users.
Product Market Study (PMF)
PMF studies help you measure how close you are to achieving a product market fit for a specific target audience.
Feature Deployment Survey
Beta Feedback Survey
Run a beta survey to the right audience in the most contextual way possible to find out what your interested users think about your new features or potential improvement. Turnover Feedback Survey
The Performance Feedback Survey makes it easy to collect feedback for users who are graduates. The more knowledge you collect, the easier it is to identify patterns that affect your product growth.
Identity research
Identity research helps you understand how your customers use your product and what you can learn from them.
Knowing Your Products Usage Time
Product survey can be used in many ways and it all depends on your goals.
Features Accept Registrations
Upsell Options
Avoid Turnover
Manage User Research
Create Personal Review
Product Map
Product Research Advantages
Usability Testing
Configure Features
Understand Your Customers
Create personalized recommendations
Making better business decisions
New Product Features
New Logos
Website launch or redesign
Name testing
Package testing
Pricing testing
Device Operation Help for Product Search
Finisher
Qualtrics
GetFeedbackSurvey
TypeForm
Survicate
What Is Customer Feedback?
Customer feedback is information that customers provide about their experience with a product or service. It aims to discover their satisfaction and help product; customer success and marketing teams understand where there is room for improvement. Businesses can actively collect customer feedback through surveys and by surveying, interviewing or asking for reviews. Teams can also collect feedback passively by providing users with a place in the product to share comments, complaints, or praise.
In other words, customer feedback is any information that customers provide to a company about their experiences, including perceptions, opinions, reactions, preferences, and complaints about a company’s products or services. Examples of customer feedback are: Customer service feedback. Questions. Note.
Importance of Customer Feedback
Customer feedback is important because it informs a business about what people experience and expect when interacting with the organization. The company can then use that information to make better, customer-centric decisions.
customer feedback can improve:
Products or services
Internal processes that impact the customer experience
Customer engagement
Types of Customer Feedback
Customer feedback surveys
Customer interviews
Customer focus groups
Social listening
Online reviews
Community forum
Customer support interactions and data
Best Practices for Collecting Feedback
Make it easy to leave feedback
Collect feedback using a variety of channels
Pay attention to timing
Offer rewards in exchange for feedback
Gather qualitative and quantitative feedback
What Is A/B Testing?
An A/B test is an experiment for determining which of different variations of an online experience performs better by presenting each version to users at random and analyzing the results. A/B testing demonstrates the efficacy of potential changes, enabling data-driven decisions and ensuring positive impacts. In an A/B test, you take a webpage or app screen and modify it to create a second version of the same page. This change can be as simple as a single headline, button or be a complete redesign of the page. Then, half of your traffic is shown the original version of the page known as control or A and half are shown the modified version of the page the variation or B.
Benefits / Importance of A/B Testing
Increased conversion rates
Higher conversion values
Ease of analysis
Quick results
Everything is testable
Reduced risks
Reduced cart abandonment
Increased sales
Improved user engagement
Improved content
Reduced bounce rates
Best Practices for A/B Test
Get ideas from everyone
Control for time
Run tests in week-long increments
Always be innovating
Go for big easy
Find your sore spots
Test changes only where changes are needed
Make A and B significantly different
Reasons for A/B Test
- A/B testing can lead to higher conversion rates. With A/B testing, you can experiment with every single element on the page to constantly chase a higher and higher conversion rate. The higher your conversion rate, the greater the return on investment in most cases, which leads us to the next reason.
- Greater ROI from all traffic sources
After all, your business goals are likely tied to the actual returns that the conversions lead to.
- De-risk design layout and messaging updates
Instead of just going “full send” with your changes with your fingers crossed, you can significantly reduce the risk by running a simple split test first.
- Build the page you were dreaming about as a variant
- Launch it as an A/B test against your current control page
- Monitor the data to make sure your assumptions are correct
- Better understand your customers & visitors
Test your assumptions with real users. Run A/B tests to experiment with product messaging, value propositions, or just overall page layouts.
How do you run an A/B test?
Cool, so now you know the basics of A/B testing. But how exactly do you go about setting up and running an A/B test to improve your campaign performance?
Here’s the step-by-step process of running an A/B test, from the initial stages of identifying your goals and formulating hypotheses, to creating variants and analyzing the results.
Step 1: Identify your key metric and goal
Before you start A/B testing your campaign, you should get super clear on the outcome you’re hoping to achieve. For example, you might want to increase your ad clickthrough rate or reduce your landing page bounce rate. (Whatever metric you want to influence, though, remember that the ultimate aim of A/B testing is to increase your campaign conversion rate.)
A clearly-defined goal will help you shape the hypothesis of your A/B test. Say you’re getting lots of traffic to your landing page, but visitors aren’t clicking on your CTA—and you want to change that. Already, you’ve narrowed down the number of variables you might test. Could you improve CTA clicks by making the button bigger, or increasing the color contrast? Could you make the CTA copy more engaging?
Once you’ve got your testing goal, forming a hypothesis is a whole lot easier.
Step 2: Form your hypothesis
The next step is to formulate a hypothesis for you to test. Your hypothesis should be a clear statement that predicts a potential outcome related to a single variable. It’s essential that you only change one element at a time so that any differences in performance can be clearly attributed to that specific variable.
For example, if you want to improve the clickthrough rate on your landing page CTA, your test hypothesis might be: “Increasing the color contrast of my CTA button will help catch visitors’ attention and improve my landing page clickthrough rate”. The hypothesis identifies just one variable to test, and it makes a prediction that we can definitively answer through experimentation.
Make sure that your hypothesis is based on some preliminary research or data analysis so that it’s grounded in reality. (We already know high-contrast CTA buttons get more clicks, for instance.) Whatever you test, you still want to be reasonably confident that it’ll be effective for your audience.
Step 3: Create your variants
Creating variants means developing at least one new version of the content or element you want to test, alongside your control version. In a standard A/B test, you’ll have two variants: variant A and variant B
“Variant A” is typically your control variant—the original version of whatever you’re testing. Since you already know how this version is performing, it becomes our baseline for any results. This is your “champion” by default. It’s the one to beat.
“Variant B” should incorporate whatever changes to your variable that you’ve hypothesized will improve performance. If our hypothesis is that a different color CTA button will get more clicks, this is the variant where we’ll make that change.
Although most A/B tests have just two variants, you can test additional variants (variant C, variant D) simultaneously. But be aware that more variants mean it’ll take longer to achieve statistical significance—and if you introduce any additional variables to the test (like a different page headline), it can become almost impossible to say why one version is outperforming another.
Step 4: Run your test
Once you’ve got your variants, you’re ready to run your A/B test.
During this phase, you’ll divide your audience into two groups (or more, if you’ve got more than two variants) and expose one half to variant A, the other to variant B. (Ideally, the groups should be totally random to avoid any bias that might influence the results.)
It’s essential that you run your test for long enough to reach statistical significance. (There’s that term again.) Essentially, you need to make sure you’ve exposed each variant to enough people to be confident that the results are valid.
The duration of your test can depend on things like your type of business, the size of your audience, and the specific element being tested. Be sure to calculate your A/B test size and duration to ensure your findings are accurate.
Step 5: Analyze your results
After you’ve got a large enough sample size, it’s time to analyze the data you’ve gathered. This means scrutinizing the metrics relevant to your variable—clickthrough rate, bounce rate, conversion rate—to determine which variant performed better. The winner becomes your new “champion” variant.
Say, for example, you’re testing a new CTA button color on your landing page to see if it gets more clicks. You’d want to compare the clickthrough rate on the button of your page variants and see which is getting more visitor engagement.
Depending on what you’re testing, you might need to use analytical tools to dig into the data and extract actionable insights. This step is critical—it not only helps you identify the winning variant, but can also provide valuable information you can leverage in future marketing campaigns.
Step 6: Implement the winning version
The final step of your A/B test is to implement your learnings across your campaign. With these new insights, you can confidently roll out your “champion” variant and expect higher overall performance. Nice.
But the process doesn’t stop here. You should keep monitoring the performance of your changes to make sure they’re getting you the expected results. You also should already be starting to think about what you might test next, looking for new ways to improve your performance.
Which brings us to the final step:
Step 7: Run another A/B test (and then another)
After you’ve implemented the winning version and wrapped up your initial test, the best thing you can do is simple:
Run another test.
Quite literally speaking, you can and should always be testing something. There’s no reason not to. It doesn’t matter if your last 10 tests all fell flat on their faces or all crushed your loftiest expectations—just keep testing.
Test your H1.
Test your buttons.
Test your form length.
Test your hero images.
Test the testimonials you’re using.
Test your section order and overall layout.
Just keep going. Take what you learn from one test on one page and apply it to another. Then take what you learn from that test and apply it to the next, and so on.
Optimization is a mindset. Never stop testing.
A/B testing metrics to measure
First, the metrics you’ll already be familiar with.
More often than not, conversion rate will be the ultimate metric you’re looking to improve when you A/B test.
It may be more indirect at times (i.e. a test focused on improving a leading indicator that will likely result in more conversions) but the end goal will remain the same:
Get more conversions.
Conversion rate metrics
Conversion rate can then be split into three primary categories, depending on what the desired action is on the page:
- Form submission rate
For lead capture pages with a form directly on the page, the conversion action you’re optimizing toward will be the number of form submissions. If you can improve the rate at which form submissions happen, you’re moving in the right direction.
- Purchase rate
For ecommerce businesses and product pages especially, the desired action on the page will be to complete a purchase. Depending on your checkout process, you may use add to cart rate as an alternative metric here, but keep the end goal in mind if you do—driving purchases.
- Click-through rate (CTR)
Lastly, the “catch all” metric for pages where the desired action is just clicking something, typically a button. If the rate at which visitors click your call to action (CTA) button goes up, chances are that’s a good thing.
User experience and visitor behavior signals
In addition to the primary metrics above, you can also test against plenty of user experience-focused metrics to optimize the things that indicate a conversion is likely.
For example, if you can improve the percentage of users who start filling out a form, you’ll likely see a lift in your overall conversion rate as a result.
- Time on page: Average time spent by users on a specific page.
- Form start rate: Percentage of users who start filling out a form.
- Form abandonment rate: Percentage of users who start filling out a form but don’t complete it.
- Pages per session: Number of pages a user visits in a single session.
- Session duration: Total length of time a user spends on the site during a single visit.
- Scroll depth: How far down the page users scroll, indicating content engagement.
- Bounce rate: Percentage of visitors who leave after viewing only one page.
- Exit rate: Rate at which visitors leave from a specific page.
- Navigation path analysis: Common paths taken through your site, indicating user flow.
- Interactive element engagement: User interactions with elements like sliders, calculators, or quizzes.
- Video engagement metrics: Includes views, play rate, and average watch time.
- Heatmap analysis: Visual data on where users click, move, and scroll on your pages.
- Page load time: Speed at which your pages become fully interactive.
- Mobile responsiveness score: How well your site adapts to mobile devices.
Marketing campaign, funnel, and business metrics
Beyond the direct on-page metrics, you can also monitor plenty of higher-level metrics related to overall campaigns, lead quality, and return on investment.
For each of the metrics below, you could segment users to compare those who converted through a given landing page vs all others to optimize accordingly. For example, you may run an A/B test that ultimately results in a 50% lower conversion rate but 200% higher lead quality score, which should still go down as a win in the record books.
Lead quality score: Average quality of the leads your page is generating.
Organic vs Paid Traffic Conversion: The conversion rates of free sources compared to paid sources.
Referral Conversion: The conversion of visitors through referral links.
Retention rate: The percentage of customers who continue to buy over time, indicating long-term value.
Loyalty Program: Participating in and committing to loyalty programs that demonstrate customer loyalty.Net Promoter Score (NPS): Customer’s willingness to recommend your product/service based on their segment.
Average time to conversion: The average time it takes for a lead to become a customer.
Funnel Conversions: Conversion rates at different stages of the marketing funnel.
Cost per lead (CPL): The cost to acquire a lead, which indicates the effectiveness of the campaign.
Return on Advertising (ROAS): The revenue generated per dollar spent on advertising.
Email Open Rate: The percentage of recipients who opened your email.
Email CTR: The percentage of recipients who click on links in your email.
Customer Acquisition Cost (CAC): The total cost of acquiring a new customer, which indicates the effectiveness of the campaign.
What Is A Responsive Product Survey
Product feedback surveys are a tool you can use to learn how customers view and interact with your product or service.
These surveys give you insight into what your customers like and don’t like, and give you advice on how to further improve your product or service. In addition, these surveys give your customers the opportunity to be honest about your products and share their thoughts and opinions with you. Their feedback can be very useful and even influence changes to your product to maximize their user experience and attract new customers.
Conclusion
If you are truly committed to growth as an organization, you will understand that your product must be shaped by the opinions of your product users, not the other way around.
It also helps improve your brand image and bottom line. Product research is a great way to develop a product that meets your customers’ preferences, increases their satisfaction and increases revenue. But not all product research is effective.
Product research is useful for organizations that want to develop a new product, update an existing product, or generate new product ideas. Product research can even help you break into new markets by assessing your target audience. As a result, almost all customer satisfaction organizations use product research.
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Tel: (+234) 802 320 0801, (+234) 807 576 5799
Email: info@Stonehillresearch.com
Office Address: 5, Ishola Bello Close, Iyalla Off Street, Alausa, Ikeja, Lagos, Nigeria
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