Discover how to harness the power of customer feedback to optimize your self-service demos. Uncover valuable insights, prioritize changes, and drive sales and marketing growth.
Data, as they say, is the new oil.
On the other hand, data that tells us how our customers see us is the holy grail!
In my previous post, I went into a lot of detail on the many ways we can collect customer feedback. Once you have all this data, it's time to refine and process it so you can extract the maximum insight from it. You see, not all feedback is created equal, and unless we're able to segment it correctly, assign the right weights to it, and figure out what the bulk of our customers are happy and unhappy with, we won't get much mileage from it. Particularly when it comes to self-service demos you're using as a part of your marketing campaigns or your pre-sales effort.
In the PLG universe, we let the product shine. It best speaks for itself through self-serve demos where the prospective customer can get a real feel for the functionality at their own time and pace, and still get enough guidance and contextual input to drive home sales/marketing messaging.
Getting our self-serve demos pitch perfect is the key to unlocking several sales and marketing multipliers. Of course, we never just make the one demo that fits all, but working out what is working for which audience at which stage of our sales and marketing efforts… that can let a tiny little startup with a disruptive idea take on the legacy Goliaths that are protecting their space through massive sales and marketing spends, and win.
So, let's get into it.
The Importance of Analyzing User Feedback
User feedback can also be complex and diverse, depending on the source, format, and type of feedback. Therefore, it is important to use different methods and tools to analyze user feedback and extract meaningful insights from it. Here are some of the most common methods and tools for analyzing user feedback:
Quantitative analysis: Using data analytics tools to analyze numerical feedback data, such as ratings, scores, metrics, statistics, etc. can help you measure the performance of your self-service demos, identify trends and patterns, compare results across different segments or groups of users, and test hypotheses or assumptions.
Qualitative analysis: Interpreting open-ended feedback and identifying common themes or issues, such as comments, reviews, testimonials, suggestions, complaints, etc. can help you understand the reasons behind user behavior, preferences, opinions, emotions, etc., as well as to discover new insights or opportunities for improvement.
Sentiment analysis: Using AI tools to analyze the tone of feedback and gauge customer sentiment, such as positive, negative, neutral, mixed, etc. can help you understand how users feel about your product or service, what aspects of it elicit positive or negative emotions, how sentiment changes over time or across different channels or platforms, etc.
Social media analysis: Using social media analytics to understand customer feedback and trends on social media platforms, such as Facebook, Twitter, Instagram, etc. can help you monitor user engagement with your self-service demos, identify influencers or advocates for your product or service, track user-generated content or word-of-mouth marketing, etc.
SmartCue's Best Practices on Analyzing User Feedback.
Best Practice #1: Well begun is half done.
Define your goals and objectives. Before you even begin collecting and analyzing user feedback, you should have a clear idea of what you want to achieve with your self-service demos. What are the main goals and objectives of your self-service demos? What are the key performance indicators (KPIs) that you want to measure? How will you use the insights from user feedback to improve your self-service demos?
Best Practice #2: Don't use a sword when a needle will do
Choose the right sources and methods. Depending on the goals and objectives you've chosen, choose the most appropriate sources and methods for collecting and analyze user feedback.
For example,
If you want to measure user satisfaction with your self-service demos,
Use surveys or questionnaires to collect ratings or scores from users after they complete your self-service demos.
Use data analytics tools to analyze the numerical data and calculate metrics such as net promoter score (NPS), customer satisfaction score (CSAT), customer effort score (CES), etc.
If you want to understand user problems or pain points with your self-service demos,
Use feedback forms or chatbots to ask open-ended questions and collect comments as well as questions from users during or after your self-service demos.
Use qualitative analysis tools to interpret the text data and identify common themes or issues.
If you want to understand user emotions or sentiment with your self-service demos,
Use social media platforms to collect user-generated content or reviews about your product or service.
Use sentiment analysis tools to analyze the tone of the content and gauge user sentiment.
Best Practice #3: Separate the wheat from the chaff
Segment and filter your feedback. User feedback can vary depending on different factors, such as user demographics, behavior, preferences, expectations, etc. Audiences each have their own quirks - that's why you create custom demos. So how can you feedback collection be any different? Identify the most relevant or significant feedback for each of your self-service demos by creating clear user segments.
For example,
You could segment your feedback by user persona, such as age, gender, location, occupation, etc.
You could segment your feedback by user journey, such as awareness, consideration, decision, retention, etc.
You could filter your feedback by date, time, frequency, channel, platform, etc.
Best Practice #4: A picture paints a thousand words
Visualize and communicate your insights. No one, I mean no one, ever looked at the perfect visualization of complex data and asked to see the raw data - unless you didn't match the right visualization to the right data type.
After analyzing your feedback, you should be able to visualize and communicate your insights in a clear and concise way. Use charts, graphs, tables, dashboards, reports, etc. to present your findings and recommendations. It's always recommended to use storytelling techniques to highlight the most important or interesting insights and to explain the implications and the actions needed.
Since there isn't a one-size fits all when it comes to visualization, play with a few formats till you find what works for you. Some examples that work well for me, personally, are:
Use a pie chart to show the distribution of user sentiment across different channels or platforms.
Use a line chart to show the trend of user satisfaction over time or across different segments of users.
Use a dashboard to show the key metrics and KPIs for your self-service demos.
Use a report to summarize your main findings and recommendations for enhancing your self-service demos.
Implementing Changes Based on User Feedback: A Strategic Approach
Once you've got your insights, you'll have inputs into your change register, your feature development pipeline, and your open (and known) issues register. Some changes/feature requests/issues may seem weightier (louder) than others, and in my experience, these have a tendency to crop up just as you've frozen your development roadmap for the quarter! 😀
While everyone has their own way to manage their development roadmap, and we're all comfortable with different levels of flexibility, there are some general guidelines that seem to work for everybody:
Recognise your most critical pain points, and prioritize those that hurt the most important user group, or the one with the biggest numbers.
Identify which goals and objectives you're contributing to, with each change/feature/performance improvement. Define how you will measure success.
Break down initiatives into manageable tasks or user stories. This approach facilitates better planning, estimation, and progress tracking. Keep an eye on your dependencies so you don't accidentally bottleneck yourselves.
Ideally, use an Agile development approach. In the fast-paced world of SaaS where customer preferences change all the time and new developments are constantly disrupting your industry, the Agile approach gives you room to maneuver and course correct.
Regularly communicate updates, progress, and timelines with the requesters and proactively seek their input and feedback. Utilizing tools like Slack can be highly effective for this purpose.
Pilot test everything. You know how clients don't know what they want? Yeah. Always run a pilot. Always.
Iterate often. When you're constantly improving user experience, your users know they're being heard, and that you're serious about improving their experience.
A/B test where you can. Every little improvement gives you an edge.
And then, repeat.
Conclusion
Why do we do what we do? For the most part, because we have a great solution to a problem. Also, because we're suckers for customer adoration. Most of us thrive on customer appreciation, on being told that what we do matters, and that our work enables others to do what they do.
However, we live in an era where customer loyalty is a bygone ideal. Customers today don't swear fealty like they used to, and we no longer expect them to! Today's customers tell us what's what. Thank God for that. Today, there are SO many ways to listen to our customers - both directly and indirectly, covertly and overtly.
Smart businesses listen, every way they can.
The ones who last, are the ones who take action.
