Deeper insights, clever new tools and more effective customer experience strategies – these are the tools you need to do advanced customer feedback analysis
What customer feedback tools are you using to innovate, retain and grow business?
If you’re doing customer interviews and using data to boost loyalty, as well as customer journey mapping and using big data to understand customer needs, you’re already well on your way toward more effective retention and innovation in FinTech.
What’s more, once you have a steady stream of customer data analytics, you can start doing deeper customer feedback analysis to inform an even more effective experience strategy.
Every single touchpoint, on every platform, is a potential gold mine of information. The trick is to pull it all together with a customer feedback analysis tool – here’s what you need to know…
As the name suggests, it’s analysing all customer feedback to inform your growth innovation and development strategies. The key part, however, is collecting data from ALL customer touchpoints – not just your external interviews, MVP feedback and validation experiments.
Customer feedback analysis involves collecting and analysing customer opinions and experiences across all possible channels – from surveys and polls on the web and app to external platforms such as ratings and comments on Google and social channels.
You basically want to find every piece of commentary related to your service or product, find a way to process that enormous amount of data (now easier than ever with AI) and then derive actionable insights that you can use to improve product and service offerings, and build sought-after new ones, first.
See how to innovate more effectively with design thinking in finance and see how to use emotional UX design to connect and build loyalty, plus the ultimate design thinking principles for UX.
If you have lots of touchpoints and data, it’s a big job so we’re going to recommend automation and specific tools – see below. But just so that you know the process and steps involved, we’ll detail it here…
Gather feedback from diverse sources like social media, customer surveys, online reviews, and direct customer interactions. Tools like NPS (Net Promoter Score) surveys can be particularly effective in measuring customer loyalty and overall satisfaction.
See the guide on how to frame customer interview questions for deeper insights and how to get the full picture with customer data analytics.
Use qualitative and quantitative methods to analyse the data. Qualitative analysis might involve sentiment analysis to gauge the emotional tone of the feedback, while quantitative analysis could look at ratings and scores to identify trends and common issues.
Get valuable insights with customer journey analytics and how to optimise your UX for customer satisfaction.
Break down the data by customer preferences, demographics and behaviours to identify specific needs or pain points of different user groups.
Identify the key themes and issues that emerge from the feedback. Determine what changes or improvements are most requested or will have the most significant impact on customer satisfaction.
See how data boosts loyalty, using emotional UX design to connect and this guide to doing customer interviews.
With real-time feedback collection and analysis across multiple channels including in-app, online, and through social media, as well as AI integration and robust data security, this is a sensible option in FinTech.
Offering not only the ability to collect existing data from various sources but also the ability to generate new surveys makes Qualtrics a good option, too. It can handle complex data sets and the company prides itself on regulatory compliance and security.
Specialising in sentiment analysis, Clarabridge can help you better understand customer emotions and intentions. The only potential drawback is that it only works with text-based feedback.
Sprinklr manages customer experiences across 30+ channels, including social media and many digital platforms (just check what tech is compatible) and even has an AI-based function for re-engaging customers, as well as enterprise-grade security features.
This AI-powered platform gathers feedback across various channels – surveys, reviews, social media, and support tickets – with sentiment (emotive) analysis and an AI assistant to help you with analysis.
Get a more in-depth look at the costs, benefits and uses of various customer feedback and experience platforms and customer experience in finance.
Also see how to use analytics for better user engagement and how to hyper-personalise and drive engagement with full customer data analytics.
Once you’ve collected and sorted customer feedback from various sources, you’ll notice that it's quite a lot. The trick is knowing what to action them effectively…
Sort the insights according to how frequent and impactful they are – focus on what most people are asking for, first (so you respond to the largest number of customers’ needs). Then evaluate them for potential impact and turnaround time – a relatively simple UI change is faster to implement than creating a new feature, for example.
Focus on changes that offer the most significant benefit to user experience and business outcomes. Consider how to optimise your UX for customer satisfaction.
Create a clear, step-by-step action plan for implementing changes. This should include specific tasks, responsible teams or individuals, and timelines. See the ultimate design thinking principles for UX.
Ensure that insights and action plans are shared across all relevant functions (departments) – product development, marketing, customer service, etc. – to create a cohesive strategy that aligns with overall business goals.
Implement the changes and closely monitor their impact on customer experience in finance and business metrics. Be prepared to make further adjustments based on new feedback and changing customer expectations. Get insights with customer journey analytics.
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