Founded nearly a decade ago, this leading fintech set out to revolutionize the banking industry, offering a range of financial services tailored for everyday people. This company provides its millions of members with user-friendly financial products, such as debit cards, early paydays, savings accounts, and cryptocurrency options, all without typical banking fees.
The problem: Inundated with customer feedback
As the fintech leader was growing, they were manually identifying, labeling and quantifying 10,000-plus pieces of customer feedback on average per day from a broad range of channels—including sources like Zendesk support tickets, iOS and Android app store reviews, PissedConsumer reviews, Reddit threads, Twitter tweets, Stella Connect and more to uncover user issues, product pain points and trending sentiment.
The organization has always been a user-centric company and recognized early on that their customer feedback is the best resource for determining what is and isn’t working across their products and services. However, it was a challenge for the member experience, data science, and engineering teams to monitor all of this incoming feedback from disparate channels to resolve user issues and improve roadmap planning with real time user insights.
In response, the fintech company began looking for an AI-first software that could help give their members the quality products and experiences they deserve. They wanted a solution that not only provided a 360° view into all feedback from any source, but that could also translate, categorize, and alert their engineering, product, and support teams on trending quality issues for more effective release management, roadmap planning, and support case resolution.
The solution:
unitQ provides actionable AI insights
“AI technology from unitQ is providing us with real-time actionable insights from our members’ feedback to inform our decision making in our mission to boost financial independence and merge true asset ownership with traditional banking,” says the company’s CTO. “The unitQ platform is a critical component to how we create financial progress for everyday Americans.”
With unitQ, the fintech’s teams can see a holistic view of trending user friction, support requests, product feature requests, and more, pin pointable by source, platform, device, customer segment, and more across 500 categories of user feedback. Types of issues encompass complaints about deposits, multiple charges, login hiccups and PINs not working. Other issues – like phone verification codes not being received or activated cards not showing up in their mobile app — are also detected in real time by unitQ.
The team employs unitQ to categorize all user feedback, particularly from Zendesk tickets, and then pushes the user feedback data as tags so the right teams, with the proper skills, can triage and address issues immediately. Faster resolutions are also made possible with unitQs Slack integration, which alerts engineering, product, and support in real time to spiking issues.
unitQ dashboards are utilized to analyze feedback trends across their product and diverse landscape of users to measure things like sentiment around promotions or recent brand refreshes — as well as feature releases like the buying and selling of crypto — to evaluate performance and assess where to invest next. Most importantly, unitQ’s powerful AI-powered insights form the basis of company-wide reporting on key topics to drive user-centric decision making across all teams.
Anomaly detection
Another great unitQ feature they capitalize on is the ability to detect anomalies in user feedback data. Anomaly alerts use machine learning to automatically trigger when the system finds an atypical spike in feedback volume. For fintech companies, this is invaluable given that for certain times of the year, there are increases in certain issues like tax-related issues during tax season or payday-related issues that occur bi-monthly for example.
“It’s great that unitQ’s anomaly detection automatically incorporates seasonality and can look for what is expected and not expected in certain times, so we can react to alerts accordingly and address timely issues like tax season and paydays,” says the company’s Head of Member Experience Strategy.
Results: Reduced support ticket volume
While this fintech’s customer base has doubled, help desk tickets have decreased 35% following their adoption of unitQ. This reduction in support tickets means this fintech is offering a higher quality customer experience as they are able to resolve issues faster with unitQ before they turn into support tickets.
Their benefits of using unitQ include the following:
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Improved app store reviews and increased app performance
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Expansion of customer base and enhanced customer satisfaction
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Decreased volume of support inquiries
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Introduction of new fintech features surfaced from user feedback
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Greater job satisfaction for developers and support staff with an increase in productivity
“With timely issue resolution because of actionable user insights provided by unitQ, we have maintained a highly satisfied user base and prevented issues from snowballing,” says the fintech’s CTO. “With unitQ, the process of identifying problems impacting the customer experience is automated, eliminating the need for manual efforts and enabling us to make better decisions and products.”
About
unitQ
As the leading Quality Automation platform, unitQ empowers companies with AI-powered, actionable insights from user feedback to help them craft high-quality products, services and experiences. unitQ centralizes feedback from all sources and automatically groups it into thousands of granular categories to help organizations discover what matters most to users — all in real time. Category-leading companies like Spotify, Bumble, Pinterest, Udemy and HelloFresh rely on unitQ to drive growth, reduce churn and build brand loyalty.
With unitQ customer feedback software, including unitQ GPT, organizations can discover quality issues at the same time as their users. Know what product launches, releases or evergreen features are causing the most bugs or support tickets. Drill into the root causes of these issues by source, platform, device, customer segment and more.
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