Tapping into the customer feedback gold mine
As I pointed out in my previous article, at DailyPay, we are very passionate about understanding our customers' interactions with our product and we iteratively strive to improve customer value and engagement.
The ‘Coffee with Customers’ sessions, mentioned in the aforementioned article, are led by my colleague Katie Speidel and are still going strong. They are an essential fixture of our culture at DailyPay. The weekly sessions are providing unique insights and discussion items across our organization and departments. In these sessions, which are centered around a rotating yet specific topic, Katie shares up to four essential customer interactions with the audience. The immersive observations and discussions within the sessions are very helpful and spark action. They also aim to inspire other groups to dig deeper into what the customers are saying.
In this post, I'd like to go into the mechanisms behind such a deeper investigation by highlighting some techniques my colleague Dan Lee and I are working on in regards to tapping into the feedback provided by customers through calling, emailing, texting, and writing app reviews.
Dan, who is a leader in our product organization, worked with unitQ to understand how their services could provide us with insights related to customer feedback. UnitQ's tagline is "Harness the power of user feedback to improve product quality". UnitQ's proprietary "AI technology extracts data-driven insights from what users are saying to help you increase product quality."
My role here at DailyPay, Inc. is to implement the practice of Digital Experience Intelligence, which also includes linking various tools together in order to provide insights faster and with more clarity.
When I heard that Dan was looking into ways to use unitQ for product improvement and even customer self service enhancements, I jumped at the chance to partner with him. Together, we wanted to see how we could utilize our knowledge of call center hot topics, understand the way unitQ provides insights, and link all of this information to FullStory as a mechanism of ideation, customer empathy, and product improvement. The goal is to find items rooted in user friction that could become roadmap actions that are internally vetted and prioritized.
Dan and I asked ourselves three questions:
Let's take a look at the answers we found.
Structure the customer feedback to align with the top call center concerns
To solve this, Dan and I worked with our operations team to understand the top call center concerns. For example, one of the questions our customers often ask about is how the DailyPay Balance gets calculated.
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Collaboration with call center operations is key here as they know the customer pain points best and are able to quantify the call volume associated with the pain points.
Utilize AI technology to validate user feedback
Creating and saving a query in unitQ is very easy. You simply search for "'Available Balance' AND calculation". UnitQ does the AI analysis via natural language processing in the background. It returns all the customer service interactions falling into the category we are looking at.?
Systematically analyze the friction behind the customer outreach
Next, Dan and I read through the customer feedback returned by unitQ in the specific bucket associated with a customer pain point that’s driving call volume.?
Reading through the customer point of view helps and unitQ presents this portion really well. What’s missing now for great ideation is to better understand how the customer got into the spot that caused the friction.
To make every experience very relatable we needed a mechanism that allowed us to reconstruct the experience the customer had before they contacted us with an issue. This is where Fullstory comes in. It helped us with looking at the experience the customer had when they tried to understand a critical topic, for example the available balance.?
In order to retrieve items that line up with sessions we could observe in Fullstory, we add the following to the unitQ search: "_exists_:metadata.uuid". This metadata add-on ensures that we now see feedback we can link to in Fullstory. And while we are in Fullstory, we are now able to analyze the friction that led to the outreach in the first place.
Documenting the findings, the customer testimonials, and the associated sessions, helped Dan prepare for the next step: creating the prerequisite research for our team brainstorming session which also includes our designer and technical teams.?
As the solutions workshop is happening soon, I can't wait to see what creative ideas the team will come up with and prioritize.
VP, Customer Engagement, Enablement and Advocacy (formerly Product Management). Customer obsessed product and customer success thought and team leader
2 年Such great stuff happening on this team. I am beyond proud of this work.
Account Executive at Snowflake
2 年Great read all the way through. Thanks for sharing Lars!