As we take a look back through the Support Insights Podcast episodes of 2022, we'll be taking learnings from many of our previous guests on how they structure teams, processes and reports to share VOC data in the best way.
We've taken clips from this year's episodes to highlight some of the best examples and advice on encouraging collaborative inter-department relationships.
Nick Moreton tells us how his team at Hotjar are using AI to implement customer feedback in the product roadmap.
Valeria Kast from Printify talks about how encouraging non-customer facing teams to regularly spend time with support speaking to customers.
And we look back at the one central theme that unites all support leaders - a genuine love for customers, for experience and for their teams.
Enjoy the episode, and be sure to check out previous episodes for more insights from our guests.
Harnessing the customer voice in every department - How Snug use feedback to shape strategies across different areas of the business.
We are a very insight driven company. Teams want to see the feedback from customers.
We don't just look at quantitative feedback, we also look at qualitative feedback to really bring the customer voice to life and understand the deep reasons of why someone gave a certain rating, or why do people love Snug, or what are their favourite things about Snug?
Some of the insights are applicable to the whole company in all departments, but I would say, it can be different use cases.
For the brand team or the social team it could be used for content strategy or what do people wanna see on social media?
For the product team it's more about what product features are people looking for or what do they love most about certain ranges?
For the website team it's about the website experience. Are we lacking any specific product information that will help them purchase online?
I think it's been really, really nice to work in a company where customer insights, feedback and customer service and experience is really valued. Cause at the end of the day, that is what's gonna drive higher customer satisfaction and growth.
What does an ideal customer centric relationship between Product and Support look like at Sprout Social?
Well I think that step one is just a mutual respect.
The way that I try to approach it initially in any role that I'm in or any company that I'm in is building trust and an understanding of each other.
I think trust and empathy, all of that, it has to exist. It's the foundation for a good relationship.
Beyond that, there's a lot of process and cadence that I like to implement in which we are providing feedback in a meaningful way regularly.
Right now we do monthly reporting to Product about customer sentiment, customer issues, quantifying, all of those things that we were just talking about from a data perspective.
And then the other thing is it's cross-functional partnership for me too.
It's working with my peers in other departments such as sales and customer success, customer marketing, and really trying to come together about priorities because I think that helps the relationship with Product as well.
I think when we are working individually we're solving the same problems but in different ways. And if we work together, then we can have more of a partnership approach with Product as well.
I also know that one of the ways to influence the product roadmap or influence the minds of product and engineering leaders is to really tie those requests or those priorities that I'm pushing to cost or financial leverages.
So thinking about: we're spending x amount of time supporting this specific part of the product, which equates to X, Y, Z dollars over the course of a year or whatever.
That really speaks the language of product and engineering. So I really focus a lot on our ability to quantify our effort and then be able to also quantify the impact that anything that goes onto the roadmap, any of those feature requests or changes on the back end would make to our overall business.
How can AI help you leverage customer support insights automatically? According to AI enthusiast, Clemens Behrend:
When companies do manual tagging, there's always cases of human error where people forget to apply tags or make mistakes, that's just normal.
AI it doesn't get tired, it just does the job and applies tags automatically, so that's definitely an advantage, it's also way better at spotting bugs.
When we started using AI for automated tagging, reporting and sentiment analysis at Bitpanda, the impact, especially on the team, was employee satisfaction went up. It's an exciting topic, people liked it, people were curious about it, it just motivated them.
Regarding reporting, the most important thing to consider at the very beginning is who the audience of your reporting is.
As a customer support team, you are super biased when it's coming to customer feedback. You will always remember the feedback where the customer asked in the nicest way, in the rudest way, and maybe in the most frequent way.
But does that say anything about how important the issue is? Maybe it indicates it, but not like absolutely.
So what we did is we built a dashboard with an overview of certain topics, customer sentiment, ticket volume for a certain timeframe and also for user group.
Then in addition besides the sentiment and also the volume, we also looked at churn risk.
This allowed product management to access all the data on their own and not rely anymore on customer support.
And actually it helped also the customer support agents that they don't have to always run to product management and tell them hat's not working.
Music: Savour The Moment by Shane Ivers - https://www.silvermansound.com
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- In the next 5 years, customer experience is 45% of companies top priority.
- Investing in CX initiatives has the potential to double your revenue within 36 months.
- 86% of buyers are willing to pay more for a great customer experience.