Can you tell us a bit about Nuuly, your role, and how you became a leader in customer service?

Nuuly is owned by Urban Outfitters Inc. and is a curated fashion destination for anyone who loves fashion and is exploring how to wear and buy in ways that are gentler on the planet and their wallets. I’m the Director of Customer Success at Nuuly and lead our support team.

I’ve had experience in various roles before I came to customer service. I started in sales, planned to move to HR, and got an opportunity to take a customer service role in the fashion industry and progressed to a leadership position from there. My roles have always had one common factor throughout, and that was a deep care for people. I’ve always loved building relationships with customers, coworkers, and employees and helping them be successful. And working in customer service at Nuuly with such a passionate subscriber base makes the job incredibly fun and easy.

What motivated you to explore AI solutions for your customer support?

We wanted to get ahead of AI functionality as quickly as we could and be an early adopter of the technology. We actually brought someone on full time to help us explore AI and what it could do for our team around the same time that Intercom was announcing Fin. That worked out really well because we had a dedicated person focused on implementing Fin in a way that made sense for Nuuly and could incorporate all of our brand personality. Ultimately, we wanted to maintain the customer journey that we had already created and have Fin be an added layer of efficiency.

There were a couple of related pain points we were trying to address with AI:

1. Maintaining team size and culture

I wanted to slow down the rate at which we were adding headcount to meet rising demand for support. I’ve witnessed a number of rounds of layoffs throughout my career, and I’m always conscious of not growing the team too fast and running the risk of needing to let people go.

For me, I have found that around 50 associates is a sweet spot for a support team. Anything larger makes me feel disconnected from each individual employee and it’s harder to create a space where employee and customer feedback is heard, recognized, and actioned on. I think a big contributing factor to our high CSAT scores – which are consistently at 95% or above – is that our support team have a genuine connection to our customers. That’s very rare, particularly for the fashion and ecommerce industries.

2. Keeping our contact rate at a manageable level

“Contact rate” is an internal metric we track and is calculated as the percentage of our total subscriber base that reaches out to support each month. We’re a growing business, and as we get more subscribers, we want to make sure the number of conversations hitting our support associates doesn’t explode and overwhelm them. We knew that Fin AI Agent would be the key to doing that.

For reference, our team was struggling with high contact rates at the end of 2022. Anywhere from 30-40% of our subscribers were seeking support every month, which was a lot. Since implementing Fin (which we call “ChatCat”), we’ve dropped that number by 11%, which has made a huge difference for our team.

What were the main challenges you faced while implementing AI, and how did you go about tackling them?

We encountered challenges in two main areas:

1. Knowledge management One of the things we did not have set up initially was help articles. So when we brought someone on full time to explore AI, that was the biggest part of their job – getting all the information we needed to feed Fin into Intercom. But once the knowledge base for Fin was up and running, it was a very easy flip of the switch.

2. Getting team buy-in A big obstacle we faced was initial skepticism within our team. People don’t like change, and in customer service, there are a million different processes, steps, tools, and things to remember, so asking teams to embrace something new can be difficult, even if it’s there to help make their jobs better.

It took some convincing and showing them how it works – and that it works really well – to get them fully bought in. We knew it was important to demonstrate just how much of an opportunity AI presents; if you want to have fun interactions and take on challenging questions vs ones that are really easy to solve and are just kind of mindless, AI is the way to do it. We have a very large team of empaths who like to build relationships both within the team and with our customers. The bigger the team gets, the harder it is to foster those relationships. They understand that AI helps to solve that and now they’re really enjoying not seeing huge queue numbers looming all the time.

Outside of the team, we didn’t have pushback from a leadership perspective and had no security concerns around adopting AI and Fin, which was great. We’ve worked with Intercom for a long time and have a lot of trust in their platform.

What impact have you seen since implementing AI with Intercom? Any “big win” moments you could share?

Since we rolled out Fin, we’ve seen strong results in a number of areas, like:

• Resolution rate: Fin is resolving 38% of conversations it’s involved in right now, which frees our support associates up to work with customers on more complex issues and build strong relationships with them.

• Response time: We’ve reduced our response time by 20% now that Fin is tackling the simple and repetitive queries, so our customers are getting help quicker.

• Staffing forecast: With Fin and Intercom’s other automation features helping us manage our support volumes, we’ve been able to slow projected staff growth by 40%. This lets us maintain our team size and culture, and has also allowed us to be more selective in hiring and get the best of the best candidates.

• CSAT: Customer satisfaction is one of our North Star metrics, and our human-AI approach to support has enabled us to maintain a CSAT score of 95% and above. That comes down to us being able to provide fast and efficient support with AI handling queries that are repetitive or quick to resolve, and our associates having more time to focus on building genuine connections with customers.

The impact we see goes beyond traditional support metrics too. Our business is subscription-based, so we want our customers to come back every single month. One of the things we focus on as a support team is how we can help to retain those customers, and our human-AI approach enables us to solve their issues quickly and efficiently while creating a great experience along the way, which is such an important part of that.

The biggest win we’ve seen to date with AI has been using ChatCat (our customized Fin AI Agent) to reduce human involvement in multitouch conversations and using it to do initial triage. For example, when we need to ask customers for a photo or more information to help them with a query, we could be waiting anywhere from an hour to 10 days to get that information. In those cases, the team was struggling to decide whether to snooze or close conversations or give the customer a nudge. But now, Fin asks for that information before passing the conversation to an agent, which keeps the queues moving and results in faster turnaround of conversations and speedier response times.

What advice would you give to other companies that are hesitant about adopting AI in their customer support functions?

When it comes to AI, you can’t just do it on a whim and let it do its thing, because it may not be as successful as you’d hoped. You really need to think about your org structure and what the future of your team should look like in this new AI-first world. It’s going to be totally new moving forward. It’s also important to look at things like your help content, processes, and workflows to understand if or how well they’re set up for AI. Once you’ve done some preparation in those areas, it’s an easier flip of the switch to turn AI on – and start seeing results.

Managing AI is going to be an ongoing journey with lots of iterations and optimizations along the way. Think about how you can lay the foundation now so you can continue to build on it in the future.

What is your vision for the future of AI in customer service?

The biggest thing for me is the new career growth paths that are going to come out of this. Customer service has always been stuck in a corner when it comes to growth. Growth within a team in the customer service space can be few and far between, unless there is movement from upper management. Ultimately that means really great associates who want career growth have to leave to go somewhere else to fulfill that. AI is giving us the opportunity to keep that talent in house – creating new career paths and opening up roles that will lead to a really strong and varied set of skills on support teams.

I’m also excited to explore how we can further integrate Intercom’s AI features into our processes – not just for customer interactions but for backend workflows as well. Customer-facing features like being able to tailor Fin’s tone of voice to fit our brand’s unique personality are going to be huge for maintaining a personal connection with our customers. And on the backend, having Fin actually take action on things for us is going to mean that even less conversations need to reach our associates. That’s incredibly exciting to me.