How Pockit reduced its email backlog by 95% in just two months

Highlights

• Pockit’s support team receives 1,000 emails a day
• In 2021, the support team had accumulated a backlog that was affecting handling and resolution times
• With Ultimate's support, 95% of the backlog was cleared within just two months
• Handling times have dropped from several weeks to under 48 hours
• Pockit now automates 12,000 emails a month, using 37 intents

The Customer: Easily accessible financial services for over 500,000 customers in the UK

Pockit is a UK fintech company that offers a range of no-frills, easily-accessible digital financial services, including prepaid spending cards, current accounts, and a mobile-first service. Launched in 2014, Pockit had gained over 500,000 customers by 2020.

In the fintech industry, accessibility is key. But when Pockit reached out to Ultimate, its team of 35 support agents was having a hard time handling the 1,000 emails they were receiving daily.

The Situation: An email backlog that drove up handling times

When Jamie Hopper joined Pockit’s newly formed Customer Support team in 2021, the company had just moved from London to Newcastle and recruited an entirely new team. Hopper’s first task? Tackling a 17,000 email backlog, the fallout from a forced two-month hiatus on all transactions due to complications with a third-party supplier.

The Solution: Ticket automation turns weeks into days

Pockit chose Ultimate based on its unparalleled onboarding process and proven track record of integrating with Zendesk Support.

Throughout the onboarding process, Ultimate’s customer success team ran regular training sessions, updates, and check-ins.

The Success: 12,000 email tickets automated per month

Soon, Hopper and his team were able to automate 12,000 emails a month using ticket automation. They also leveraged Ultimate’s Zendesk integration to identify, refine, and prioritize the most frequent and significant customer intents, scaling up to 37 from only four.

Overall, Ultimate’s automated solutions produced 3.5 times more output than a human agent while implementation costs remained below one monthly salary.