Farewell to the customer service Frankenstack

You’ve probably met the Frankenstack – a friendly monster made with the best of intentions and from a concoction of different support software and tools.

I talked about Frankenstacks recently on The Ticket podcast with our VP of Customer Support, Declan Ivory, and our Director of Human Support, Bobby Stapleton. I wanted to clarify one thing: my issue with Dr. Frankenstein’s monster is not that he’s assembled from different components. It’s that he’s ugly (or put more politely, his individual parts don’t work seamlessly together).

In real terms, it’s not that I believe a single tool will do everything for your customer service team. It’s that the experience using these tech stacks is clunky, inefficient, and suboptimal, and we’ve tolerated it for a bit too long. With recent advances in AI-powered customer service, support teams don’t need to put up with disconnected tools anymore.

How did the Frankenstack emerge?

Much like Frankenstein, these ugly tech stacks don’t appear overnight – they sneak up on you. If you’ve worked in a customer service team, you probably know what it’s like to be viewed as a “cost center” with an unrelenting focus on response times and reducing spend. This doesn’t leave a lot of time or money to invest in corralling our tech.

On the one hand, hundreds of great tools emerged in the last decade to solve niche, but important, problems – and I’m grateful for them. That said, getting all of them to work harmoniously together is a huge lift. Pair this with limited bandwidth and:

• New tools are bolted on to existing support systems and end up requiring extra steps, logins, and another UI to learn. This inflates how long it takes to troubleshoot and makes your support team less efficient.
• Duplicative toolsets emerge and end up being underutilized, leaving your team with 2-3x the cost with little ROI (return on investment) to show for it.
• Your backlog of user feedback gets bigger and your team becomes more and more dissatisfied, impacting your team and customer experience.

What’s the solution? Rally your tech behind one platform and let AI fill in the gaps

1. Switch to an AI-first platform

First, migrate to a platform that makes it easy for you to streamline your tech stack – one that integrates with your tech easily but has its own core AI features. Here are just two of the ways we do this on our own team at Intercom:

• Our AI chatbot, Fin, works with our Messenger, learns from our Help Center, and has its own reporting for us to monitor performance – all in Intercom. This makes testing and improving our bot quality 10x easier.
• We use Intercom’s integration with Unbabel to help our team help customers in other languages. Fin can also provide multilingual support to customers in 45 languages.

2. Use AI to increase efficiency and improve the customer experience

Next, find and use AI features to save time and money without compromising the customer experience. Here are two recent examples of how we did this – and continue to do – this at Intercom:

• We used AI to analyze 500,000 conversations and help us understand key trends across our customers’ issues and questions. Imagine reading these manually.
• When handing things off in an escalation, our team uses Intercom’s Fin AI Summarize feature so that the next rep easily understands what’s going on – this is especially useful for long conversations.

Imagine a world where your tech stack saves your team money, features and tools work seamlessly together, and your team has more time to create white-glove customer experiences. We’re building that future at Intercom. 😉