My takeaways from Enterprise Connect in Orlando

Author: Simon Black | Date: 31/03/2023

I’ve just arrived home after a few days attending Enterprise Connect in Orlando, Florida.

It was a good event. Busy room, thought provoking conversations, and a great setting.

It was also the first event I’ve been to since the launch of large language models, GPT4 and Bard. And understandably, they dominated a lot of conversations.

More on generative AI below, but the other key themes that came out of the event were; audio clarity in the contact center is more important than ever, hiring is still a massive challenge, and people are struggling to balance their digitization efforts with what is best for the customer.

Read on if any of those themes resonate with you and get in touch if there is anything you’d like to discuss.

The importance of audio clarity

I was in Orlando with our partner, IRIS Audio. They kindly “put us up” on their stand so we could talk to people about our joint offering.

The thing that struck me most was how people in contact centres are so used to the noise that they are just willing to put up with it.

And it doesn’t have to be that way.

IRIS have a really compelling noise cancellation platform that eliminates background noise in the contact center. This is really important for:

  • Having a clear customer dialogue
  • Transcription quality
  • Post-interaction analytics and quality assurance

Given 50% of contact centers in the US are still using mono audio (vs. stereo) it becomes even more important to use a noise cancellation tool that can isolate the different voices in the conversation.

This boosts analytics and quality assurance performance dramatically, that on its own can sometimes struggle with mono audio.

Hiring agents still a challenge

I’m not sure this one is going away any time soon.

Since the pandemic, contact centers have found it harder to recruit and retain agents.

They’re having to do a lot more with less.

We support our clients efforts to hire and retain agents in a number of ways:

  • Reduction in training – Our technology acts as “over-layer” for agents so they need to learn a single process, not the multiple customer systems and processes that sit behind. This makes it easier for them to get up to speed.
  • Automating repetitive tasks – our technology guides with the next-best-action and automates repetitive tasks, such as accessing systems – making finding the right information easier and the working day better for agents and customers
  • Cost-saving efficiencies – by working from a single, unified desktop, agents aren’t wasting any time on calls, which means those interactions can be resolved quicker, more calls can be answered and money can be saved
  • Improving customer satisfaction – as a follow on to the point above, if customers are put on hold less, and reach a resolution quicker, then invariably they will be more satisfied with the service they have received

How digital is too digital?

It was clear at Enterprise Connect that organisations are still grappling with their digitization efforts.

What is the right level of digitization? How to stop digital becoming a barrier for their non-tech savvy customers? How will generative AI change things?

Awaken has a very clear view that humans are and will be critical to customer service delivery in the years to come.

As research continues to indicate customers desiring more human service interactions (due to lack of trust for digital channels) placing more digital barriers in their way will simply cause frustration and annoyance.

Better then to think through your customer use cases in detail.

What easy, transactional processes can be handled digitally or through a bot? Which scenarios require the empathy, knowledge, and perseverance of a human.

And then. How do we empower that human to be the very best version of themselves for the customer?

Large Language Models

Firstly, we’re crafting an article all about generative AI in the contact center right now, so look out for that in the coming weeks.

The release of large language models, GPT4 and Bard, were the talk of the town in Orlando.

Mainly due to the speed of technology advancement and the hype associated with the rate of change.

We’re busy looking at the best uses for generative AI in the contact center, and in the same way we advise our clients to think through their customer use cases in detail, we’re digging deep to make sure any implementation does the following:

  • Saves agents time and effort
  • Improves the customer experience
  • Increases insights for operational teams

And yet, something I’ve noticed is a lack of discussion around the data security / customer privacy of using these public-hosted, large language models.

The owners of the models themselves stipulate that the tools cannot be used for, “activity that violates people’s privacy”.

So, questions to ask yourself if you are talking to a technology vendor that has plugged in a large language model:

  • What data will we be feeding the model?
  • Does that data contain sensitive customer information?
  • Where is that data going in the public cloud?
  • Will I be in violation of data privacy agreements with my customers?

I may sound serious, but I think there is a real area of concern here.

Speak to Awaken

If any of the themes I’ve raised today resonate, then please get in touch.

We’d love to discuss your contact center operations in more detail, where you can drive tangible efficiencies and service improvements.

We’ll also be at the Call & Contact Center Expo USA at the end of April – hope to see you there.