Content Guru has had a blistering three years of 30 per cent year-on-year growth and a headcount which has grown 42 per cent, just last year, to nearly 300. Martin Taylor, CEO, spoke to Comms Business to provide an update on the Storm platform and what has been behind this spectacular growth story.
Comms Business Magazine (CBM): Which segment of the market are you competing in?
Martin Taylor (MT): We tend to focus on large scale users, 1000+ seats, and are largely competing against the incumbent, on-premise type providers. That’s been interesting, and they have been well dug-in, but with the need for omni-channel and the need for organisations to offer a clean experience across all of those channels that has caught a lot of those old systems on the hop. Many of them can’t cope with demands of multi-session chat or social. The integration of these voice channels and written channels in a more integrated way and making it easier for the agent as well.
CBM: How are intelligent automation and deep integration driving transformation in the contact centre?
MT: Automation is where we came from. Before we did live agents we did IVR, we launched our first SMS based chat bot in 2011 for National Rail Enquiries on 84950, it’s still going strong and you can ask it anything to do with train routes/ times. That’s an area we have always been comfortable with and luckily that’s coming into vogue again particularly with the link to data sources.
AI technologies are driving more of a conversational interface now. We are seeing more of an automated front end, perhaps the identification and authentication part, and finding it out what the person wants. Then we might bring the human in and prompt them with the right information from the relevant data source. At the end of the conversation we might be writing it up automatically too.
Through links to data sources we are feeding the agents information during interactions which typically cuts out that 15-20% of time which they use to look things up.
For many of our customers the integration is the whole point of us being there. Take the NHS 111 service, no longer do callers get taken through a flow chart called Pathways. Before we even connect the call we are checking several different health and care information sources to see if we know anything about them. That might be long-term conditions, end of life care plans, things that might trigger an ambulance dispatch or a recommendation to go to the emergency department.
CBM: How has the role of human agents in the contact centre evolved?
MT: One of the things human agents don’t like is the repetitive nature of what do in the call centre, answering the same questions over and over again for example. We are actually asking agents to be a bit robotic in that sense which doesn’t always sit well with the human psyche. That is also part of what drives agent churn and dissatisfaction. There was a US survey a few years ago which only 16 per cent of contact centre agents declared themselves as satisfied. The number one source of this satisfaction is workload, what we are doing is addressing a lot of the low value jobs and verification processes. Once we remove that layer we are dealing with the more interesting stuff. It is also intrinsically more satisfying and varied.
Going forwards it means we will rely on agents for their human qualities. The machine will be doing the heavy lifting and looking things up and the agent’s job might be to empathise and provide a warm human face. This is all about improving the Customer Experience which will be the prime differentiator for organisations and their service offerings in the future.
CBM: What is the link between omni-channel and AI?
MT: I describe omni-channel as the gateway drug to AI. You need to have a technology base which is going to enable you to flip between the channels the consumer is going to use at the time they want to use them. If they come in on a phone call you need know that it was the same person which came through the chat the day before. It’s a much more tied together view of the customer and gives the AI more to work with. Ultimately, many businesses will use AI to interpret vast pools of unstructured data. Lots of companies have that data in the form of things like call recordings, but they aren’t really using it to gain insights in the way they could.