Josh Comrie is the Co-Founder & CEO of Ambit, a company that helps enterprises scale their customer support operations with a conversational AI platform designed to solve real-world problems.
In this interview, Mr. Comrie shares insights on how enterprises can start their conversational AI strategies by identifying the pain points in their business processes and interact with their customers using virtual agents and chatbots.
What is your background and how was Ambit started?
I have a background in technology services, having started and exited three companies in this space. Alongside this I have created and run a fund for investing in early stage ventures, this numbers 26 investments and 3 exits so far. After my last exit and some time out, I formed a (potential) founders group. We looked at 2 things: emerging tech at the start of the hype cycle – that would make a meaningful impact upon the world (IOT, Blockchain and AI were in our consideration set). Then we looked for real world problems that could be resolved through the application of the technology. We landed on AI solving the CX pain point; for organizations and individuals: this is largely broken. Businesses have marginalized the experience and treat it as a cost centre pain point, so as customers we feel this. We struggle to find timely and accurate solutions to our problems. This thinking evolved into Ambit as a conversation platform.
What is Ambit‘s mission?
Any channel, all contexts and situations, we capture the content, sentiment and intention of those conversations. This enables organizations to make well informed product, service and pricing decisions to serve their customers better.
Walk us through Ambit’s products, and what problems they solve.
It is a single console solution for the design, build, analysis, integration and training of conversation agents. Voice, text and digital avatars are able to be designed by business users in days, integrated with the data source and developed through machine learning. As a platform, we have delivered to many use cases to most industries.
What are the biggest challenges that you are currently facing at Ambit?
Like any scale-up, we face the perennial resource application question: In which part of the business should we direct resources and in what cadence. As we scale internationally we’re endeavoring to build success through partnerships as opposed to a large global salesforce. This is a key ongoing challenge.
Ultimately, our customers’ success is ours; if they can achieve a revenue uplift or reduction in the costs to serve in the area we apply our solution, we have succeeded.
How do you measure the performance of your products?
We measure a multitude of metrics: time on chat, funnels and milestones, and completed vs incomplete chats. Ultimately, our customers’ success is ours; if they can achieve a revenue uplift or reduction in the costs to serve in the area we apply our solution, we have succeeded.
Tell us about the Ambit team.
We number around 30 people, 3 of us in Sydney, the remaining in Auckland, New Zealand. We have a founding team of 3: I am an entrepreneur for most of my career, plus an investor and advisor. My partners are a skilled technology executive as CTO and a financial services exec as COO. Our team is around 50% engineers, a mix of full stack, front end, data scientists and machine learning. The remaining half is split between Marketing/Sales and Customer Success.
What are the main business use cases of chatbots?
We have delivered to IT Support, HR Knowledge Support, Customer Acquisition, and Support and Contact Centre support. Our main focus is in alleviating the 80% of (repetitive) queries that would otherwise land in the contact centre, before they reach a human, across text, voice or avatar.
Once the bot is live, evolve it fast through listening and observing what your customers want from it. Build, test, learn and iterate: constantly.
How can enterprises get started with their conversational ai strategy?
Well, the key is getting started. Start with the overlap of something that delivers business value (strategic alignment) and where customers experience pain. This varies across business and industry but is always simple lower level queries relating to support or onboarding. Pick a vendor with experience! Buy, don’t build. Be clear on what your hypothesis and problem to resolve is when investing. Then, change the behavior of your customers by incentivizing them or making it more difficult to use the traditional channels. Once the bot is live, evolve it fast through listening and observing what your customers want from it. Build, test, learn and iterate: constantly.
What are the biggest opportunities for enterprises to leverage Conversational AI?
At this point, Conversational AI is really effective at solving the relatively simple and repetitive issues that relate to account initiation, servicing and delivery. So, the start is really about understanding where your customers are experiencing most difficulties, then overlaying the time spent in resolution by customer service. The intersection of these two provides a starting point, then work upwards from there.
Which Conversational AI-related technology trend do you think will have the biggest impact in your industry in the coming years?
The combination of predictive analytics, integration with key data sources (effective CRM) and omnichannel servicing. In other words, being able to know your customers intimately, service them when, where and how they want, seamlessly, through great technology and design. Once the industry nails this, we win the hearts and minds of customers.