This is part one of a five-part blog post looking at how AI, speech analytics and conversational computing are changing the processes, efficiency and CX / C-Sat metrics within many organizations around the world.
- Part two covers the topic of whether humans can keep up in a big data, real-time digital world.
- Part three covers the “real needs” within omnichannel and real-time data strategies.
- Part four covers how these speech technologies are helping to transform sales and service functions and leadership.
- Part five concludes on the future vision for speech analytics and conversational computing.
So, it is clear that many organizations think they have finally made the big leap and now consider themselves to be a digital company.
Of course, we have made massive strides in just the past few years. I love my mobile banking app, the various collaboration and communication services I use are truly incredible, and the data that is now available to me at work via so many sources is mind-boggling.
That is me as a consumer, an employee, a leader and a citizen. I like it. Much of the time I don’t want to talk to anyone, I just want information, make a transaction or change a setting. If I can do this simply and easily myself, I’m all in!
The upside is that I am empowered, the service, change or transaction is controlled and secure and I can get reports on what I have done, changed, spent etc, as it is a digital record. It is black and white – there is little or no scope for grey – it is digital.
The companies or organizations that provide these services – whether through a mobile app, an AI chatbot, website, web form or an IVR service – glean masses of information and intelligence. This can be about location, product, $$$, click-stream, time on site, purchase trends and so on. Fundamentally, I am digitally connected to the company.
Now, let us consider that not all interactions are via apps, websites or IVR. On average, 60 per cent of consumer interaction is via voice and video. Naturally, this varies from industry to industry or service to service and there are also different mixes for inbound calls versus outbound calls. However, any way that you cut it, it is still a lot of calls.
This is amplified “when the call matters”. This could be a service emergency, escalation, complaint or need to buy and need for specialist advice. With these scenarios, call rates jump to more than 83 per cent.
Now this is where the “digitalness” of an organization starts to waiver. If I feel the need to call my bank, it is not because I want to transfer some money, pay a bill or buy some stock. I can do all of that. No, it is because I need an advisory service: I need some advice; something is not working; or I am angry. All of these situations are “moments that matter’”. Whether my interactions are positive moments or neutral moments or negative moments, I believe I am a tier-one customer to my bank. If I am calling, I expect them to react and, on the whole, they do.
In many cases banks use speech analytics, AI and conversational computing to complete the “digital signature” of customer interactions. But many sales, service and support organizations are not doing this yet. This is where the competitive battleground is emerging and research organizations such as Gartner, Forrester and 451 Research are forecasting a significant growth in AI technologies that assist the human, rather than replace the human. Banks have had a strong track record of leading the field in technology advancement. They lead (with their big budgets) and the rest follow once pricing normalizes.
So, what have they been doing that other industries should learn from?
Well, many financial services organizations (for compliance, efficiency, sales or CX reasons) recognized that the call center agents are only human. The first break in the digital signature of a customer is the fact that the agent may not have understood the request or question. Or worse, they did not want to understand the question or request as it is too complex to deal with. The second break point is that the agent then has to enter the request into the keyboard. This is prone to errors, and susceptible to fatigue and “gaming the system”. Ultimately, the top 20 per cent of agents do a great job. They are skilled, diligent and professional. The middle 60 per cent are OK, and the bottom 20 per cent are rogue.
The overall digital signature from this data input point is very poor, and this is what many organizations, especially in Financial Services, have been using AI and speech technology to resolve. This gives them a significantly better digital picture as calls can be transcribed into the system. All questions or actions can be captured via speech to text, analyzed for understanding, sentiment, technique, key words and topics. In short, it offers digital insight into the conversation, not via the agent’s keyboard, but via the conversation itself – no gaps, no gaming, just great data.
The next chapters investigate what we can do with this data, now we have it.
See you at the next blog.