Automation and AI in Customer Communication

What’s the Difference Between Automation and AI?

First, it’d be useful to establish the difference between the two terms because whilst they’re often used interchangeably, they’re actually very different.  Automation is the scheduled carrying out of a task by a non-human entity (generally a piece of software code for customer communication) based on pre-set parameters. A great example of automation is Facebook quick replies. A customer can contact your brand and choose their question from a pre-designed list, and then receive the relevant pre-written answer. There’s no learning or judgement call made here, just a simple “if this, then that” style process. AI, however, is much more complex.

Generally speaking, there are two types of AI: artificial intelligence and augmented intelligence. Rather than go down the minefield of deeply technical definitions, in this article when we use the term “AI”, we’re referring to a technology which uses its own learning and experience to improve its output.    

A good example here is a sentiment analysis tool. In Gnatta, we use tools like this to give you real–time insight into your customer’s perception of you. The tool does this by constantly learning to recognise sentiment in an ever-greater vocabulary, and therefore increasing both its range and its accuracy. This is separate from automation as there’s no human manually entering that “bad service” is a negative term; the intelligence deciphers it on its own.   

Whilst it’s easy to get the technologies confused, this fundamental difference of self-improvement is what separates AI from automation and gives it the much greater potential when it comes to creating new processes and unlocking additional value. But that doesn’t mean it’s not worth taking a step back and appreciating automation in detail. 

The Uses of Automation

Yet, despite automation playing a part in our daily lives, it’s still the most underrated tool available for customer care. At Gnatta, we believe the first step towards a great customer journey is all about getting a system in place to handle everything a human advisor shouldn’t be involved with

For example, historically (and all too often, even now), advisors would need to: 

• manually select an interaction to work on, having to decide which was the best to prioritise at that time; 
• gather data and go through data protection with customers using the same stock questions every time; 
• and manage follow–ups with departments and keep customers up to date on more detailed queries which couldn’t be resolved at first touch. 

Every one of these tasks can be done easily, and more accurately, by a workflow system working on pre-set conditions. Taking the first instance around assignation, for example, a machine can make a quicker and more accurate decision on which is the highest priority contact taking wait time, subject, the customer, and more into account.

What About AI?

Automation may have been around a long time, but the same is true of AI. Leading experiments such as Deep Blue from IBM began in the 1980’s, and it defeated chess grandmaster Gary Kasparov for the first time in 1997.    

But these are more marketing and testing experiments. The real change in AI has been the huge increases in accessibility in the last 10 years.   

The impact of AI on the customer journey has been huge, from bots handling queries through to sentiment and language analysis to provide greater real–time insight. However, it’s important to take that step back before getting the AI bug, and realising the use cases for the technology are generally still at early stages – and that customers still value human interaction.   

With that in mind, whilst exploring the benefits of a new bot or adding in sentiment analysis is certainly a good idea, it’s important not to let the AI chatter distract from the importance of making sure you’re as automated as possible.  

Getting Started

As with everything, the key when it comes to making the most of both automation and AI is starting right. Whilst both can be daunting due to the sheer scale of opportunity available, there are three quick tips that will get you up and running quickly: 

• Find the right partner.

  A supplier who has experience in providing solutions utilising automation and AI in your industry will not only cut down the lead time to launch but will also be able to use that industry experience to highlight priority areas to get going with.

• Fix the easy things first.

  When you begin on this journey, it may be tempting to dive straight into a world of bots and new management insight; but the greatest value may come from getting dynamic service level agreements set up. Fundamentals still matter and deliver the greatest success.

• Iterate. 

  When it comes to the customer journey, gradual change is better than a wholesale change. Find the pain points using customer data and focus on fixing them systematically. Again, the right partner will make this so much easier by helping develop a plan of action.

Hopefully this blog has helped present some of the brilliant opportunities both automation and AI can create. If you’d like to get some personalised insight into how we can use our solutions to improve your customer communication, get in touch today.