Alexa - How Can I Use Conversational AI to Create Better Customer Experiences

While speech recognition tools have been in existence for decades (the first made available to consumers was Dragon Dictate in 1990), it’s safe to say that voice has finally arrived in the mainstream. In Australia, we’ve already seen a 57% adoption rate of voice assistants in the last year (iProspect, 2019), while in the US, which is leading the market, recent findings from Edison Research suggest at least 22% are using voice assistants to make regular purchases.

As with most trends, demand for voice has been consumer-led and many brands are being left behind in the race to accommodate the need for voice interfaces. Only recently, major brands such as Woolworths and National Australia Bank's digital bank, UBank, revealed their commitments to making conversational AI - technologies that enable computers to simulate real conversations - a priority. This lag is set to change soon, however, with Gartner research suggesting that by 2022, 70% of enterprises will be experimenting with conversational platforms for consumer and enterprise use.

At Switch, we’ve been working closely with clients to help incorporate conversational AI into their customer experiences. For any organisation looking to implement a voice strategy, there should be two key considerations - firstly, a strong use case and, secondly, a flexible and omnichannel conversational AI technology.

Find a strong use case

As customer experiences and interactions have become increasingly digitised, there has been an increased awareness of just how much time we’re spending looking at screens or typing as a main method of inputting details. With both Google and Apple recently releasing tools to help users manage the amount of time spent looking at their mobile devices (Google has called its app ‘Digital Wellbeing’), the most successful use cases for conversational AI appear to be those that can free users of screen time or provide a clear convenience. iProspect’s research revealed that the top drivers for voice assistant usage were tied to convenience, with 55% of respondents citing ‘Voice interactions free up my hands and allow me to multi task’.

Some naturally well-suited use cases for voice include retail, ecommerce, customer service and business-to-business education; but start simple and think about the existing touchpoints in your customer journey that could be made more hands-free by a conversational AI tool.

Finding the right provider

Conversational AI isn’t optional - it is something that your customers, regardless of the size of your business or your industry, will come to expect in the not-so-distant future. At Switch, we’ve recently partnered with one of the leading conversational AI providers, Cognigy, in order to ensure that our clients can implement voice interfaces that provide the most seamless and flexible customer interactions.

Recently named a Cool Vendor in Gartner's Cool Vendor Report in ‘AI for Conversational Platforms’, Cognigy’s solution enables businesses to build advanced conversational AIs within minutes, rather than days, and can be fully integrated with leading CX management platforms, such as Sitecore, to easily manage content and create natural, up to date dialogue flows. To see how Cognigy works with Sitecore, watch this short video tutorial.

Getting Started with Conversational AI

Here at Switch, we start any conversational AI project with the following:

• Proof of concept and use cases - the best examples of voice and chatbots are those that provide a real convenience for customers, so ensure that any projects look to make an improvement in the customer journey, no matter how small.
• Technical architecture and integration requirements - evaluate your existing tech stack and which conversations will be managed through dialog and which are data source queries.
• Interfaces for conversations - What would work best to ensure a seamless and easy to manage customer dialog across multiple user preferred interface.
• Workshop use cases - test how your chosen use cases would work for customers and get real customer feedback.
• Working dialog - testing the dialog to ensure that it flows for the optimal output to service your customer.
• Functionality roadmap - as with all digital transformation projects, aim to constantly improve and build upon the first phase launch. Think about other areas for improvement in the customer journey and work to build upon existing conversations (for example, in solutions such as Cognigy, this might mean personalising conversations or working to make dialogue flows deeper and more complex over time).

Ultimately, all signs suggest that conversational AI is only going to get bigger and for brands that aren’t already considering how they can offer this service to customers, the clock is ticking. If you’re considering implementing a conversational AI strategy, get in touch with our team to find out how to get started today.

— Nick Jones