Four tips to ensure your AI innovation is a success

Many businesses still find themselves struggling with automation and AI – indeed leveraging these technologies can prove to be extremely challenging.

However the rewards for getting it right – a smoother and more effortless experience for customers, and more efficient and time-saving processes for your business – mean that it’s essential that you’re able to get your automation and AI projects on track.

Specific areas where AI can work well for CX operations are:

• Predicting customer intents – AI can track a customer’s journey across your website and then predict their intent based on what their behaviour indicates. AI can then route the customer to the contact option that best suits their needs – whether that’s a chatbot, text, voice, or live chat.
• Creating natural conversational experiences – automation enables new levels of service consistency by replicating the same high quality customer journeys for everyone.
• Pattern matching – customers matched to the most appropriate agent means that you’ll always have the right people interacting. By tracking customer and call types, AI can connect agents with the same types of interaction that they have supported previously.
• Improved listening – AI is great at ‘listening’ to conversations and augmenting the experience for agents by making smart suggestions about what to do next.

On the flipside, it’s important to avoid the most common automation and AI pitfalls: misunderstanding customer needs; focusing on technology rather than process optimisation; failing to gather company-wide support for your automation projects; and rushing in to large scale deployments too quickly.

To avoid these pitfalls and ensure AI and automation success, there are four critical actions you must adhere to:

Secure company-wide buy-in

Technology innovation needs the right conditions to flourish, and automation initiatives particularly require support from across the business – not just the C-Suite that initially approved the project. Buy-in has to be collective, with everyone aware of the potential benefits. Marketing teams and call centre managers will need to work together better, and the digital team will benefit from building awareness of how their actions impact the call centre.

For example, a digital team can often add new online contact options without consulting the call centre – leaving frontline staff left to manage increased and unscheduled demand. This level of cultural change can be challenging, but it’s our experience that your AI will end up a lot more human if you get all of your people involved.

Take small, iterative steps

When thinking of automation and AI, it’s tempting to focus on big deployments with the largest potential for cost savings – such as conversational AI. That makes sense, but you’re unlikely to successfully create something so complex straight away. That’s why it’s better to start small – for example by automating a single step in the customer journey and limiting it to 10% of all your calls.

At BGL Group, the company routed a percentage of live calls through its contact centre AI, and was able to capture customer intent and categorise their reasons for calling. Having access to this dataset allowed calls to be redirected to the right place, along with the creation of customer journeys that involved both voice and SMS.

Work at a smaller scale, prove things work – then carry on iterating until it all works on a bigger scale. It’s also important to know where to start, so use data to identify opportunities and build a solid feedback loop to help you drive the process on the back of data that you’ve already captured from customer responses. Test and learn as you go, and be ready to pivot as customer needs change.

Be process-first, not tech-first

Focusing less on tech and more on processes can make sure you succeed at automation and AI. Too many companies see AI technology as a magic bullet, but it’s how you use it that counts. You need to understand your customer journey and your processes, and learn how to optimise them.

When organisations have a better grasp of the end-to-end journey needed to fulfil a customer request, then they will be in a much better position to deploy a solution in order to optimise or automate it. Following this approach will help in terms of securing real value, however you will also need to invest in the people and knowledge to support flexible but regimented automation and AI rollout processes. This will reap long-term dividends, but it also requires a long-term view.

When M&S sought an AI-powered solution to improve the accuracy, efficiency and scalability of its contact routing, Sabio built a flexible and scalable solution that helped M&S to be proactive about trending customer concerns. This not only reduced call handling times by ten seconds, but also delivered an increased routing accuracy of 70%.

Understand how automation and AI will impact your people

There’s nothing artificial about the people who work alongside your automation and AI, indeed its applications don’t only impact your customers but also the people in your contact centres.

Done right, automation attempts can result in a leaner, more skilled group of agents – but it’s still really important to have ongoing oversight of how these changes are affecting your people. As you iterate and grow your automation capability, the overall call volume for agents should drop. However, agents will be left to support your customers through longer and more demanding conversations.

That’s why automation and AI also needs to reach inwards towards the contact centre, using the same powerful technology to support your agents with their more complex workloads.