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Customer service automation is nothing new, but very little has actually changed since the IVR was developed in the 1970s… until now.
We have now reached a point where speech recognition and conversational AI technologies are sophisticated enough to reliably handle customer queries, and the next 3-5 years will see this technology totally transform the contact center.
With that in mind, now is the time to build your business case for customer service automation.
In this post, we’ll take a look at some of the most important contact center metrics, and explore how using conversational AI for customer service will impact them.
Shrinkage, occupancy, adherence, utilisation: however you choose to measure agent efficiency, you can always expect some discrepancy between the amount of time your agents are at work and the amount of time they’re on calls.
Virtual assistants can reduce the impact of shrinkage and make workforce management calculations easier by reducing the overall agent minutes required to staff a call centre.
Using AI to handle repetitive tasks frees up your agents to spend the time they do have on more complex and valuable conversations.
Removing mundane, repetitive work is likely to impact your staff retention too, creating space for your agents to do what they do best – having high value conversations with your customers.
Abandon Rate. The percentage of inbound calls that are abandoned by the customer before they reach an agent can be massively reduced using conversational AI.
Where IVRs have traditionally been used to route callers to the right department, they can be incredibly frustrating, so it’s no wonder when customers give up and try more public channels like social media, where businesses can be publicly held accountable for the level of service they offer.
As conversational AI technology is infinitely scalable, virtual assistants are able to answer all calls immediately. Because they understand what customers mean, regardless of the way they word queries, virtual assistants can route calls directly to the right department without sending customers through complex multiple choice IVR flows. What’s more, virtual assistants can take specific details from customers, including a description of their issue, and share these with agents via computer-telephony integration.
Average Handling Time. Because customers can get straight to the point, and express themselves in their own words without being forced through IVRs, contact centers using virtual assistants can expect a significant reduction in average handling time.
But it’s not all about call routing. Using AI to handle repetitive tasks – taking details like addresses and reference numbers, or taking customers through step-by-step troubleshooting processes – will free up a significant amount of time for your agents, time that can be reinvested in more valuable, empathy-requiring and complex conversations.
After-Call Work. Depending on your technology and processes, your agents may be spending a not insignificant amount of time on after-call admin such as completing ticket details. AI can take care of this admin as the call is happening, completing ticket details and tagging relevant information as its given, reducing the amount of after-call work required from agents, and logging accurate tickets quickly.
Average Call Waiting & Service Level. It’s typical for contact centres to aim to answer 80% of their calls in 20 seconds. Virtual assistants can answer 100% of calls immediately, completely removing the pressure of this metric from all contact center staff, and providing instant support to customers, whenever they want it.
First Call Resolution. Allowing AI technology to route queries directly to the right department will increase the likelihood that calls are handled effectively first time.
The data obtained by virtual assistants will help to accurately identify which types of customer queries often require more than one call for full resolution, which in turn will inform contact centers of how best to optimise their processes. Virtual assistants can quickly be retrained to handle situations differently should process improvements be deployed.
Misrouted calls – where a caller connects with the wrong agent – are costly for contact centers and frustrating for customers. Misrouted calls – which typically occur as a result of poorly designed IVR systems – can cost upwards of one minute of an agent’s time for each misrouted call.
Because virtual assistants can understand natural language, they can replace IVRs entirely, allowing customers to explain their reason for calling in their own words, and using this detailed description to forward the call directly to the right department.
Using virtual assistants, you can unlock accurate data on the metrics discussed above. But it isn’t only your contact center operations that will benefit.
Restaurants using virtual assistants to handle bookings can expect insights into optimal table configuration. Ecommerce companies can learn about return operations. Travel companies can learn about demand patterns. Energy and communications providers can better understand engineer demand.
Whatever your business, there are plenty of insights to be gained directly from customers, insights which are currently being skimmed over by overworked and underprepared customer service agents.
Pushing your team to upsell or cross-sell can be a struggle, and can end up annoying customers who are fed up of being treated like cash cows. But AI can intelligently identify moments in conversations where an upsell or cross-sell could be advantageous to both the business and the customer.
For example, imagine a customer contacting an airline with questions about checking in. AI agents can scan the customer’s booking information and look for opportunities to improve the customer’s experience, such as offering additional baggage where there is a long period of time between outbound and inbound flights, or offering reserved seating for people travelling in groups. Conversely, where the customer is travelling solo, taking a short flight, returning in a couple of days, for example, the virtual assistant can skip the upsell, knowing that it is highly unlikely that the customer will wish to upgrade.
Virtual assistants are designed to replicate your very best customer service agents, and while applications vary wildly depending on business goals, there are hundreds of opportunities to use conversational AI technology to reduce operational expenditure, streamline your customer service operations, create additional revenue and provide outstanding customer support.