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How automation can increase contact centre efficiency and customer satisfaction

Automation can help contact centres improve their customer engagement, analytics and backend processes. In doing so, increase customer satisfaction and efficiency, create happier employees and discover new revenue opportunities.

However, automation needs to be integrated wisely into a contact centre’s processes as automation for its own sake may lead to lessening the value human interaction and experience can contribute. For example, when using virtual assistants, it is necessary to know when to handover to a live agent so that sales opportunities are not missed. In other words, best practice needs to balance service goals with automation if customer service and operational efficiency are to be maximised.

In this blog, we look at the areas of customer engagement, analytics, and administration to examine how they can be improved with automation and how you can select the right technology.

Customer Engagement

Automation in the form of virtual assistants, whether it is voice or chat or both, is a key part of driving efficiency and improved customer satisfaction in your direct customer contact. They enable better outcomes by giving customers the option to make payments or resolve problems faster, and at a time convenient to them. For example, a chatbot can answer questions 24/7 and their ability to answer potentially unlimited amounts of calls at the same time reduce queues, allow your customers to get an answer immediately and improve customer satisfaction.

Chatbots can solve simple things like FAQs, but if a bot with natural language processing is implemented, it can have near-natural conversations with your customers, making it possible to handle much more complex enquiries and contribute significantly to customer engagement.

Virtual assistants also enable your organisation to revolutionise its KPIs. Understandably when all conversations are being handled manually, metrics like calls per hour and average handle time are important to keep down costs. A bot significantly reduces those costs as it can handle more calls per hour. The result is that your business can focus on the customer journey and metrics like customer satisfaction and first contact resolution.

Choosing the right virtual assistant technology

As your customers interact with your business over multiple channels, it is therefore important that any natural language AI can handle both voice and message-based conversations – as well as work effectively over not just the Internet, but telephone channels.

A virtual assistant should also offer not just language-based communication but visual and point-and-click UI elements to make human-machine interaction much more convenient.

In addition, the functionality of a natural language bot doesn’t have to be limited to agent conversations, it can be integrated into an IVR to help improve dropout rates, compared to the clunky tree-like navigation of IVRs. It can be used for outbound as well as inbound communications - if you have a solution that works over the telephone line, a bot can be used to prequalify candidates, conduct surveys, and get other customer feedback, before passing over to the agent.

Remote Visual Assistance

Contact centre agents have traditionally had to resolve problems and help customers through the medium of voice and asking questions. For example: ‘Is the cable fully attached to the green socket?’ Remote visual assistance is a unique tool that is driving increased customer satisfaction and improved first call resolution numbers by arming agents with the ability to get ‘eyes on a problem.’

With remote visual assistance, an agent can take over the camera of the customer’s smartphone and then guide the customer to resolve the problem by using augmented reality to annotate on the screen. Remote visual assistance is proven to reduce call outs and, when call outs are necessary, ensure that the problem is solved by allowing the person onsite to involve experts back in the office.

Remote visual assistance can also be an excellent source of analytics as best practice of problem-solving is videoed and then used for training.

Interaction Analytics

The ability to carry out natural language processing is essential in helping assist agents in solving problems. Machine learning and AI combined with natural language processing allow businesses to listen to call recordings to analyse 100% of conversations – instead of just a small percentage through surveys – and identify patterns in interactions that would not previously have been possible. This kind of analytics, interaction analytics, can then be used to proactively monitor conversations; sentiment indicators and alerts for signs that the conversation isn’t going in the right way can be set up, allowing supervisors to get the conversation back on track and ensure net promoter scores and sales opportunities are met.

Interaction analytics can be used across all your digital channels and empower your agents with the right information at the right time, so they can resolve customers' issues rapidly and offer solutions based on personalized, predictive insights.

Backend Processes and Administration

While automation is incredibly important for helping customers and agents, the ability to drive efficiencies by enabling backend processes is an equally crucial part of the puzzle. Being able to pass post-call updates and fulfilment activities to bots leaves your agents with more time to spend on customers.

Good examples of proactive communication include sending:

• Confirmations of changes in order statuses

• Information requests

• Appointment reminders

• Payment notifications

Omnichannel

Even when you have an omnichannel solution and customer record, if you have to fill out the details manually for messages across each of your key communication channels then it will not be very efficient. Best-in-class implementations enable seamless switching between channels and the capacity to write a message once and schedule it to go out automatically across multiple channels, adapted for each one.

ACW

Through monitoring the processes that advisors follow and the systems that they dip into, bots can record an advisor’s digital footprints during a call. They can then auto-complete much of the ACW form, generating an automated summary of the contact.

Conclusion

With careful planning and the choice of the right technology, including chatbots, remote visual assistance and interaction analytics, it is possible to automate many of your processes and still keep the benefits that your human agents bring.



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