People often say that they don’t like automated systems. What they usually mean is that they don’t like automated systems that don’t provide a good service. The systems we do like, such as cash machines, are simple and perform a specific task, and we probably no longer think of these as automated systems in the same sense as modern service automation.
However, customer service can often be much more complex than these simple systems. But when you use automation, along with artificial intelligence (AI), correctly it can be a substantial differentiator for a business.
The pandemic accelerated digital transformation at a pace never seen before. The early stages of lockdown, with the need to enforce social distancing or send contact centre employees home, led to long call wait times for many consumers. When digital became the default, many organizations realized that their self-service experiences weren’t up to scratch.
The need to cope with increased levels of demand with reduced levels of agents available has meant that organisations have been forced to look at how they can automate both for efficiency and to maintain the customer experience.
Building the case
When building the business case you should prioritise the KPIs that matter most to executive decision-makers and wherever possible attach these to a financial value. For example, what would the financial impact be if assisted service could deliver the right content at the right time to your agents so that the average case handle time decreases by 20%? What would your average cost per contact look like if you could enable self-service for an additional 30% of inbound calls using conversational service automation? How much agent time could you save by handling 50% of your webchats using Intelligent Virtual Assistants?
'Excellent Customer Experience' is a great aim for any project, but definitive benefits such as 'reducing overall agent time by 30% by using chatbots and speech assistants’ are needed to sell the idea of service automation to key stakeholders.
So below we have listed the areas we think you should cover - include specific numbers wherever you can.
Reduce Costs and Increase Operational Efficiency
Reduction in volume of live chat requests that can now be handled by AI chatbots and increase in telephony self-service using conversational AI / natural language IVR.
A large number of simple queries can be answered by chatbots or speech assistants. IBM estimate that chatbots can answer 80% of standard questions. Even with more complex questions and tasks we have deployed recent projects that have demonstrated a 43% reduction in live chat requests.
For webchat queries that can be handled solely by AI chatbots agent Average Handle Time for webchat is reduced to zero agent hours.
For those calls that still require an agent our recent projects have seen a reduction of 90 secs in the average live chat time.
Voice biometrics allows chatbots to initially identify and verify (ID&V) a caller, saving an agent an additional 40 seconds per call.
AI powered Assisted Service for Agents can reduce the average handle time per call by suggesting best-next-action or pulling up relevant information from the knowledge base. This reduces the need for screen switching and streamlines the call. This can also increase First Call Resolution (FCR).
Using Robotic Process Automation (RPA) to update multiple systems after customer conversations saves agent time switching between screens during the call and reduces call wrap-up times post call.
Intelligent Call Routing enables AI-powered decisions based on the caller identity, customer journey and data already gathered via chatbot or IVR so the call can be routed to the agent best suited to resolve the issue.
Chatbots can be used to manage times of excessive demand, peak times, staff sickness or out of hours requests, providing back up to live agents when they are not able to deal with call levels.
This table from Contact Babel Inner Circle Guide to AI, Chatbots and Machine Learning demonstrates the average comparative costs for responses via different channels:
Increased customer satisfaction means higher retention rates. According to Invesp, improving customer retention rates by just 5% can increase profits by between 25% and 95%. Using the average Life Time Value (LTV) of a customer you can model the impact that even small percentage increase in retention would have.
Assisted Service can use AI to suggest relevant cross-sell or upsell options to the customer or to the live agent while on the phone.
As we said at the beginning we need hard numbers in any business case, but we should not forget the more qualitative benefits that automated customer service can bring:
Improve the Customer Experience
First contact resolution (FCR) and a short wait time for a response are the top two most important criteria for customers showing that increasing FCR through self-service and reducing handle times contribute strongly to the overall customer experience.
Gartner research shows that AI drastically reduced customer wait times, with chatbots replying within five seconds of customer contact, while typical advisors took 51 seconds. Our own recent projects have shown a 26% increase in user engagement after only 3 months.
Happy customers are advocates for a business and help to build your brand.
Improve the Employee Experience
Agents will spend less time on mundane calls and repetitive tasks, allowing them to focus on more valuable calls, revenue-generating projects or where customer empathy may be required. This aids with staff retention and future recruitment.
But you don’t have to take an all or nothing approach. In fact, we recommend you make decisions with the long term in mind but start with small projects. If you are undertaking large contact centre system upgrades or already have an existing estate, we recommend you start with a small self-contained project for a clearly defined business issue or process. This could be a pilot to automate the answering of phone calls, respond to web enquiries or handle social channels.
You also don't need a huge, specially trained IT department. The right platform empowers business users to design your interfaces and workflows with a simple No-Code GUI. Then build a roadmap of linked businesses cases that map out a long-term vision for the strategic use of AI across all customer-facing parts of the organization. A low-code portal enables your in-house IT team to manage integrations with little or no external assistance.
If you are ready to start your customer service automation journey, but need help to quantify the benefits, contact us or call us on 0333 6000 360 and we can help you build a business case and get your project moving.