Balancing contact centre customer wait time and agent staffing: there’s a bot for that
Across all industries it is a common problem for contact centres – balancing customer wait time and agent staffing.
If it is not done right, contact centres might either staff too many agents, thus increasing operating costs, or too few agents, thus increasing customer wait time. This increased wait time translates to poor customer experience and even lost customers.
But what if you don’t have to sacrifice customer experience while reducing agent burden and thus operating costs at the same time? Advanced artificial intelligence (AI) and machine learning–driven conversational chatbots (virtual agents) could be the solution.
Chandra Reddy, solution advisor for the travel and hospitality industry at Amazon Web Services (AWS) shares a hypothetical customer example that proves that businesses can not just enjoy better customer experience, but also see a 94% cost savings worth more than USD3 million in three years.
Customer experience matters and is a vital component of any business offer
Every travel and hospitality enterprise wants to deliver a differentiated customer experience for their travellers and guests.
Mr Reddy considers a car rental organisation that has 1,500 contact centre agents who talk with their customers for an average of 6 hours a day, 20 days a month, thus amounting to 10.8 million minutes per month.
Now, let’s assume that 2% of the customer calls fall under the category of frequently asked questions (FAQ), such as: “I need my rental receipt”; “My flight was delayed, and I just arrived. It’s 1:00 a.m. where is my car?”; “How much time should I plan for to go from your rental centre to the airport?”; “I don’t have time to fill up the gas tank. Will I be charged?”; “I need to stay for 2 more days. How much will it cost me?”; or “How much does a car seat cost?”
A live agent doesn’t need to address such FAQ. Advanced artificial intelligence (AI) and machine learning-driven conversational chatbots (virtual agents) can automatically answer such FAQ in real time, without any customer wait time, thus improving the customer experience significantly.
Such virtual agents can communicate through multiple channels like voice, SMS, web chat, and WhatsApp, and even simultaneously across channels.
For example, when a customer of the car rental company asks for the latest travel receipt, the virtual agent has the flexibility to send it to an email address or phone number through a text message while continuing to serve the customer over voice for other questions.
Deflecting just a small percentage of requests provides significant operating cost savings
Mr Reddy says that by deflecting just 2% of calls to an automated chatbot you can achieve 97% operating cost savings. How this is achieved in this example is now explained in more detail.
A meagre 2% of 10.8 million minutes per month of call deflection to a chatbot translates to 216,000 minutes, or 3,600 hours. The benefit for the contact centre is that it reduces the total agent burden by 3,600 hours per month. This gives agents the ability to spend more time on more important questions, thus improving their productivity.
Assuming a very nominal USD25 per hour fully burdened (salary, bonus, overtime, benefits) labour cost, 3,600 hours per month translates to USD90,000 in savings per month. This means savings of USD1.08 million per year, or USD3.24 million in three years.
Of course, you need to factor the technology costs to deliver the chatbot to calculate net savings. Amazon Web Services (AWS) offers Amazon Lex, a fully managed AI service with advanced natural language models to design, build, test, and deploy conversational chatbots.
As of Jan-2022, the streaming conversation cost for Amazon Lex was priced at USD0.0065* per 15-second speech interval. Thus, total Amazon Lex costs are (3,600 hours x 60 minutes / 15-second interval) x USD0.0065 per 15-second interval = USD5,600 per month = USD67,300 per year = USD202,000 in three years.
This example highlights that by handling just 2% of the 10.8 million calls per month using an Amazon Lex voice chatbot, the customer gains a net savings of USD3 million in three years – or 94% of the total planned savings by diverting those calls, in addition to an improved customer experience.
Also, note that savings would be even higher if the customer were to use the Amazon Lex text chatbot instead of the voice chatbot as Amazon Lex text request pricing is relatively lower than voice pricing.
Agent burden versus Amazon Lex voice chatbot cost comparison
Different organisations will have different fully burdened agent costs.
A comparison of agent burden costs versus Amazon Lex costs per month for varying scenarios of fully burdened agent labour costs per hour
While the percentage volume of calls that are FAQ might vary for each customer.
A comparison of agent burden costs versus Amazon Lex costs per month for different percentages of calls with FAQ deflected to virtual agents
The figures illustrate that total cost savings increase dramatically as a greater percentage of calls are deflected to virtual agents powered by Amazon Lex.
Organisations are modernising contact centres and adopting cloud solutions
Thousands of organisations have modernised their contact centres using Amazon Connect, an omnichannel cloud contact centre. They have used Amazon Lex alongside Amazon Connect to create virtual agents that automatically help resolve customer questions or guide customers to the right agent.
Some organizations who use other contact centre solutions such as Genesys PureCloud have also used Amazon Lex to deliver virtual agents and improved customer experience.
Many have also created informational bots in their websites and mobile apps for everyday requests and FAQ. Some organizations, like Hawaiian Airlines, have also created application bots for internal enterprise and use cases to improve productivity by automating many mundane user tasks.
Benefits of conversational AI solutions are clear
Mr Reddy says there are clear benefits for travel and hospitality companies to adopt conversational AI solutions, and there are examples from across different parts of the industry.
Airlines like Delta Air Lines have modernised their contact centres using Amazon Connect and can divert many of their contact centre calls to voice/text bots for FAQ such as tracking baggage or answering COVID-19 pandemic–related or pre-flight queries.
Hotels like Marriott and Wynn Las Vegas have simplified guest access to amenities using Alexa for Business, a service that empowers organisations and employees to use Alexa to get more work done (Amazon Lex is powered by the same conversational engine as Alexa).
Car rental companies like Avis Budget Group have automated and simplified rental reservations, streamlined roadside support, and answer billing inquiries using Alexa for Business.
Restaurants are using chatbots to check hours of operations, review menus, automate and update ordering, verify deliveries, and more.
For example, Le Rivage, a traditional French cuisine restaurant in New York City, used a chatbot to streamline staff time for order taking by 50%, according to Mr Reddy.
Offering natural conversations with customers in multiple languages through multiple channels
Many others are now using Amazon Lex to deliver natural conversations with their customers in multiple languages through multiple channels, sometimes concurrently.
“Using Amazon Connect with Amazon Lex, it was easy to build an intelligent virtual agent to answer calls, match guests with their reservations, and engage naturally with users”, says Tim Choate, founder and CEO of RedAwning, which has more than 140,000 properties in more than 10,000 destinations.
Another is the European LCC Ryanair, which worked with Cation Consulting, an AWS Partner, to deploy Amazon Lex and Amazon SageMaker to permit users to build, train, and deploy machine learning models for virtually any use case.
New automated chatbot designer helps developers automatically design chatbots from conversation transcripts
At re:Invent 2021 AWS launched the new service Amazon Lex automated chatbot designer, which helps developers automatically design chatbots from conversation transcripts in hours rather than weeks.
Amazon Lex helps to build, test, and deploy chatbots and virtual assistants on contact centre services (such as Amazon Connect), websites, and messaging channels (such as Facebook Messenger). This automatic chatbot designer enhances the usability of Amazon Lex by automating conversational design, minimising developer effort, and reducing the time it takes to design a chatbot.
For “buyers”, then as “builders”, AWS has experienced AWS Partners in this space to do the heavy work.