Role of Voice AI in Contact Center Transformation
Role of Voice AI in Contact Center Transformation
Providing better customer experience is a goal that many businesses struggle with.
A survey of over 30 industries found that “providing better customer experience” has risen to the top of the list of strategic goals for outsourcing.
The survey also shows that 40% of businesses consider providing their customers with “more current and effective technology capabilities” as a key strategic goal.
Further, below insights as per a Gartner study are interesting:
- Nearly 66% of all customer experience projects will rely on technology and 40% of all analytics projects will concern customer experience and attitudes.
- 72% consumers expect agents to know all the key information about their account and have insights based on their previous engagements.
- 59% consumers report to have used multiple channels to get their queries resolved.
- 50% expect responses on social media within an hour and 18% expect immediate responses to their service requests.
- 83% report that they have had to repeat the same information multiple times to multiple agents.
- Nearly half say agents almost never have the context to solve their issue efficiently.
Customers Expect Smooth Contact Centers Interactions in their language
- 75% of the Indian language internet users will be composed of non-English users by 2022.
- Globally, only 9% of users are native English speakers.
- 52% call centers globally state that they expect multilingual interactions to increase over the next 3 years
- only 19% are equipped to handle some level of multilingual interactions through human agents.
These evolutions mean that contact centers have their task cut out.
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Automating the Contact Center through Voice AI
The challenges with legacy IVR are well-documented. Enterprises certainly don’t need a solution that’s non-intuitive and out-of-sync with evolving customer expectations. Voice AI, also known as conversational AI, is being touted as an intuitive, quick, and convenient solution. Through use of pre-trained AI bots, contact centers can reduce the burden on their staff.
The bots handle repetitive, tier 1 support requests, freeing up contact center employees for complex tasks that require human intervention. Conversational IVR uses AI to transform traditional DTMF menu navigation into an interactive dialogue. Users can reach the right point in the menu by stating their needs in their own common language instead of dealing with complicated options.
Conversational AI: A Cost-effective Solution for Contact Centers
Conversational AI differs from basic FAQ bots thanks to their ability to understand and interpret meaning.
Self-serve decreases operational costs and lightens the workload of agents.
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Also, most follow ups and regular engagement can be handled on these low-cost channels with human-level empathy.
All this also allows agents to focus on more important tasks and increases their motivation.
Conversational analytics uses recorded interactions and applies textual and emotional analysis to help in,
- Call center monitoring and reporting
- Agent performance analysis and training
- Customer satisfaction and service quality analysis
- Automation of quality monitoring processes
- Competition, market and campaign feedback analysis.
Through features such as,
- Sentiment analysis
- Emotion detection
- Topic categorization
- Real-time analysis
- Predictive insights
- AI-powered speech analytics
Building an Efficient Contact Center with AI
An agent can take one call at a time. More than 100 conversations can be managed at once at 1/10 of the cost when you layer in AI-powered chatbots. With > 70% conversations handled by bots, contact center staff can focus on high-value, sophisticated requests.
Omnichannel conversational experiences have proven to increase conversions by up to 3X and decrease customer care costs by up to 48%. Agents and AI bots can collaborate in a single web-based workspace to handle all clients’ messaging and call channels.
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With the ability to monitor bot in real-time along with smart routing, agents can intervene when necessary to maintain a positive consumer experience. Simulations, live monitoring and self-training also helps improve the bot over time and increase its scope.
The ROI of Implementing AI in Contact Centers
Organizations report a reduction of up to 70% in call, chat and/or email inquiries after implementing a cognitive customer-facing assistants. They also report increased customer satisfaction and a savings of 33% per voice engagement.
A 5% increase in IVR completion could result in annual savings north of US$ 250,000. A moderate improvement in CX would impact the revenue of a typical $1 billion company an average of $775 million over three years.
With a typical business process outsourcing (BPO) contract running 4.1 years and the pace of AI automation ramping up quickly, it makes sense for customer services leaders to question whether to sign new, long-term BPO contracts until they have more visibility into the pace of AI adoption.
Pure-play contact center BPO companies are less mature but have tremendous potential to move up the value chain. Some contact center companies surveyed by HFS find it difficult to fit contact center AI into their business and they think that automating customer interactions brings with it revenue cannibalization.
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However, for front office use cases there is a tremendous opportunity for these players to take the lead given their wealth of customer data and customer experience expertise. By embracing cognitive assistants, these service providers have the opportunity to carve out a differentiated capability for a blended bot and human model, providing seamless transitions to human agents and harnessing the power of their core capability.
They can accomplish all this while potentially breaking out of the legacy FTE models that have dampened innovation and profitability for years. Cognitive technologies, when smartly managed, will allow business to scale without the linear addition of staff to deliver scale.
This creates a huge opportunity for service providers to compete, as those which can provide volume services and lower rates, based on their acumen to deploy cognitive assistants to support their clients.
Of course, enterprises will have the choice of deploying cognitive assistance themselves inhouse, or whether to engage with external service partners which can deliver high volume/ low-cost cognitive services for them.
Much depends on the skills needed to develop ongoing algorithms based on an intimate understanding of the business and its institutional processes. This is where Voice AI solution providers are taking the next step towards empowering building, maintaining and monitoring of such cognitive services.
Innovative voice AI companies are building a fully integrated low-code enterprise platform which can be leveraged by non-technical people to build such conversational assistants without specializing in NLP. Contact center transformation with Voice AI promises a tech-based approach that works in the benefit of every stakeholder. The day is not far when Voice AI will be the standard, rather than the exception, for contact centers around the world.
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Sangram Sabat is the COO and co-founder of Saarthi.ai, a pioneer in multilingual Voice AI technology. An IIT alumni, he has previously worked as business consultant at Citibank and Fractal Analytics. Sangram is passionate about artificial intelligence, Big Data, NLP, and how these technologies can be used to automate business processes.