February 14, 2018 | Written by: Zach Tomlinson
Categorized: Discovery and Exploration
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- Customer engagement innovations take shape at lightning fast speeds, increasingly with artificial intelligence (AI) at the core
- Through the AI-powered concierge, enterprises can execute the same interactions once taking place in stores, online, 24/7 on a global scale
- Other firms with complex interactions, long email chains and multiple calls are reinventing and streamlining customer journeys using AI
- Real-time analysis of unstructured customer-generated data is the next big thing – and will be one of the most critical sources of differentiation available in 2018. Applying artificial intelligence will not only ensure businesses keep up, but lead
Learn more about creating your own insight engine
Standards of exceptional customer service are always changing
Just a few decades ago, interactions were slow. Customers sent their complaints through the mail, waiting months for a response that may never arrive.
As technology advanced, businesses offered new ways to innovate and improve customer engagement — at ever-increasing speeds. Snail mail became phone banks with advanced logical routing to subject matter experts. Then the conversation moved online, with inventions such as live chat and interactive voice response creating new channels for engaging with the customer.
Today, customer engagement innovations take shape at lightning fast speeds, increasingly with artificial intelligence (AI) at the core.
Cutting-edge organizations apply the very latest technologies to break new ground, like insight engines with Watson AI. Mining unstructured data not only unlocks rich customer insights, but can also empower employees to deliver a consistent, expert customer experience across channels.
All new purchasing channels
The explosion of social media, connected devices and mobile applications opens a world of new channels for enterprises to engage with customers — and creates a vast amount of data with which companies can learn more, and operate more effectively. By 2025, the average person will interact with connected devices nearly 4,800 times per day — one interaction every 18 seconds. Forward-thinking companies are already engaging their customers through these new channels — or preparing to — and using the resulting data to reap financial rewards as a result.
1-800-Flowers began engaging customers through Facebook Messenger to provide customer service support with live staff. They then went on to introduce a bot to handle basic customer inquiries and allow customers to purchase products within the messenger app itself.
Following these successes, the company launched its first AI-powered online gift concierge using IBM Watson. This allowed customers to make purchase on their own terms, whilst receiving personalized gift recommendations.
Through the AI-powered concierge, 1-800-Flowers is able to have the same interactions it was having with its customers in store, only now they’re happening online, 24/7 on a global scale.
Reinventing and accelerating the customer journey
Banking, insurance and tax are three sectors renowned for complex interactions with long email chains and multiple calls. Combined with complex products and services across multiple channels, this often leads to an inconsistent experience. The customer is often left frustrated by long and often fruitless interactions, which are only available through limited communication channels between the hours of 9-5. Innovative businesses across these three sectors are reinventing and streamlining these customer journeys using AI.
H&R Block has reinvented tax preparation by training Watson on the language of taxes, rolling out a new AI experience for customers across all its retail locations. The platform understands context, interprets intent and draws connections between client statements and relevant areas of their return. This information empowers H&R Block professionals, who can swiftly build on this guidance to maximize a client’s refunds.
Leading Australian insurer Suncorp now uses IBM Watson artificial intelligence to conduct liability analysis and assist in fast-tracking simple claims, such as single vehicle incidents with detailed descriptions. The system analyses customer descriptions of motor vehicle accidents – which are often written in a conversational way, including colloquialisms and Australian slang. Since launched in June 2017, the proportion of fast-tracked claims has tripled, enabling claim consultants to focus more time on complex scenarios, while helping more customers get their vehicle into a repairer and back on the road faster.
Personalized marketing experiences
Shopping online creates a rich digital footprint of individual preferences, spending habits and preferred purchasing channels.
Feeding these data points into an insight engine can bring hyper-personalized shopping experiences to mass audiences. That’s incredibly powerful considering 62% of 18-34-year-old internet users value AI for recommending products and services, according to eMarketer.
There are also powerful use cases for insight engines in improving how customers interact with a brand beyond influencing purchasing decisions.
Toyota, Unilever and Campbell Soup use Watson Ads — to deliver personalized one-to-one brand experiences built on new consumer and product insights uncovered by Watson. Consumers can now ask Watson for personalized Campbell Soup recipes built around the weather, past decisions, personal preference and even the groceries available on hand.
Empowering customers to self-serve
There is an ever-growing demand for do-it-yourself customer service, driven mostly by tech-savvy millennials. Almost 75% of millennials prefer to resolve their own issues using a web forum or FAQ page, before picking up the phone to talk with a customer service rep.
Artificial intelligence plays a critical role, enhancing self-service virtual agents and chatbots, whilst using real-time and historical data to recognize hidden opportunities to improve gaps in service and enhance the customer experience.
Autodesk introduced its Watson-powered virtual agent AVA as the first stop for any customer service inquiries. Autodesk trained Watson Conversation on their consolidated body of knowledge, allowing the system to understand and recognize different types of customer queries. The result: AVA allows customers to resolve their issues in a matter of minutes, rather than the previous average of a day and a half, a dramatic improvement of 99%.
The Royal Bank of Scotland has drastically reduced its customers’ waiting times through its own Watson-powered chatbot now known as ‘Cora’. The system uses natural language processing to interpret all queries and makes decisions based on its learning, allowing the customer to rapidly resolve simple customer queries like address updates and overseas card use, whilst redirecting complex queries such as stolen credit cards to a human advisor. Cora has been rolled out to RBS, Ulsterbank and Natwest customers.
For businesses, sometimes the customer is actually the employee.
As an example, Woodside Energy, Australia’s leading oil and gas company, delivers real-time information to its new recruits, in a language tailored to their work. The service, powered by IBM Watson, ingests the millions of documents related to Woodside Energy’s deep ocean gas platform operations. Helping bring new recruits up to speed and develop ‘heroes,’ employees who use the best tools to make a positive difference.
Predicting the customer needs
Taking personalization to the next level, businesses are increasingly using AI to leverage their unstructured data to predict when or what customers are going to purchase, or when they might get in touch.
This method of preemptive activity is crossing over into customer support and other knowledge workers, including sales professionals, analysts and others. Firms can monitor distress indicators and identify customers experiencing issues, products with quality assurance challenges and credit or security risks. Brands can respond in real-time with self-service and virtual or human agents to resolve customer issues before the user even knows they’re having a problem. This has the power to significantly improve employee performance, lower shopping cart abandonment rates, reduce complaints and improve overall consumer satisfaction.
Looking towards the future, real-time analysis of unstructured customer-generated data is the next big thing – and will be one of the most critical sources of differentiation available in 2018.
Applying artificial intelligence to implement an insight engine will not only ensure businesses keep up, but lead. Especially considering only 7% of companies are able to consistently deliver real-time, data-driven experiences across all customer touchpoints and across both digital and physical engagements.
Learn more about creating your own insight engine to improve customer engagement and employee performance.