How can Artificial Intelligence help in creating meaningful customer engagement?
Artificial Intelligence (AI) has been defining a whole new dimension of human-machine and human-human interactions. Once deployed to automate processes through logic, it is now being used to create a bigger and deeper connection with the audience, on a personal level. And in the near future, on an emotional level too. In this article, we dive deeper into the different benefits of adopting this technology.
Note: Interested in tech and Artificial Intelligence but doesn’t know where to start? For a clear introduction, check out this article from the Harvard Business Review.
#1 Early Adoption of AI at the core of business to improve customer experience
AI generally refers to the ability of machines to exhibit human-like intelligence, in this article we look at a set of AI technology systems that solve business problems. In the realm of exciting possibilities, AI’s investment is growing fast, led by Google and Baidu with an estimated spend of $20 billion to $30 billion on AI in 2016. 90 percent of this is spent on R&D and deployment, and 10 percent on AI acquisitions. There are no shortcuts for firms, a survey shows A successful program requires firms to address many elements of a digital and analytics transformation: identify the business case, set up the right data ecosystem, build or buy appropriate AI tools, and adapt workflow processes, capabilities, and culture. To manifest this reality leadership from the top, management and technical capabilities, and seamless data access will be key enablers.
High tech and telecom or financial services, are investing in AI using multiple technologies and function and integrating them at the core of their businesses to improve customer experiences. Businesses with proactive strategies combined with robust digital capabilities can use AI to deliver real value to adopters and be a force of disruption. Mckinsey’s case studies in retail, utilities, healthcare, and education can use AI’s potential to improve forecasting and sourcing, optimise and automate operations, develop targeted marketing and pricing, and enhance the user experience.
Amazon
Amazon has achieved impressive results from its $775 million acquisition of Kiva, a robotics company that automates picking and packing. “Click to ship” cycle time, which ranged from 60 to 75 minutes with humans, fell to 15 minutes with Kiva, while inventory capacity increased by 50 percent. Operating costs fell an estimated 20 percent, giving a return of close to 40 percent on the original investment.
Source: Eugene Kim, “Amazon’s $775 million deal for robotics company Kiva is starting to look really smart,” Business Insider, June 15, 2016.
Businesses and brand can use AI to create value in four areas: enabling companies to better project and forecast to anticipate demand, optimize R&D, and improve sourcing; increasing companies’ ability to produce goods and services at lower cost and higher quality; helping promote offerings at the right price, with the right message, and to the right target customers; and allowing them to provide rich, personal, and convenient user experiences.
In this article, we focus on technology systems such as: machine learning, virtual agents, and machine learning, and emotional AI and their impact on business and customer experience.
#2 Anticipate consumer expectations
Machine Learning is a subset of AI which allows a machine to automatically learn from past data without programming explicitly. (always briefly explain when introducing a new term) It creates value by creating new sources of value to make it richer, more tailored, and more convenient in a dynamic market environment. It has gone beyond recognising patterns and behaviours and analysing algorithms, as new developments enable aligning a brand's creative interests with its influencers’ content and create new opportunities that drive their audience.
Netflix
Netflix achieved impressive results
from the algorithm to personalise recommendations to its 100 million subscribers worldwide. Helping customers to quickly find desirable content. Through better search results, Netflix estimates that it is avoiding cancelled subscriptions that would reduce its revenue by $1 billion annually.
Source: Eugene Kim, “Amazon’s $775 million deal for robotics company Kiva is starting to look really smart,” Business Insider, June 15, 2016.
Machine learning and computer vision can for example, at a regular supermarket observe a shopper put a bunch of bananas in his/her cart, relay the information to an AI application that would have a good idea of what the shopper likes based on previous purchases. The app could then, via a video screen in the cart, suggest that bananas would be delicious with a chocolate fondue, which the purchase history suggests the shopper likes, and remind the shopper of where to find the right ingredients, giving new meaning to the idea of a “convenience store.”
Over the summer, Starbucks started using a real-time artificial intelligence personalisation engine to create personalised email offerings. In October that expanded to the mobile app. In November Starbucks started adding recommendations for additional items at the point of checkout for mobile orders.
Starbucks uses their data from 90 million transactions every week to inform business decisions such as where to open new stores, and which products they should offer. The company uses predictive analytics to process this data in order to deliver personalized marketing messages to customers including recommendations when they’re approaching their local stores.
The algorithm uses many different inputs besides purchasing history to contextual events such as weather and data from other third party segments to offer recommendations. The brand can connect deeply with its consumers by sending personalised marketing communication to recommend drinks at their local store based on their average spend. A virtual barista service on the app allows customers to place orders directly from their phone via voice command.
While machine learning underpins benefits of tailor-made opportunities for your consumers, it is essential as an industry to identify the AI technologies that will bring the most benefits to you, and then start to develop their infrastructure, talent, and knowledge as early as possible to catch up on the learning and adoption curves.
#3 Intuitive AI assistants that reflect brand personality
Now-a-days we are all too familiar with virtual assistant’s unique voices and personalities of Amazon’s Alexa, or the sassiness of Apple’s Siri and perhaps even the caring assistance of Microsoft’s AI assistant, Cortana. These bots with extensive human training developed just the right tone and attitude that best reflects the personality of the brand.
Human-machine collaboration enables companies to interact with employees and customers in novel, more effective ways. AI agents like Cortana, for example, can facilitate communications between people or on behalf of people, such as by transcribing a meeting and distributing a voice-searchable version to those who couldn’t attend. Such applications are inherently scalable—a single chatbot, for instance, can provide routine customer service to large numbers of people simultaneously, wherever they may be.
Giving chatbots a human name – like Cleo, Amelia only enhances the connection to the tasks performed by these AI assistants. Cleo, for instance, an Ai chatbot can manage your money. The Ai-driven chatbot messenger combines natural language processing and Fintech to organize users' finances using intelligent insights and a simplified interface. Unsurprisingly, 77% of about 1000 Cleo users have stopped using banking apps to manage their finances within 3 months of using the service.
Airbnb
Airbnb uses the chat bot to streamline communication about short or long term stays over messaging. Over 80% of the messages can be answered by the bot like a human.
Source: dribbble.com
Brands can harness the potential of machine learning’s near human-like personality characteristics to reflect the personality of the brand. As products and services become more commoditized, delivering great customer experiences at every step of the customer journey has become the differentiating factor between success and failure. Virtual assistants can reach a large customer base simultaneously, and will play a crucial role in improving customer journeys.
#4 Emotional AI: Emotional quotient to build a deeper customer connection
We’ve often heard that Ai can be many things but it cannot gauge human emotion. Right! think again. Affectiva's Emotion AI technology assesses emotional and cognitive states expressed by the user as they watch content in a specific context. Emotion AI or affective computing is a subset of artificial intelligence (the broad term for machines replicating the way humans think) that measures, understands, simulates, and reacts to human emotions. It can help businesses identify consumers' emotional reactions in real time, it decodes facial expressions, voice patterns, monitors eye movement and neurological immersion levels to build a closer and a more personal connection with their consumers.
Affectiva Automotive AI is the leading In-Cabin Sensing (ICS) solution that understands what is happening inside of a vehicle. Affectiva's patented deep learning-based software uses in-vehicle cameras to measure in real time, the state of the cabin, and that of the driver and occupants in it — from complex and nuanced emotions and cognitive states, such as drowsiness and distraction, to occupancy, activity, object and child seat detection.
Affectiva Automotive AI
OEMs, Tier 1s, ridesharing providers and fleet management companies can deliver optimized occupant experiences and advanced safety features using Affectiva's AI.
Source: https://www.therobotreport.com/affectiva-automotive-ai-cars-monitor-emotions/
Ford, AutoEmotive and Affectiva’s Automotive AI are getting market ready to detect human emotions in the driving experience to take charge of the vehicle to prevent accidents or road rage.
In a recent Deloitte Digital survey of 800 consumers, 60 percent of long-term customers use emotional language to describe their connection to favored brands; likewise, 62 percent of consumers feel they have a relationship with a brand. Trustworthiness (83 percent), integrity (79 percent), and honesty (77 percent) are the emotional factors that consumers feel most align with their favorite brands.
Personal assistants, chatbots, or conversational IVRs (interactive voice response) give brands the emotional quotient input that helps them connect with their consumers on a deeper and more personal level. Smarter and emotive AI can help with forecasting and optimization in production and maintenance cycles for businesses. Promotions can be more tailor-made, and convenient, and targeted to the consumer all done with the aim to improve and enhance the customer-centricity.
Conclusions: When advancing with AI ask the following questions:
Rethinking the value proposition around investing AI and improve customer experiences and business benefits?
How can you reflect your brand personality with Intuitive and human-like AI Chatbots to build personalised connections with customers, how to start?
When human empathy and friendly smile is simply irreplaceable?
