With or without AI, customer experience decides whether your brand has “loyalty power” or will end up in the graveyard of dead ones. Why? Enriched CX’s drive customers toward the cash till and beyond to repeat purchasing or brand ambassadorship. In both instances, it signifies a retained customer. So, the key to a successful CX is meeting or exceeding customers’ expectations at every touchpoint on their customer journey.
Conversely, unsuccessful customer journeys fall apart due to toxic or dysfunctional touchpoints. Indeed, it takes only one frustrating, aggravating, or anger-provoking brand interaction to derail a customer journey; that’s how sensitive the customer journey can be.
Are you willing to bet that your customers are already on the right track?
Customers make their own journey… right?
Think your customers should be able to find their own way? That they can get over a few hiccups? That your customer journey is already optimized?
Don’t take this lightly.
According to a 2020 report in Forbes, an astounding 96% of customers affirm they would abandon a brand on receiving poor service.
TCN (a call center software provider) agrees, noting that American customers in droves said they tanked a brand (as high as 73% in 2022) after experiencing a single defective brand experience, up from 42% the previous year.
So, this brings us to the next crucial question in improving CX…
What is AI customer experience?
AI embraces advanced technology that can create meaningfully different touchpoints, encouraging brand loyalty and driving revenue growth. From a marketer’s viewpoint, it involves shifting talent mindsets within the organization to improve customer experience with artificial intelligence. How? Harnessing machine learning (ML) algorithms, natural language processing (NLP), predictive analytics, and even robotic process automation to meet the strategic challenges of intensely competitive markets.
A few things to keep in mind about AI-driven customer experience:
- In almost every situation, it boils down to AI’s extraordinary capability to delve into vast data volumes, sift, and separate the wheat from the chaff.
- AI can do this significantly more accurately and in a fraction of the time it would take a multi-person team.
- AI seamlessly detects patterns, trends, and extracts “diamonds in the rough” concealed by a mega-quantum of numbers and text in company records that nobody could make sense of until AI’s analytical power appeared on the scene.
AI customer experience examples
The following AI-driven customer experience examples highlight how some iconic brands deploy AI tools to improve customer engagement, service, and satisfaction. They also reflect how small businesses with extraordinary tech insights disrupt oligopolies established sometimes for a hundred years or more:
a. The startup revolution owes much of its impetus to AI opening the pathway via micro-market segmentation. Startups based on high-tech notions converted quickly into disruptive juggernaut market entries, threatening and taking established enterprise strongholds down a peg or two. For example:
Massive banking institutions never contemplated the possibility that small fintechs (without banking licenses or financial compliance discipline) would severely shift their clients’ brand loyalty by offering compelling new value propositions.
AMEX, VISA, and MasterCard are countering wave after wave of Buy Now Pay Later (BNPL) insurgents taking over credit card customers hand over fist.
b. Olay Skin Advisor represents the many typical cases in the beauty industry of AI improving customer experience by harnessing ML to diagnose dermatological characteristics like skin age, acne issues, and shades to recommend beauty options in its brand range.
c. North Face is one of the first marketers to discover the revelations emerging from IBM’s heralded Watson ML technology. They use it to recommend jackets for computing, hiking, skiing, and other activities from “most precise fit” to “lowest match.”
d. Third-party retailers springboarding off of Amazon Echo: Amazon initially designed Echo to help customers shop via voice from the monolith retailer. However, Best Buy, REI, 1-800-Flowers, Domino’s, and Uber have jumped on the bandwagon, integrating Alexa into their customers’ shopping/service experience and websites.
Generative AI for customer experience – Levels of deployment
An extensive McKinsey report categorizes the maturity of AI-driven customer experience and service into five categories. They range from “Manual/high-touch” at the entry-level (Category 1) to the ultimate cutting-edge “personalized and digitally enabled engagement” (Category 5). The examples above represent higher-level case studies by focusing AI on proactive and efficient customer engagement, predictive intent recognition, and elevating self-service channels.
What can AI do for you? Read on!
The top 10 ways AI can improve customer experience
While the realm of artificial intelligence is evolving every day, here’s a quick snapshot of ways in which AI will impact CX today and tomorrow. (Next year? Anything is possible! 😉).
1. Personalized Recommendations
Many of us have experienced Netflix recommending movies and TV series in the same genre (comedy, documentary, drama, etc.) with the title – “Because you watched X.” It may seem old hat to you. Still, without ML algorithms spinning their wheels to identify your buying patterns and preferences, those convenient “close option” lists wouldn’t be possible. It directs your behavior by aligning with flashing lifestyle signals, short-circuiting your search, and creating a better CX.
2. Chatbots and Virtual Assistants (VAs)
The McKinsey report mentioned above emphasizes that AI development applications relieve employees of mundane tasks. They answer frequently asked questions, process orders, and even provide personalized brand recommendations.
Contact ATT or Verizon to appreciate that chatbots have shifted from the mechanical versions of yesteryear, becoming significantly more intuitive. It has reached the point where phone-in or live chat customers don’t know they’re talking to an AI voice program (i.e., a chatbot or VA).
Three massive benefits are that a virtual assistant:
- Frees a company’s human resources to uplift personal services.
- Routinely delivers high-quality outcomes.
- Uses AI data analytics to anticipate customer needs before they engage.
3. Natural Language Processing
Siri, Alexa, and Google Assistant are becoming popular voice assistants for families, from adults to small children. How do they operate? NLP (Natural Language Processing) is an advanced AI capability that enables machines to understand and respond to spoken commands, questions, and orders. In addition, these voice assistants:
- Virtually connect to and control other devices
- Provide accurate, personalized support and suggestions (by analyzing the user’s past requests and preferences).
4. Predictive Customer Service
5. Advanced Analytics
These two go hand in hand. Arguably, the most groundbreaking AI advance is its ability to derive patterns from mega-volume customer data and usage trends. From there, AI technologies demonstrate their power to:
- Predict future customer behavior:
- Across the customer journey, traversing sensitive touchpoints
- In brand usage and perceptions
- By identifying customers’ most pressing needs
- Pinpoint improvement areas.
The company can then proactively contact the customer with a solution or offer additional support, enhancing the customer’s brand experience.
6. Sentiment Analysis
AI can scan reams of customer reviews, emails, and social media posts in seconds. In so doing, it interprets the human sentiments behind the text, uncovering emotions such as passion, frustration, and anger to generate improvement suggestions.
7. Real-Time Personalization Aligned with Segmented Markets
8. Seamless Omnichannel Experience
Firstly, this circles back to AI data analysis, configuring markets into meaningful and detailed segments based on demographics, behaviors, and psychographic data.
Secondly, AI possesses the versatility and sophistication required to modify users’ experiences in real-time by tracking customer movements at and between touchpoints.
For example, an already segmented customer’s browsing habits on a website telegraphs incredibly accurate signals to an AI algorithm that can adjust the content to align with its insightful ML interpretations. The latter goes further than a desktop, laptop, or iPad, expanding such powers to embrace mobile devices, in-store movements, and navigating social media channels.
As a result, users consider this (applied directional behavior) an extraordinary brand service linked to a highly personalized shopping experience.
9. AI-Powered CRM
AI-driven customer experience technologies can significantly bolster CRM systems with insightful recommendations on the best leads to follow for fast downloads and conversions. That’s in addition to the time-saving automation of data entry, lead scoring, and follow-up reminders, which allows sales teams to focus on their sales enablement strategies, requiring crucial human input.
10. *Generative AI
Why the asterisk on this one? While generative AI for customer experience can be a plus, it has its risks as well. AI’s impact on our lives and the differences it can make is not all positive.
- Unintended data biases result in a “garbage in, garbage out” scenario that becomes the accepted truth in a company’s strategic decision-making.
- Privacy issues are front-and-center concerns with AI in the mix, creating ID theft and cyber-criminality issues.
Thus, generative AI cannot avoid ushering in essential ethical vigilance and protection of customers’ private thoughts, feelings, and profiles related to brands.
Where is AI headed next?
From the AI customer experience examples above, it’s evident that AI has moved past text and voice recognition into the realm of emotions – emotional AI, if you will. Algorithms are in the works to advance AI comprehension and response to facial cues and voice inflections. Customer service based on body language – how you express things versus what you actually say – elevates the stakes considerably. Empathetic AI-driven customer experience is the ultimate achievement in this conversation.
Another aspect is deploying AI advances to create AR (Augmented Reality) and VR (Virtual Reality) customer experiences. Like what, for example? Before purchasing, reality imaging a, say, “Rooms-to-go” furniture collection in your living room or see how a clothes ensemble looks on you (without a changing room)!
AR/VR, as it advances, will change the game, redefining the shopping experience from A to Z. Throw this together with AI neural networks/quantum computing and deep learning capabilities as they progress in leaps and bounds to analyze data more accurately and faster. Undoubtedly, it will create a more autonomous AI role in managing customer experiences by supporting human agents and acting independently from them as functional intermediaries, thus optimizing the customer journey.
One thing is certain in B2B and B2C marketplaces: the business ecosystem has embraced the AI-driven customer experience, understanding and anticipating customer touchpoints before shoppers arrive.
In a nutshell, the future of the AI customer experience will:
- Be faster and more efficient.
- Broaden out into unique, immersive, and emotionally intelligent interactions
- Jet-propel the marketplace into another dimension.
If this resonates with you, contact Sogolytics to guide you through an AI customer experience program customized to your business and marketplace. We have the resources, experience, and up-to-date insight on how AI and CX solutions can work together to improve customer experience and grow your business.
