The AI-enhanced CX Journey
What if shaking a Magic 8-Ball could really tell us what to do and then back it up with raw data? While AI definitely is not an 8-Ball (yet), it can certainly help us decide if making changes to our customer experience journey is a wise decision. This AI-enhanced CX journey drives a new era of making informed and (big) data-driven decisions that can help businesses create flawless Customer Experiences and stay ahead of the curve. In 2019, 25% of all customer interactions were automated through AI and machine learning. This number is expected to grow to 40% by 2023, since 90% of companies are planning to deploy AI within 3 years. CTOs, CEOs, and other executive-level roles report a growing demand for AI-enhanced CX. And as they want more than AI can provide, according to Gartner’s recent Hype Cycle for Artificial Intelligence 2021 report, these capabilities are changing fast, pointing out that the above-average number of innovations will reach mainstream adoption in the period of two years.Artificial Intelligence: A New Era for Customer Experience
AI is enabling new approaches to improving CX design, development and overall strategies. This is prompting businesses to en masse start adopting AI and ML ecosystems that have the ability to understand unstructured data in a similar way humans do but do it at enormous scales. Since the evolution of AI allows systems to see, hear and talk, the CX teams are starting to leverage these capabilities to create a new era of AI-powered customer experiences that very much feel like natural and organic human engagement. This change within the digital landscape matches the scale of the one that happened when the WWW completely disrupted the way modern businesses operate, only this time the timeframe of this digital evolution is much shorter.Leveraging AI/CX technology to stand out on the market
The modern business landscape is quite harsh competition-wise. Direct competitors are all fighting for the same consumers, which means that CEOs need to step up their game on all fronts if they want to stand out in their already saturated market. To do this, they must invest in AI-powered CX as the quality of their customer journey can often be even more impactful than the quality of their actual product and/or service. If they fail to do so, they will struggle to stand out as they will offer an outmoded, uncompetitive business model. Based on McKinsey’s findings, an increasing number of retailers are launching smaller pop-up stores, highlighting the power of AI retailers should leverage to offer their local consumers more personalized shopping experiences. AI is capable of dramatically elevating the level of consumer experience and customer service, especially via techniques like:- hyper-personalization
- real-time decisioning and predictive behavior analysis
- chatbots
- better overall understanding of your customers
Hyper-Personalization Drives Customer Engagement
According to Hubspot, over 90% of customers are more likely to repeat purchases from brands that offer outstanding customer service. The modern consumer has increasing expectations from the brand’s customer service. They expect you to treat each user as if they’re their only one, by providing them highly personalized services and solutions. These data sets, especially those that AI accretes about an individual’s activity and purchasing patterns, enable businesses to more quickly and more granularly learn what their customers want and then react accordingly by offering individual customers exactly that. While segmentation allows businesses to create customer groups, hyper personalization drills down to the smallest differences which allow them to target customers’ at the individual level. Based on the study conducted by the University of Texas, companies feel the urge to personalize customer experience because this allows customers to have control and make their decisions more easily. Put simply, by providing customers with information that is tailored to their needs helps them decide on the brands and the products they prefer. This builds trust, drives loyalty in customers and increases the brand’s ROI. Namely, 86% of consumers claim that they always think of brands they are loyal to when they need something. Also, emotionally loyal customers will always put the brand they trust first when buying something. And, according to Gartner, brands risk losing 38% of their customers if their experience is not personalized. Take Amazon, for example. It uses a recommendation engine algorithm to suggest products based on the gathered data (customer demographics, psychographics, view history and previous purchase) that allows it to create user profiles and make a highly personalized and contextualized email for the shopper. Netflix is another big player which leveraged the power of AI to personalize their customer experience. It uses the algorithm to gain insights into what kind of content its viewers want to see. It combines predictive learning with behavioural attributes to create highly personalized and individual experience starting from the homepage. Another interesting example of how retailers used AI to boost their customer experience is In Australian Uniqlo which built an AI fashion booth that used neuroscience to measure customers’ reactions to various designs and recommend items that suit the individuals’ preferences.How Does Personalization Help Your Customers Work Smarter?
By leveraging the power of AI, companies can offer their users completely new ways of consuming the content they search for. Our experts, who are well-versed in Machine Learning and Data Analytics joined strengths with one of our clients to build advanced analytics and utilize Natural Language Processing (NLP) to transform passive knowledge resources into a personal knowledge assistant that actively provides users with the personalized content based on their ever-evolving needs and interests. This can really be a booster for businesses, but more importantly, it can make work much easier, making people less like machines, by making machines more like humans.“This kind of system tracks users’ behaviour, identifies and suggests possible new pieces of information that would otherwise be missed or would take a huge amount of time to be manually extracted from the available data. Relevant information about the users’ behavior includes how many times the user looks for something, how much he interacts with the similar content, etc. By combining all pieces of information into a recommendation, we let users receive relevant information without having to manually search for them. This way the system does the “boring” stuff and you, as a user, have more time to focus on extracting the information and combining the results into a new business strategy.” — Ivan Petrovic, Machine Learning Engineer at HTEC GroupTo find out more about how our experts implement NLP, read How Natural Language Processing Powers Businesses.