Perhaps this situation has happened to you: you went to a store where you were treated in an extremely personalized manner because the sellers already had access to your history. Then, you started to wonder: “Why isn’t it always like this?” Next, you go to the hospital in an emergency, but the service is delayed because of your registration—even though you’ve been to this hospital many times and your medical data is available on your Apple Healthkit. Or, upon learning where and how the coffee bean you are consuming from your favorite brand was grown, you wonder why the same isn’t true for the material used in your computer’s semiconductor, and so on.
It’s a fact: we update our expectations based on the best experiences of our daily lives—not by what that hospital or store has always done, nor by what its competitor does, but by the best experience the customer has in their daily life, regardless of the sector.
My thesis, in a world where technology increasingly accelerates customer empowerment, is that Artificial Intelligence is the great means by which we can pivot from a more passive, reactive, and transactional customer relationship (as it is today), to a much more proactive, conversational, and experiential relationship.
Let’s start by listening to a quote from Satya Nadella, CEO of Microsoft:
How AI Brings Hyperfocus on the Customer: Satya Nadella on AI
Perhaps this situation has happened to you: you went to a store where you were treated in an extremely personalized manner because the sellers already had access to your history. Then, you started to wonder: “Why isn’t it always like this?” Next, you go to the hospital in an emergency, but the service is delayed because of your registration—even though you’ve been to this hospital many times and your medical data is available on your Apple Healthkit. Or, upon learning where and how the coffee bean you are consuming from your favorite brand was grown, you wonder why the same isn’t true for the material used in your computer’s semiconductor, and so on.
It’s a fact: we update our expectations based on the best experiences of our daily lives—not by what that hospital or store has always done, nor by what its competitor does, but by the best experience the customer has in their daily life, regardless of the sector.
My thesis, in a world where technology increasingly accelerates customer empowerment, is that Artificial Intelligence is the great means by which we can pivot from a more passive, reactive, and transactional customer relationship (as it is today), to a much more proactive, conversational, and experiential relationship.
Let’s start by listening to a quote from Satya Nadella, CEO of Microsoft:
“One of the things that’s so exciting to see is the software engineers at Starbucks, their ambition to completely incorporate digital throughout, blockchain and sustainability, IOT and the coffee machines. (…) Today I’d like to show you some of the exciting things that we are doing in our labs and in our stores. As all of you know, Starbucks is all about human connections, and we love the experience of our customers with our baristas in our stores. But technology is playing a bigger and bigger role in those interactions. (…) We are here today at Build conference to take you through what we have been doing with personalized recommendations. (…) I am going to go ahead and get the Sous Vide Egg Bites with bacon and Gruyere (…) So what just happened here is that we’re actually using our DeepBrew AI Platform to be able to suggest optimal product pairings based on contextual information of the store, the weather, and other things that are going on.”
Let’s start with the problem: Starbucks traditionally followed a process of preparing drinks in order of arrival, which risked drinks not being served at the right temperature if customers picked them up without ordering in-store. Starbucks decided to use AI: its algorithms determine the order in which baristas in stores should prepare drinks based on estimated customer arrival times and orders. This helps optimize the drink preparation process and improve the customer experience, ensuring that each customer receives the drink at the temperature it should be consumed.
All of this was made possible by Starbucks’ Deep Brew platform mentioned in Satya Nadella’s quote above. How does it work? To understand this, we need to explore a bit of the history and how Starbucks got there…
In 2011, Starbucks launched its mobile app, which was its first step towards data and analytics. They discovered that it was one of the most important drivers of their digital transformation.
The app was designed to be used as a loyalty program, allowing customers to earn stars with each purchase and redeem them on their next order. Eventually, the app became a hub where customers could learn about menus, store locations, and opening hours. The app provided Starbucks with information about popular store locations, drinks, and times of day based on customer activity.
Today, Starbucks processes a quarter of its 100 million weekly transactions through its mobile app, and the trend accelerated even more during the Covid-19 pandemic. Starbucks’ digital flywheel strategy included allowing users to place orders from their mobile apps in advance and pick them up from store windows or by entering stores. The brand capitalized on the power of AI and marketing to expand the capabilities of its app. Starbucks now has four digital components in its flywheel—a rewards program, personalization, payment, and orders. Digital innovation at Starbucks has undoubtedly been credited with driving growth; they have established themselves as experts in creating loyal customers through the use of data. The coffee brand’s executives realized that using data analytics to maximize customer lifetime value (average purchase price per customer per visit, number of visits per customer per year, and average customer lifetime) would be key to achieving an unbeatable competitive advantage. By using data analytics, the coffee company was able to maximize customer lifetime value while reinventing its brand offerings… and the areas where they innovated were as follows:
“Personalized Recommendations” – Starbucks personalized the customer experience for each consumer based on their unique preferences and consumption habits, collecting and analyzing a large amount of data on customer spending and preferences. By analyzing past orders and patterns, the app can suggest food and drink choices, but also send personalized deliveries. Starbucks creates a deeper connection with customers by sending real-time triggers and push notifications. Customers are delighted that the brand caters to their preferences and pleases them with a personalized experience.
“Innovation and New Product Offerings” – In addition to personalization, Starbucks creates new products using the data collected through its digital flywheel. Their innovative products, such as dairy-free or sugar-free beverages, special summer drinks, or new products for home consumption, were the result of analyzing user preferences. Starbucks discovered, for example, that 43% of tea drinkers do not add sugar to their tea, and about 25% of iced coffee drinkers do not add milk to their drink when consuming it at home. This information led to the development of two unsweetened K-cup iced teas—Mango Green Iced Tea and Peachy Black Tea. Additionally, they developed pumpkin spice lattes and cold brew coffee without milk or added flavors as a result of their data efforts.
“Store Location” – It may seem like Starbucks stores are popping up everywhere, but in reality, the flywheel’s data helps discover where each new store should be located. The coffee giant uses data and AI to predict revenue based on variables such as income levels, traffic, and competitor presence, and determine where the next big growth opportunity is. This gives them the opportunity to minimize risk as well as position the new store in an area targeted to a specific audience. With Deep Brew, they can not only personalize drive-thru experiences but also automate time-consuming tasks like inventory management and preventive maintenance on their Internet of Things (IoT) connected espresso machines.
But Starbucks is obviously not alone: companies like John Deere and Tesla have also reinvented their relationship with customers through AI, and if there’s one message here, it’s this: today, you can’t generate value for the customer without using AI.
Why is that? Because AI allows companies to focus more on the customer through the following pillars, which together end up transforming the customer experience (as it is today) from Reactive and Transactional to a Proactive and Conversational experience. This is done through the 5 main pillars of AI activity today, which are as follows:
- Prediction and Decision Making Based on DataAI can analyze large volumes of customer data to identify patterns, trends, and valuable insights that would be nearly impossible to detect manually. This allows companies to predict customer behaviors, such as the likelihood of purchase, churn (service cancellation), among others. These predictions enable more informed and proactive decision-making, allowing for mass personalization of the customer experience. For example, recommending specific products or services based on past behaviors or anticipating customer needs before they even express them.
- Content Creation (Through Generative AI; Large Language Models)Large-scale language models, such as GPT (Generative Pretrained Transformer), can generate highly personalized and relevant content for users. This includes personalized marketing emails, website content, blog articles, and even responses to frequently asked questions, all tailored to individual customer preferences. By providing relevant and valuable content, the customer experience is enriched, increasing engagement and satisfaction.
- Process AutomationProcess automation with AI ranges from customer service chatbots to order management systems that operate with little or no human intervention. These automations improve operational efficiency and ensure that customer experiences are fast, consistent, and of high quality. For example, chatbots can resolve simple customer service issues 24/7, while automated order management systems ensure purchases are processed and shipped quickly and accurately.
- Natural Language Processing (NLP)NLP allows machines to understand, interpret, and respond to human language naturally. This translates into significant improvements in the customer experience, as it allows for more natural and humanized interactions with AI systems, whether through chatbots, virtual assistants, or conversational user interfaces. NLP can be used to analyze customer feedback on a large scale, identifying sentiments, trends, and areas for improvement.
- Machine Vision and SensingMachine vision enables AI systems to “see” and interpret the visual world, while “sensing” refers to the ability to detect and interpret various types of sensory inputs. In the context of the customer experience, this can be used to identify products in a physical store, facilitate automatic checkout, personalize digital advertising in physical spaces based on the demographics of the present audience, or even for accessibility, helping visually impaired customers navigate environments or digital interfaces. These technologies significantly improve the shopping and interaction experience with the brand, making them more intuitive, efficient, and personalized.
These 5 AI activity pillars are extremely powerful in generating more value for the customer. Considering just process automation, such as interaction with Chatbots, a Capgemini report titled “The Art of Customer-centric Artificial Intelligence” points out that two to three years ago, most organizations (93%) had less than 30% of interactions enabled by AI.
Today, however, only 10% of organizations are still at this low level, with 80% stating that between 30% and 50% of customer engagements are AI-enabled. In two to three years, the vast majority (80%) will have more than half of their interactions enabled by AI. In other words, eight out of ten organizations will have more than half of their interactions with customers conducted by AI during this period.
In conclusion, the potential of AI is enormous—but we are still only seeing the tip of the iceberg. The areas where AI can maximize Customer centricity include personalization, immediate gratification, anticipation of problems, low-friction journeys, and much more.
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