In his May 2023 paper, "The Impact of AI on Customer Experience in Financial Institutions", Phase 5 Partner and Chief Innovation Officer Arnie Guha lists 4 key opportunities for FIs to transform CX through the use of artificial intelligence. The first of these four is “Personalized Products and Recommendations”, a concept that can be applied not only to financial services, but also to other sectors, such as retail, and manufacturing. In this article, we share several examples of how advanced technology is creating opportunities for CX improvement across industries.
It’s obvious that there is no shortage of ideas or options. However, organizations must somehow sift through and prioritize the possibilities to determine where to invest, as they need to develop the new experience in a way that is most meaningful and desirable to their unique customer base. Existing papers such as “Future of the Interface” can provide strategic direction, and custom research can help quantify specific opportunities in order to minimize risk and maximize ROI.
Examples of AI Improving CX in Financial Services
One of the leading examples of an AI application improving customer experience in financial services is “Marcus Insights” by Goldman Sachs, which is cited by Guha in his latest paper. This personal finance management tool provides customers with personalized insights and recommendations based on their transaction data not just at Goldman Sachs, but across all their accounts at any institution.
The technology enables Goldman Sachs to gather and analyze a very broad view of the customer’s finances, enabling customers to “see <their> money clearly and make empowered financial decisions”. It’s free and easy to use, even for those who aren’t a current Marcus customer, promising “no spreadsheets or manual tracking required”. In terms of Jobs-To-Be-Done, Marcus Insights does the tedious job of pulling together all of a customer’s financial data, and then the time-consuming and sometimes challenging job of identifying options for acting on that information. These “jobs” get done quickly and easily, creating a ‘wow’ level of customer experience.
In the insurance industry, Allstate has created Amelia, which Forbes describes as an “AI-powered cognitive agent trained on more than 50 unique insurance topics and regulations across all 50 states”. The use of this artificial intelligence application enables front line service representatives to more quickly and efficiently answer complicated questions from customers. In a business rife with regulations and complexity, having a tool to facilitate speedier service without sacrificing accuracy or jeopardizing compliance can be a game changer. Its use by agents creates competitive advantage by helping them deliver a more personalized customer experience that accounts for specific circumstances without dropping the ball on service time, accuracy, or compliance.
Examples of AI Improving CX in Retail
Modern home décor retailer West Elm created Pinterest Style Finder by leveraging AI together with a customer’s Pinterest boards to help define that customer’s “individual style based on their source of inspiration”. Forbes reports that people used to bring physical copies of their Pinterest boards into West Elm stores, presumably to get guidance from in-store staff. But now, the Style Finder tool can easily scan those boards and then automatically generate recommendations for furniture or décor to suit that particular style. Once again, the customer experience is enhanced by the personalized service that is not only speedy, but also thorough in terms of its knowledge of the customer as it relates to the category.
Shifting retail gears to the everyday grocery category, Kroger is working on a smart shelf system it calls EDGE (Enhanced Display for Grocery Environment). An article in Forbes describes how sensors will be able to identify a customer (with the Kroger app open) who is walking down an aisle, and personalize the signage/display just for that customer. If you’re someone who typically needs to read ingredient lists to ensure allergens (e.g. gluten, peanuts, soy) aren’t present, imagine if those specific ingredients were highlighted for you in the signage, in font as big as the price. Or consider a scenario where you are on vacation at an Airbnb for a week and need to navigate a different grocery store. Imagine all of your typical weekly staples highlighted for you in the aisles so that you save time shopping. This type of customer experience would be possible through AI applications like EDGE.
Examples of AI Improving CX in Manufacturing
Manufacturing may not seem as obvious in terms of its ability to improve customer experience through the use of AI. But here are a couple of examples of where artificial intelligence is making its mark in this sector.
The essence of manufacturing is the assembly line and/or machinery that works together to make a product. Sometimes during that manufacturing process, machines will break down, mistakes will occur, and a sub-standard product might reach distributors and/or end-users. With machine learning however, defects are being detected earlier in the process, triggering repairs, and preventing a negative customer experience that would have previously been inevitable.
Built-in.com shares several examples of AI at work in manufacturing, including a company called Veo Robotics that is combining 3D sensing, computer vision, and AI to constantly monitor operations and reduce the need for shutdowns to perform inspections. If any malfunction is sensed, that area of the line can be automatically shut down temporarily so that the issue can be addressed.
Of course Quality Assurance practices and regularly scheduled maintenance can prevent defects. But by using data driven automation, AI enables manufacturers not only to sense and correct an unexpected problem when it happens, but also to react and initiate customized, predictive adjustments for scenarios specific to that operation. The MIT article “4 Ways AI Will Change Design and Manufacturing” shares this example of how AI can save the day (and ultimately the customer experience):
"...imagine that the temperature in a manufacturing plant spikes overnight, or that a machine is fed a batch of materials with slightly different properties from standard materials. Without sensors and smart systems, machines will simply continue to operate as normal and not take variations in the environment or materials into account. This can lead to delays, machine degradation and ruined products.
By contrast, smart manufacturing systems detect when something is off and automatically adjust to changing conditions. This, in turn, can improve quality control, as well as reduce costs and increase reliability."
Another great example of leveraging AI for personalization to improve CX in manufacturing is product customization. Advanced technology makes it much more feasible for large companies to produce several versions of product as opposed to only one mass market version. Nike is one company that has embraced this concept, with COO Eric Sprunk telling datadriveninvestor.com, “As demand for our product grows, we must be insight-driven, data-optimized and hyper-focused on consumer behavior. This is how we serve customers more personally at scale.” By analyzing and applying data from connected devices and apps (where data sometimes includes customers’ photos of their feet), Nike is able to quickly and easily find customers the right model and shoe size. Eventually, the company hopes to “fully personalize the product” as their capabilities advance.
The Future is Personalized
AI is not just a buzzword. It’s being talked about and implemented across industry sectors such as financial services, retail, and manufacturing, and it’s having a real impact on these organizations’ abilities to personalize their products and services. Capabilities are also evolving quickly, so the bar is rapidly getting higher in terms of customer expectations. Companies whose customer experience falls short are at risk of losing share.
The strategic decision to invest in artificial intelligence and its related applications can be daunting. The possibilities are far reaching, so understanding what is most important to your customers can help narrow the focus in a meaningful and actionable way. Contact Phase 5 to further discuss our work on the impact of AI on CX, and how we can support your organization’s journey to customer-centricity.
