New technologies are revolutionising the way customers interact with brands. Virtual assistants, chatbots, speech processing, personalized offer in real time are just some of the possible uses of Artificial Intelligence that change the quality of customer experience. However, many companies are afraid of the costs associated with the implementation of new technologies, and these fears are reinforced by the possibility of failure or lack of interest in the novelties on the part of customers.

Customer Experiences in the Age of Artificial Intelligence researcher

A novel approach to understanding how the integration of AI-based services can impact the customer experience is described in the article “Customer Experiences in the Age of Artificial Intelligence”. Researchers from Royal Holloway, University of London decided to break apart the customer experience into its constituent parts. The study used an analysis of nearly 450 customers of one beauty company. The beauty company provided its customers with technology that allowed them to select cosmetics based on the customer’s beauty type. This was the first step towards the current trend of technological revolution. The virtual assistant compares the customer’s selfie with a database of clinically evaluated photos and accurately classifies the signs of skin aging, selects the color of foundation or the most suitable shade of lipstick – and does so with up to 95% efficiency. The resulting customer experience data was validated using structural equation modeling. Based on trust and commitment theory, they measured how AI service quality, including convenience and personalization, affects customer experience, highlighting the importance of trust, commitment, and some customer churn as mediating elements.

Measuring the impact of AI on customer experience

The key to success in AI business is to understand the mechanisms in the minds of customers and design the buying process according to their preferences. Within a single brand, even individual customer segments can differ significantly from each other. The same service based on AI will be perceived differently by young consumers and differently by the 60+ segment. Therefore, the starting point should be the customer and their needs. Once customers have their first experience with a brand, their commitment to maintain an ongoing relationship has a positive impact on the quality of the experience. However, it is not enough to implement AI to generate additional profits. So the question is, how to do it effectively?

The proposed model illustrates the relationships between the components of Customer Experience – it shows how the individual factors influence each other, highlighting the role of trust and the necessary cancellations of customers (sacrifices). The results of the study show that trust plays a key role in AI-enabled experiences.

Key elements

From a consumer perspective, earning trust is a major challenge in AI-based services. Consequently, a higher level of trust in the brand and their technology improves the customer experience. It is important for vendors to clearly communicate their achievements and subsequent security certifications to customers. The more convinced the customer is, the more willing they are to commit to a long-term relationship with the brand. Because of the sensitivity of handling customer data, the relationship between brand trust and customer experience is particularly prevalent just in the context of digital experiences.

Trust in a brand, the technologies and processes it uses, and the purpose for which it collects and analyzes customer data increases when the service is more convenient in terms of time and location and offers better quality in terms of interface design, customer service reliability, and security. In this case, the convenience of the service indicates time and effort savings. An additional convenience is its ubiquitous availability from anywhere on earth. These advantages can prove to be significant to encourage customers to use the service. Convenience has been identified as a key advantage of AI-based solutions. It is important, however, for vendors to understand that increased convenience alone is not enough to overcome the sacrifices that customers must make to use the service.

Marketer challenges

Retail for the third decade of the 21st century must include the customer in the creative process. Customers expect this because the result is personalized service and a more relevant product. Personalization is important in building a positive customer experience. In the context of the customer experience with a personalized service, consumers may feel less sensitive about what they are giving up (sacrificing), plus they are more likely to engage in interactions with the brand. The relationship engagement achieved through personalized experiences leads customers to believe that there are no alternative brands that provide similar benefits.

However, solutions based on Artificial Intelligence involve a high degree of automation in the customer service process. For the customer, this means no contact with a real consultant, which can prove to be a big obstacle, especially for customers who have not used new technologies so far. Retailers should strive for a balanced approach to human interaction, for example through carefully personalized experiences accompanied by a well-trained customer service team. This will increase engagement with the customer, which the study found has a significant impact on how consumers view their AI experience. Additionally, the number of steps a customer must go through during their shopping journey is determined by the requirements of the technology, not the needs of the user – this comes with some imposed limitations. In order to make a purchase, the customer gives up something else to use the service (sacrifices something), such as having to share more data about themselves, feeling a loss of control, loss of privacy, or lack of human interaction. Each subsequent opt-out or limitation on the part of the consumer, can result in a weaker experience.

Summary

Customer experience is recognized as a way to differentiate a company from its competitors. Unlike price, quality or product availability, which are increasingly undifferentiated in the marketplace, customer experience creates strong, lasting relationships.  The ability to diagnose the key parameters influencing the purchase experience and then understand and skillfully leverage them contributes to maximizing company profits.

The study demonstrates an innovative perspective on customer experience. It contributes to a better understanding of customer behavior related to AI. Taking trust and other modifiers into account, through the above analysis, a beauty brand could assess which metrics it should improve to optimize the customer experience by as much as a few to several percent.

Well-created consumer profiles help increase sales, but there is no doubt that marketers often do not even realize they are not using the full potential of the information about their consumers. So how do you use this data, build an effective loyalty program and mark out in the market? Show us your data and we will tell you who your customers are – we will implement an effective program adapted to consumers’ needs and expectations.

Loyalty programs are useful to optimize company costs and identify a significant portion of customers, allowing you to get to know your consumers, personalize offers, and improve the overall brand experience. There is certainly no one-size-fits-all loyalty program, so every decision should be well thought out and supported by advance analysis. At Loyalty Point, we have developed a universal way to holistically analyze the feasibility of implementing and matching loyalty program features.  

Knowledge instead of intuition

Loyalty Point’s proprietary methodology called ‘Raport Otwarcia’ is a process that we have implemented more than twenty times so far. This approach has proven successful in a wide range of industries, from NGOs to large multinational corporations.

There are two key stages in ‘Raport Otwarcia’:

1. pre-implementation analysis
2. strategy development based on the insights gained during the analysis

The process is very methodical, and in addition to analyzing the data available in the organization, it also involves reviewing available IT tools, team structures and processes.

Our approach is characterized by partnership and result-oriented attitude what is very important. We are committed to building long-term relationships with our customers, so ‘Raport Otwarcia’ is just an introduction to cooperation, not the culminating project. That causes us to look in the long term at the ROI of the recommended actions and it happens that we advise the customer against implementing a loyalty program based on classic solutions. There are situations when we recommend the setup of a Communication Platform, where the main element is providing consumers or other groups with relevant information, and the loyalty mechanisms are in the background of our actions.

During the pre-implementation analysis firstly we focus on the available data. These are transactional data, data related to interaction, as well as many sources available, such as purchasing power, data from the Statistics Poland, information on client’s media and advertising spending and about his competitors, and a number of other information from the market. We also look at a client’s previous marketing activities, analyzing their effects and benchmarking them against best market practices in particular categories.

Importantly, ‘Raport Otwarcia’ is equally effective for entities that are just considering the implementation of a program as it is for those that already have a loyalty program in place.

Loyalty program – what do you know about your customers?

The customer base was used to send SMS messages informing about seasonal discounts. There was no personalization or segmentation was used. The company’s approach was limited to the belief that consumers were only interested in discount offers and cut prices. As the base grew in size, the cost of promotion and direct communication grew faster than ROI. A change in approach was needed. There is where ‘Raport Otwarcia’ came in.

In order to verify the customer base, we decided to analyze contents of the shopping baskets and transaction data. We verified which products customers choose (women’s, men’s, children’s), what products they combine them with and when they shop (during sales or a new collection). Ultimately, we were able to identify 50 key customer characteristics. Thanks to the segmentation of the customer base we were able to describe precisely the behavior and shopping habits of different groups. Some customers did indeed decide to buy products at discount prices, but there was also a large group of people who did not use the promotional offer at all. They preferred novelties or the highest quality products.

The key role of employees

In retail, it is very important to analyze the actions of shop assistants, as they are the ones who have direct contact with customers. Employees should be ambassadors of the program, promoting and encouraging customers to register transactions with loyalty cards. Conducting an audit among customer service allows us to find out how much employees know about the program strategy and promote it among customers. It is relatively easy to show how much an organization loses from the wrong attitude. One such example is the % of loyalty card transactions. Differences between individual shop assistants sometimes reach several dozen percent. The result is that we cannot attribute some of the transactions to a participant, so we lose of a large portion of knowledge that could learn recommendation models and communication paths.

In this case Thanks to the Opening Report, we were able to develop an approach to personalize offers taking into account all consumer groups of the brand. Understanding customers and differentiating communications proved to be the turning point for the loyalty program. Without an in-depth analysis, the company had an incomplete image of its customers’ profiles, making communication unattractive for many. In addition, it was possible to optimize the store’s offer in terms of customer preferences. The result was a 20% increase in sales performance on key campaign indicators. As it turned out, the client without data science analysis did not realize the potential of the data they had.

‘Raport Otwarcia’ is also a helpful tool in optimizing other areas of the organization. During the pre-implementation analysis we try to get to know the structure of the company as well as possible, therefore we talk to various departments (marketing, sales, finance, IT, complaints deparment) in order to gain as full knowledge as possible about the barriers and potential of processes and tools.

As a result of the above activities, the recommendation of strategy and future actions will be based on reliable knowledge that a given company possesses, and not only on benchmarks and trends. Combined with our know-how and experience, ‘Raport Otwarcia’ will be succeed.