Digital transformation has gone beyond what we once imagined; we are entering the era of ‘machine customers.’ A futuristic vision that promises to redefine the interaction between technology and commerce as we know it. At the heart of this radical change lies the pioneering work of Don Scheibenreif and Mark Raskino, “When Machines Become Customers,” which not only captures our imagination but also challenges our traditional understanding of markets and the economy.
This term, coined by visionaries Don Scheibenreif and Mark Raskino in their influential work “When Machines Become Customers,” describes a phenomenon where machines, powered by artificial intelligence and machine learning, make purchasing decisions and conduct transactions without human intervention. Scheibenreif and Raskino predict that by 2030, up to a staggering 20% of business revenue will come from these autonomous entities. This not only redefines who the customer is but also how companies should structure their marketing and sales strategies. Read on to learn what a machine customer is and how it will impact businesses in the future.
What are Machine Customers?
Machine Customers represent a new paradigm in the e-commerce ecosystem. These digital entities, which operate autonomously, are intelligent systems capable of making transactions and purchasing decisions without direct human involvement. They function through sophisticated algorithms and artificial intelligence software, processing large amounts of data to execute purchase actions based on programmed logic and efficiency.
Characteristics of Machine Customers
Machine customers are characterized by their objectivity and lack of impulsiveness. Their decision-making process is data-driven and efficiency-oriented, which implies a shift in the approach to customer experience and service personalization. The trend toward sales automation and programming is accelerating, and companies that want to thrive must adapt quickly. Here are some distinctive characteristics of these non-human customers:
1. Objectivity in Decision-Making
Machine customers are not influenced by emotions or impulses. Their decisions are based on data analysis, efficiency, and logic, making them predictably objective in their choices.
2. Lack of Impulsiveness
Unlike humans, these customers lack impulsiveness. They are not subject to impulse buying or influenced by emotionally charged marketing strategies.
3. Data-Driven Decision Process
They use large volumes of information and data analysis to make decisions. This includes real-time price comparisons, product quality assessments, and analysis of specific needs.
4. Efficiency-Oriented
They prioritize efficiency both in the purchasing process and in the use of the acquired product or service. This may mean a preference for automated digital solutions or products that maximize operational efficiency.
5. Adaptability and Learning
Equipped with machine learning capabilities, machine customers can adapt their purchasing patterns based on new information or market changes, requiring companies to be equally agile and adaptable.
Impact of Machine Customers
These systems, which operate independently of human intervention, are characterized by their ability to execute purchases and make decisions based solely on algorithmic logic and predefined criteria. Their importance lies in several key capabilities:
- Operational efficiency: With these new customers, there is a significant acceleration in buying and selling operations, leading to reduced operational costs and considerable time savings.
- Personalized experiences: These entities enable dynamic adaptation of offers, adjusting to specific needs and preferences, something previously achievable only through human interaction.
- Market expansion: They have the unique ability to explore and create market niches previously inaccessible or nonexistent for human consumers.
Business Transformation Driven by Machine Customers
This new era of customers, equipped with Artificial Intelligence, Machine Learning, Natural Language Processing, and Computer Vision capabilities, promises to revolutionize not only productivity and efficiency but also open doors to new markets and significantly enhance customer satisfaction. These technological advances allow Machine Customers to process information, make autonomous decisions, adapt their behaviors through data analysis, and interact more human-like in the digital environment.
In response to this transformation, companies face the challenge of adapting and evolving. To thrive in this new environment, it is essential to consider a series of strategies aimed at maximizing the opportunities presented by Machine Customers:
Facilitate Access to Information
Ensure that information about products and services is fully accessible through machine-friendly interfaces, such as open APIs, and remove barriers that hinder access.
Incorporate Them into the Digital Strategy
Machine Customers should be an integral part of the e-commerce strategy, recognizing their presence across all platforms, from social media to customer relationship management systems and chatbots.
Promote Interdepartmental Collaboration
Successful adaptation requires synergy between different areas of the company, such as sales, marketing, IT, supply chain, and analytics, to ensure an agile and coordinated response to the demands of these autonomous customers.
Training and Specialized Knowledge
It is crucial that personnel are trained not only in the technological tools that enable interaction with these customers but also in understanding the algorithms and logic that govern their decisions and behaviors.
Adapt Customer Service
Develop capabilities to identify and meet the needs of Machine Customers, who will require a different type of service, focused more on efficiency and accuracy than traditional human interaction.
The emergence of machine customers is a natural evolution at the intersection of technology and commerce. Companies that anticipate and adapt to these changes will not only survive but thrive, leading the forefront of a revolution in customer behavior. The key lies in preparation and the ability to adapt to a constantly changing business landscape, where the traditional boundaries between humans and machines are becoming increasingly blurred.
