Feature
The Gist
- Machine customers transform business. Machine-driven transactions are reshaping customer relationships.
- Autonomous purchasing power. AI and IoT enable machines to autonomously order supplies and services.
- Adapting to non-human clients. Businesses must innovate to cater to algorithm-driven machine customers.
A new player has recently emerged, reshaping the dynamics of business interactions: the Machine Customer. This intriguing concept marks a significant shift in how we understand customer relationships in the digital age. No longer confined to human interactions, businesses are increasingly catering to machine-driven decisions and transactions. A recent Gartner report revealed that CEOs believe by 2030, up to 20% of their companies’ revenue will come from machine customers. Understanding the role and impact of the machine customer becomes crucial for businesses aiming to thrive in a rapidly changing digital ecosystem. This article will explore how artificial intelligence, automation and interconnected devices are transforming the traditional customer profile.
The Dawn of the Machine Customer Era
The idea of a machine acting as a customer has been speculated about in conjunction with emerging technologies for several decades. As early as the 1980s and 90s, visions of "smart" internet-connected devices and autonomous vehicles fueled ideas that machines may one day purchase goods and services to replenish their own supplies and components.
However, these were mostly forward-looking thought experiments. Practical applications did not begin emerging until the 2000s and 2010s with the rise of advanced artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT). Companies began to conceptually explore how connected devices such as assembly line equipment and even home appliances could leverage automation and data to order their own maintenance services or replacement parts.
Over the past 5-to-10 years, the vision of the machine customer has gotten closer to reality thanks to AI/ML advancements, 5G connectivity enabling complex autonomous device coordination, and blockchain supporting machine-to-machine transactions. Use cases are still fairly limited, but some examples today include self-driving cars autonomously paying tolls or charging stations and industrial machines coordinating maintenance check-ups and spare parts orders.
As algorithms, robotic technologies, and device interconnectivity continue rapidly developing, the machine customer concept is beginning to proliferate across many industries, enabling fully automated, self-maintaining, and likely self-improving systems of the future. The machine customer space is still emerging but shows immense promise for unlocking efficiency and capability gains.
Two pioneering examples of the machine customer concept are HP Instant Ink and Amazon Dash Replenishment, where devices autonomously make purchase decisions and execute transactions.
HP Instant Ink represents a significant shift in how customers interact with printer ink purchases. Instead of the traditional model where customers manually monitor ink levels and purchase replacements as needed, HP Instant Ink-enabled printers monitor their own ink usage. When the ink levels are low, the printer automatically orders ink before it runs out. This service not only offers convenience but also allows for more efficient ink usage and cost savings, as customers pay a subscription fee based on the number of pages printed, not cartridges used. It's an early example of how connected devices can take over routine purchasing tasks, seamlessly integrating product replenishment into the customer's life.
Amazon Dash Replenishment takes the concept of the Amazon Dash button — which allows for the ordering of specific products with a simple button press — a step further by integrating it directly into appliances and devices. For example, a washing machine with Dash Replenishment can automatically order laundry detergent when it's running low. Similarly, a smart coffee maker can order beans or pods when they're needed. This system works in conjunction with IoT to streamline the process of replenishing frequently used items.
Related Article: How to Handle Machine Customers With Contact Center Adaptation
The Impact of Machine Customers on Businesses
The growing prevalence of machine customers signals a significant trend in business, marking a shift in how customer interactions and transactions are conceptualized and managed. This development is very likely to have a profound and multifaceted impact on businesses across industries.
One of the most striking implications of this shift is the emergence of new revenue streams. The advent of machine customers, capable of autonomous purchasing decisions, opens up opportunities for businesses to develop products and services tailored to these automated processes. This could include innovations such as automated restocking systems or subscription-based models similar to HP Instant Ink that are specifically designed for machine-based purchasing, offering businesses new avenues for growth and profitability.
However, this shift also necessitates a rethinking of traditional marketing and sales strategies. With purchasing decisions now being made based on algorithms, data analysis, and programmed criteria, businesses must adapt their approaches to cater to a more data-driven and technically sophisticated customer — the machine. Businesses will now be able to add yet another sales model to the list: B2B, B2C, D2C, B2M, and now, B2MC. This evolution calls for a strategic pivot to methods that resonate with algorithmic decision-making processes.
Alok Kulkarni, co-founder and CEO at Cyara, an AI-powered CX assurance platform provider, told CMSWire that the emergence of machine customers in 2024 will introduce a new dimension to the customer experience, especially in the support realm. "Organizations will need to adapt their support strategies to accommodate non-human economic actors. This may involve creating specialized interfaces and communication channels designed to interact with machine customers,” said Kulkarni. “Automation will play a crucial role in handling routine transactions and inquiries, allowing human agents to focus on more complex issues that may arise in interactions with machine customers."
Gartner’s recent predictions for 2024 and beyond speculated that by 2025, over 25% of sales and service centers in large businesses will be dealing with calls from machine customers. The report emphasized that machine customers will force a reshaping of key functions such as supply chain, sales, marketing, customer service, digital commerce and customer experience. Daryl Plummer, distinguished VP Analyst at Gartner, said in the report that he anticipates that machine customers will require their own sales and service channels because they make transactions at high speeds and the volume of decision variables they use far exceed human capabilities. “Machine customers will require different talent, skills, and processes that may not exist in a human-customer focused division,” said Plummer.
The rise of machine customers is spurring innovation in product and service design. Brands are prompted to ensure that their offerings are not only compatible with machine-driven purchasing processes but also cater to the demand for more standardized and interoperable products. This trend is pushing businesses to rethink how they design, develop, and offer their products and services.
Another critical area impacted by the rise of machine customers is data management and analytics. As machine customers rely heavily on data for decision-making, the role of robust data infrastructure and advanced analytics capabilities becomes more pronounced. Businesses must invest in and prioritize these areas to effectively cater to and benefit from these new types of customers.
The concept of customer relationship management (CRM) will also be forced to undergo a transformation. In the era of machine customers, CRM is less about traditional human-centric communication and more about managing data exchanges and algorithmic interactions. This new paradigm challenges businesses to reimagine how they build and maintain customer relationships.
Additionally, the integration of machine customers into the business ecosystem brings with it a host of ethical and legal considerations, particularly concerning data privacy, security, and the responsibility associated with decisions made by machines. Businesses must navigate these challenges with caution, ensuring compliance and ethical practices in their interactions with machine customers.
"Organizations must heighten security measures to accurately identify and authenticate machine customer requests to guard against potential deep fakes, as building trusted relationships with human customers while ensuring efficiencies for machine customers will be paramount,” said Kulkarni. “Serving machine customers will require organizations to take a proactive approach that involves developing APIs and integration capabilities for seamless communication, alongside creating self-service options tailored specifically for machine customers to enhance their overall experience."
Operational adjustments are yet another critical aspect of this shift. To accommodate the speed and efficiency that machine customers demand, businesses may need to overhaul their supply chains and operational processes. This includes faster order processing, real-time inventory updates, and a more automated approach to logistics.
Finally, businesses that effectively integrate and cater to machine customers could gain a significant competitive edge. Particularly in industries where machine purchasing becomes prevalent, being at the forefront of this trend could be a key differentiator, offering businesses a unique position in the market.
Related Article: 4 Ways AI, Analytics and Machine Learning Are Improving Customer Service and Support
The Future of Machine Customer Relationships
The impact of machine customers is compelling businesses to innovate, adapt their strategies, and invest in new technologies. Those proactive in responding to this shift are likely to realize significant market advantages and tap into new potentials for revenue and growth.
The evolving relationship between machine customers and businesses, propelled by technological advancements and shifts in consumer behavior, is set to redefine the concept of customer interaction. In the future, we can expect several transformative trends to emerge from this dynamic.
Machine customers are anticipated to gain increased autonomy in their purchasing decisions. Their role is likely to evolve from performing routine tasks, such as restocking supplies, to making more complex, independent choices. These decisions will be driven by sophisticated algorithmic analyses of factors such as quality, price, and customer preferences, marking a shift toward more nuanced and autonomous machine-driven purchasing.
Simultaneously, we'll see these machine customers becoming more deeply integrated into business supply chains. Using predictive analytics, their role will expand beyond mere purchasing agents to key players in optimizing inventory management, forecasting demand, and streamlining logistics operations. This deeper integration signifies a shift toward more efficient, data-driven supply chain management, where machine customers play a central role.
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As ML and data analytics continue to advance, machine customers will also become more skilled at offering personalized experiences. They will leverage historical data and predictive analytics to tailor purchases and interactions, leading to highly customized business-to-machine interactions. This trend points toward a future where personalization is not just a human-centric concept but also extends to machine interactions.
The relationship between human and machine customers is also set to become more collaborative. Humans will define the overarching goals and parameters, while machines execute tasks with efficiency and precision. This collaboration will lead to a more seamless and efficient overall customer experience, blurring the lines between human and machine roles in the customer journey.
Dimitris Sotiriou, director of product management at Twilio, a customer engagement platform provider, told CMSWire that in 2024, machine customers will interact more with contact center agents. Sotiriou envisions a future where B2B consumers, intrigued by AI’s capabilities to outsource their customer service needs, will seek out their own chatbots (i.e., “custobots”) that will interact with contact center agents on their behalf.
"This will be particularly true for following up on more basic customer service requests like refund tracking, order updates, etc. This means contact center agents, also using AI-powered chatbots to expedite requests on their end, will need to make sure they’re relaying the appropriate information to communicate with these chatbots and ensure they’re communicating back to the customer clearly."
It is not difficult to imagine a smart fridge that automatically replenishes its stock by ordering food items from Amazon Fresh as they run low. Configured with a preference for specific brands and quantities, the fridge streamlines grocery shopping by reordering staples such as bread, milk, eggs and butter. Amazon, familiar with the fridge's previous orders, efficiently processes these repeat orders, ensuring consistency in brand and quantity. Following each order, the account owner receives an email receipt, confirming the seamless transaction executed by the smart fridge. This integration of technology simplifies grocery shopping, making it a hassle-free, automated experience.
Marketing strategies will evolve to address the needs of both human and machine decision-makers. This will involve a greater emphasis on leveraging data and creating content and campaigns that are optimized for machine interpretation and selection. As a result, marketing will become a more data-driven and algorithmically influenced domain.
The expansion of machine customers is also likely to extend into new markets and industries, influencing a broader spectrum of business activities and consumer interactions. This expansion will open new avenues for growth and innovation across various sectors.
Consider a smart home system integrated with a personal health and fitness tracker. This system, upon noticing a consistent increase in the user's physical activity, automatically adjusts the home's food inventory. It orders high-protein snacks and healthy meal ingredients from a partnered online grocery service. The system takes into account the user's dietary preferences and allergies, ensuring the ordered items align with their health goals. For instance, if the user starts training for a marathon, the system might order energy bars, electrolyte drinks and lean proteins. The user receives a notification for approval before the order is finalized, and once confirmed, the items are delivered to their doorstep, facilitating a healthier lifestyle through the seamless integration of technology.
In a B2B scenario, consider a food warehouse equipped with an intelligent inventory management system. This system is connected to the inventory systems of its clients, such as a Walmart store. When the system detects that certain products are running low at the store, it automatically triggers a replenishment order. For instance, if the Walmart store is nearing depletion of a popular cereal brand, the warehouse's system, recognizing this through real-time inventory data, initiates an order for that specific cereal. The system considers Walmart's sales data, seasonal trends, and upcoming promotions to determine the optimal quantity for reorder. Once the order is processed, it is automatically prepared for shipment, ensuring that the Walmart store maintains a consistent stock level without manual intervention. This B2B machine customer interaction streamlines the supply chain, reduces the risk of stockouts, and optimizes inventory levels for both the warehouse and the retail store. This is not far from the current reality, as Walmart is already using AI, RFID and robotics for inventory management.
The rise of machine customers will create new opportunities for partnerships and collaborations. Businesses will seek to leverage the capabilities of these systems to enhance efficiency, drive innovation, and improve customer satisfaction.
Final Thoughts
The future of machine customers and their relationship with businesses is poised to be characterized by greater autonomy, deeper integration into business operations, enhanced personalization, and evolving ethical and regulatory practices. Businesses that adapt and innovate in conjunction with these changes will be well-positioned to capitalize on the opportunities presented in this new era of customer interaction.
