Machine customers: Preparing for the future of nonhuman economic actors

As we advance into a complex digital future dominated by artificial intelligence and connected technologies, a new type of customer is emerging: the machine customer. These nonhuman economic actors are poised to revolutionize the way businesses operate, interact, and transact, so understanding the intricacies of machine customers is crucial for businesses aiming to stay ahead. This blog explores the characteristics, data management needs, and industry impacts of machine customers, delving into the strategies businesses can adopt to build trust with these nonhuman economic actors, ensuring compliance with regulatory frameworks and ethical standards.

Understanding machine customers

Machine customers are a new class of customers that operate autonomously, driven by advanced AI systems, IoT devices, and connected technologies. These machines can make decisions, purchase products, and interact with businesses without direct human intervention. Machine customers are characterized by their ability to analyze vast amounts of data in real-time, make informed decisions, and execute transactions autonomously. Examples include smart refrigerators placing grocery orders, autonomous vehicles booking maintenance services, and intelligent software purchasing digital assets or services.

Operating based on preset parameters, learned behaviors, and sophisticated algorithms, these machines make purchasing decisions that are often more predictable and efficient than those made by human customers. However, similar to human customers, they require specific management systems to handle their interactions, particularly concerning data use and consent.

Data collection and usage

Given the autonomous nature of machine customers, they generate enormous amounts of data, which can be used to optimize services and experiences. Managing this data, however, becomes a critical task for businesses. Data collection should be done in a way that aligns with privacy regulations such as GDPR, CCPA, and other international frameworks, ensuring that the information is stored, processed, and shared ethically.

Machine customers also require strong security measures to prevent breaches that could manipulate their decision-making processes. Businesses must ensure that machines’ data is protected, and the consent to use that data is clearly defined, both from the owners of the machine and the systems governing them. Maintaining a transparent data management policy is essential in building trust with both machine customers and their human counterparts.

Personalization and Customization

Machine customers introduce a new dimension to the way businesses provide personalized services. Just as human customers expect tailored offerings based on their preferences, machine customers will require personalization based on their programming and consent settings. Companies will need to shift from focusing on human-centric data to machine-centric data, optimizing their products and services for the preferences of these automated decision-makers.

For instance, a machine customer, such as an autonomous vehicle, may prioritize services like battery optimization or tire longevity when selecting a supplier, based on pre-configured preferences. Understanding these unique requirements will be key to gaining a competitive edge. Businesses that can offer products and services aligning with machine preferences will thrive, as long as they honor the consent settings built into these devices.

Compliance and trust

Trust remains crucial when dealing with machine customers. To ensure that machines operate within agreed-upon parameters, industries must adopt transparent practices, including proper consent management and clear guidelines on how customer data is handled. As machines will often act as proxies for human owners, businesses must ensure that they handle consent diligently, ensuring that the machine’s transactions align with both legal and ethical guidelines.

The industries that build trust with machine customers will gain a significant competitive advantage. Transparency about how machine data is used, along with easily accessible consent management options, will be fundamental in maintaining trust and long-term customer loyalty.

Adapting business models

Consent Management

As machine customers become more common, businesses will need to adapt their operations to accommodate this shift. One of the most important changes will involve implementing Consent Management Platform (CPM) designed for machine interactions. These systems will allow businesses to manage and track the preferences and consent of machine customers in compliance with legal standards.

CPMs can act as a centralized hub that records the permissions granted to machines by their owners, ensuring that each transaction or interaction is compliant with the necessary regulations. These systems will be crucial for industries like healthcare, finance, and retail, where sensitive data and stringent privacy regulations are involved.

Preference Management

Understanding the preferences of machine customers is just as vital as understanding human preferences. Preference management solutions can help businesses track and analyze machine behavior, allowing for better customization of services. These solutions not only improve the machine’s experience but also optimize business offerings.

For example, a smart home device that orders groceries will have specific preferences based on the user’s habits. Businesses that can interpret and cater to these preferences, while respecting the machine’s consent settings, will improve customer satisfaction and retention. The ability to manage preferences seamlessly will be a major factor in gaining the loyalty of machine customers.

Future considerations

Regulatory Landscape

As the concept of machine customers evolves, so will the regulatory landscape. Governments and regulatory bodies are expected to introduce frameworks that govern how businesses interact with autonomous systems, focusing on consent, data security, and transparency. Staying compliant will require businesses to adopt systems that can handle both the ethical and legal requirements of machine transactions.

Future regulations may also set stricter guidelines on how machine customers interact with financial markets, healthcare systems, and other sensitive sectors, given the potential for ethical concerns. Preparing for these shifts in regulations by adopting a consent and preference management platform which will enable businesses stay ahead of compliance challenges.

Ethical implications

The growing autonomy of machines raises several ethical questions, particularly around decision-making and consent. Ensuring that machines are programmed to operate within ethical standards is essential. This includes considerations such as ensuring machines do not engage in exploitative behaviors, are not manipulated by external actors, and act in a way that reflects the values and interests of their human owners.

Businesses must carefully consider how machine autonomy impacts their operations, from respecting privacy laws to ensuring that the decision-making processes embedded in these machines are aligned with ethical standards. Ultimately, companies that adopt a thoughtful approach to consent and ethics will lead the way in creating a responsible ecosystem for machine customers.

How can businesses build trust with machine customers?

Transparency

Clear data practices: Ensure that data collection, storage, and usage policies are transparent. Clearly communicate how data will be used and obtain explicit consent from the machine’s human owners.

Accessible information: Provide easy access to information about how machine data is handled and the measures in place to protect it.

Security measures

Data protection: Implement strong security protocols to protect machine data from breaches and unauthorized access.

Regular audits: Conduct regular security audits to identify and address vulnerabilities.

Consent Management

Consent Management Platforms (CMPs): Use a CMP like Cassie to manage and track the preferences and consent of machine customers. When choosing, ensure that the platforms has the ability to be compliant with legal standards.

Owner permissions: Record and respect the permissions granted by the machine’s human owners, ensuring all interactions are compliant with these settings.

Ethical practices

Ethical programming: Ensure that machines are programmed to operate within ethical standards, avoiding exploitative behaviors and manipulation by external actors.

Alignment with values: Program machines to act in ways that reflect the values and interests of their human owners.

Personalization and customization

Tailored services: Offer personalized services based on the machine’s programming and consent settings. Understand and cater to the unique preferences of machine customers.

Preference Management: Use preference management solutions to track and analyze machine behavior, optimizing services accordingly.

Compliance with regulations

Stay updated: Keep abreast of evolving regulations governing machine interactions, focusing on consent, data security, and transparency.

Adopt best practices: Implement systems that handle both the ethical and legal requirements of machine transactions.

Building long-term relationships

Trustworthy interactions: Ensure that all interactions with machine customers are trustworthy and transparent.

Customer loyalty: Build long-term loyalty by consistently respecting consent settings and providing high-quality, personalized services.

Final thoughts

As we move towards a future where machine customers become more prevalent, businesses must adapt to this new paradigm. By understanding the unique needs and behaviors of machine customers, implementing a consent and preference management platform, and staying ahead of regulatory changes, companies can position themselves for success in this evolving landscape.

To delve deeper into the implications and strategies for engaging with machine customers, we highly recommend exploring the Gartner Market Guide for Digital Marketing 2024. They hype cycle provides valuable insights and recommendations for preparing your business for the future of nonhuman economic actors.