Perspective: Responsible AI for Pricing
Buyers trust algorithms more than people – Responsible AI for pricing means adopting practices that sustain and enhance this trust.
According to a recent survey by EY, even though only 22% of consumers reported having a good understanding of AI, three in four (77%) are neutral or comfortable with AI being used to improve purchase experiences.
As companies work to build consumer trust, AI touchpoints become opportunities to build and strengthen that trust. As EY says, “in the age of AI, touch points become trust points.”
This survey is further supported by PROS research. In 2019 and 2021, PROS collaborated with Hanover Research on an independent study of B2B buyer behavior. Hanover surveyed over 1,000 B2B buyers on their perspectives regarding algorithmic pricing. That is, what are their views on and preferences for suppliers that use algorithms as a basis for price setting?
We know that consumers are increasingly exposed to algorithmic dynamic pricing – but what about B2B? Do they embrace this practice by suppliers, or do they prefer the thrill of the high-stakes negotiation dance of price determination that has been predominant since the beginning of commerce?
In fact, B2B buyers have an inherent affinity for suppliers that use algorithms for price determination. That data shows that B2B buyers trust the objectivity and fairness of algorithms which overcome the typical obfuscation of people negotiating price.
However, the potential for AI algorithms to make pricing efficient and optimized does not come without the need for vigilance. It is incumbent on companies to maintain and enhance the trust in AI for pricing. So how can this be achieved?
The Trifecta of Trust:
In the realm of B2B pricing, Responsible AI ensures that pricing strategies are fair, transparent, ethical, and aligned with legal frameworks. It prevents discrimination, protects consumer privacy, and promotes long-term trust in pricing systems and brands.
B2B Businesses Must Uphold Responsibilities
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Legal Compliance: Is the AI pricing being adopted in accordance with national and local laws? Does it respect consumer protections? Does it foster, instead of hinder competition? Does it ultimately benefit consumers?
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Shareholder Value: Are AI pricing strategies maximizing shareholder value without harming current and future customers? Are they prioritizing short-term gains over long-term customer loyalty?
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Brand Integrity: Is AI pricing consistent with the company’s brand promise? Is there unfair differential treatment among customer segments? Does it risk negative brand positioning through perceived discrimination?
Companies that adopt AI for pricing need to consider these three factors to maintain and enhance the trust of their customers.
For this trust to be meaningful, transparency is essential. Buyers need clarity on the factors influencing AI-generated outputs and assurance that vendors are committed to Responsible AI practices. Such commitment not only enhances trust but also fosters long-term relationships, ensuring that AI serves ethical and beneficial purposes.
Accounting for Ethics, Bias, Privacy and Security
When implementing AI for pricing, it is crucial to address ethical and bias considerations to ensure fairness. This involves regularly auditing and updating algorithms to prevent any unintended consequences that may disadvantage certain customer segments. Additionally, transparency in how pricing decisions are made is essential to maintain customer trust.
Companies should clearly communicate the factors influencing AI-driven pricing and provide mechanisms for customers to challenge or inquire about pricing decisions. By prioritizing fairness considerations, businesses can ultimately enhance their reputation and customer loyalty.
As AI-driven pricing systems rely heavily on vast amounts of data, privacy concerns become paramount. For any consumer-related data, the data should be de-identified (i.e., cannot be associated with any particular consumer/reveal their identity). Data privacy laws should be strictly adhered to, and personal data should never be used to calculate pricing recommendations.
Companies must ensure that their data practices comply with privacy regulations such as GDPR and CCPA, safeguarding customer data against unauthorized access and breaches.
Transparency is key; businesses should inform customers about what data is being collected, how it is used, and the measures in place to protect it. Additionally, implementing robust data anonymization techniques can help mitigate privacy risks while still allowing AI systems to function effectively.
By addressing privacy concerns proactively, companies can build and maintain trust with their customers, ensuring that AI pricing practices are both effective and respectful of individual privacy.
Internal Stakeholders
Organizations, regardless of their sector, are typically risk-averse, especially when it comes to pricing. This is understandable. Pricing is an emotional decision; no salesperson wants to lose an opportunity over price.
Transitioning from human intuition or spreadsheet-based pricing to AI-informed decisions demands high accuracy. The AI-driven price must utilize the latest data, market trends, commodity prices, and competitive benchmarks to ensure optimal and relevant pricing for both the company and the customer.
When AI is inaccurate, salespeople lose faith in the system. They may revert to outdated practices that could yield short-term sales but ultimately harm the company’s revenue potential and profitability. This highlights the importance of informed pricing strategies and the real benefit of Responsible AI powering them.
Deploying AI-based pricing offers only one chance to make a strong first impression. Salespeople who consistently close deals with accurately priced offers build confidence in the AI's decision-making process.
Bottom Line
People trust algorithms more than humans. Responsible AI means maintaining and enhancing that trust.
By embedding Responsible AI principles into pricing strategy, companies can achieve a Price Advantage while enhancing consumer trust in the company’s brand. This Responsible AI must be transparent, internally and externally, to build confidence in the company’s approach to pricing.
Lastly, Responsible AI must be relevant to the market and environment in which it is being deployed. This requires companies to pick the best AI systems which can efficiently and accurately handle the many internal and external data factors and use algorithms that can practically translate these components into market- relevant prices.
Choosing the right AI and pricing strategy is critical. A poor choice can erode salespeople’s confidence, leading to wasted time and resources.
AI-based pricing is here – and here to stay. It has proven to be the most efficient and adaptive way of helping companies outperform in their market. However, companies need to ensure a responsible use of this powerful technology to reap the long-term benefit from it.