How AI is transforming rewards and incentive programs in the US

Rewards and incentives are powerful tools for motivating and engaging customers, employees, and business partners. However, traditional rewards and incentive programs often suffer from low participation, high costs, lack of personalization, and limited impact.

Artificial intelligence(AI) is enabling new ways of designing, delivering, and optimizing rewards and incentives for various stakeholders. The article will provide examples and best practices from leaders in the industry, as well as discuss some of the benefits and challenges of using AI for rewards and incentives. The focus of the article is on non-cash rewards and incentives, where AI can provide greater value-added in terms of providing end-users with more memorable and meaningful experiences, and a greater value for money for businesses, also helping them to attract and retain customers and/or employees.

Market size of the rewards and incentive industry in the US

EDC estimates that the rewards and incentive industry in the US is a huge and growing market, with an estimated value of $541 billion in 2023.

This includes reward points, gift cards, trips and travel, merchandise, and experiential rewards that are used to reward sales staff, employees, channel partners, and customers.

The rewards and incentive industry in the US is highly diverse and dynamic, with different industries and customer segments having different needs and preferences for how they are rewarded and incentivized. According to Sales and Marketing Management, a leading authority for executives in the sales and marketing field, among businesses that use incentives the most common are gift cards (used by 80%of businesses that adopted a reward and incentive program), followed by program reward points (55%), merchandize (50%), experiential rewards (45%), and incentive travel (40%).

Examples of leading businesses leveraging AI to enhance their rewards and incentive programs

AI is a hot topic, with ChatGPT showcasing the progress of generative Large Language Models (LLMs), which are AI models specifically designed to understand and generate human language for everyday use, but AI is not new, and forward-thinking businesses have been working with advanced algorithms and improving the way they operate for years.

One application for AI has been within companies’ rewards and incentive programs, to segment and personalize rewards based on individual preferences, behaviors, and goals, thus increasing engagement and loyalty. We are seeing this across different sectors, such as retail, hospitality, entertainment, healthcare, and financial services, with some of the key examples being:

• Starbucks: Widely regarded as one of the most sophisticated and successful customer reward programs, Starbucks Rewards leverages AI to analyze customer data (such as purchase history) and provide personalized offers and recommendations (such as favorite drink discounts or exclusive promotions) to program members. The loyalty program also uses AI to send customized emails and push notifications to members, such as reminders to redeem rewards before they expire.
• Sephora: Sephora’s loyalty program, called Beauty Insider, uses AI to analyze customer data such as purchase history, browsing behavior, and social media activity, to provide customized product recommendations and offer personalized beauty advice. Furthermore, the AI-powered chatbot assists program members in real-time with product recommendations, new product arrivals, and also directly redeem rewards.
• PayPal: PayPal uses AI to offer personalized and dynamic rewards and incentives to its customers, such as cashback, discounts, coupons, and loyalty points, based on their preferences, behaviors, and transactions. PayPal also uses AI to optimize its rewards and incentives programs by testing and analyzing different variables and scenarios, and adjusting and improving the rewards and incentives accordingly.
• Hilton: Hilton utilizes AI in its Hilton Honors loyalty program to enhance guest experiences and drive engagement. Through AI-powered analytics, Hilton creates detailed guest profiles using data such as past stays, preferences booking patterns, and demographics to offer personalized rewards, room upgrades, and other amenities. Additionally, Hilton uses AI chatbots to provide personalized assistance and recommendations to loyalty program members.

None of these examples are new, they have been developed and improved upon over time, and have gathered large volumes of data to train and iterate algorithms to perfect recommendations and operations of the AI.

Benefits of using AI for rewards and incentives

AI, when used correctly, can help businesses solve common pain points and innovate how rewards and incentives are offered to customers/employees/partners. Some of the most common benefits that AI can offer when applied to rewards and incentives include:

1. Personalization: AI can help design meaningful, individualized rewards and recognition for every employee and customer, based on their preferences, behaviors, and goals. For example, AI can analyze the data from loyalty programs, surveys, social media, and other data sources to create personalized reward profiles for each customer, and then offer them relevant rewards such as discounts, freebies, or experiences that match their interests.
2. Efficiency: AI can streamline the administrative processes of managing rewards and incentive programs, such as tracking performance, delivering feedback, and managing budgets. For example, AI can automate the calculation and distribution of rewards based on predefined criteria and rules, reducing errors and delays. AI can also provide real-time feedback to employees, based on their performance data and goals, and suggest appropriate rewards and recognition to motivate them.
3. Innovation: AI can also help reward and incentive providers adapt to market trends and consumer needs in real-time, by analyzing data and generating insights. For example, AI can help identify emerging customer segments, preferences, and behaviors, and then design and test new reward offerings and strategies to attract and retain customers/employees.
4. Customer service: AI can streamline the customer experience by providing immediate and personalized assistance through chatbots and voice assistants that can generate natural, human-like responses. For example, AI can use generative models to understand customer’s intent, context, and emotions, and then offer relevant solutions, suggestions, or feedback. This can help improve customer satisfaction by making the experience more seamless and user-friendly. The more chatbots learn over time, the more efficient and intelligent they can answer queries. Over time, this can reduce costs, increase efficiencies, and personalize interactions, all while being available 24/7.

Challenges of using AI for rewards and incentives

AI is a rapidly evolving field that poses many challenges for regulators and policymakers. Businesses that use AI as part of their rewards and incentive programs need to be aware of the potential risks and ethical issues involved and take proactive steps to ensure their programs are compliant, fair, and transparent. Some of the key considerations for businesses implementing AI should revolve around:

• Data quality and privacy: AI relies on large amounts of data to learn and improve, but the quality and privacy of the data are crucial for the accuracy and trustworthiness of the AI. There is a need to ensure that the data used for rewards and incentives are reliable, relevant, and secure, and that they comply with the relevant regulations and ethical standards, such as the California Consumer Privacy Act (CCPA) and General Data Protection Regulation (GDPR).
• Bias and fairness: AI can sometimes introduce or amplify bias and unfairness in rewards and incentives, due to the limitations or assumptions of the algorithms, models, or data. Businesses must monitor and mitigate the potential bias and unfairness of the AI, and ensure that rewards and incentives are inclusive, diverse, and equitable.
• Human-AI interaction and communication: AI can sometimes be complex, opaque, or unpredictable, making it difficult for humans to understand, interact, or communicate with the AI. Businesses need to ensure that the AI they use for rewards and incentives is transparent, explainable, and accountable.
• Cost: Whilst AI can have big upsides for a business’ rewards and incentive program, organizations need to be aware of the costs associated with implementing AI. These can be broadly categorized into:

              - Hardware: One of the biggest costs for businesses, as AI algorithms require specialized hardware that can handle high volumes of data and computations  

              - Software: These are costs relating to data collection, analysis, and processing, which scale to the size of data utilized by the AI

              - Implementation: These types of costs refer to hiring data scientists, machine learning engineers, or software developers to maintain the technology running

How to successfully leverage AI within a rewards and incentives program

Businesses wanting to use AI for rewards and incentives effectively need to adopt a strategic and holistic approach, considering the following factors:

1. Business objectives and value proposition

• Define business objectives and value proposition for using AI for rewards and incentives, and align them with the overall vision, mission, and strategy  
• Have proper methods to measure and evaluate the outcomes and impacts of using AI for rewards and incentives, to demonstrate the value and return on investment to stakeholders, such as:

             - Setting clear and measurable goals (productivity, retention, satisfaction, and loyalty)  

             - Collect and analyze data (employee surveys, feedback, reviews, and performance records

2. Customer, employee, and partner needs and expectations

• Understand the needs and expectations of customers/employees/partners for rewards and incentives, and design and deliver rewards and incentives that meet or exceed them  
• Solicit and incorporate feedback and suggestions from customers/employees/partners, and continuously improve the rewards and incentives program based on them

3. AI capabilities and limitations

• Assess the current and desired AI capabilities and limitations for rewards and incentives, and identify the gaps and opportunities for improvement  
• Select and use the appropriate AI tools and techniques for rewards and incentives, and ensure that these are supported with the necessary resources, skills, and infrastructure with the organization

4. Ethical and legal implications

• Consider the ethical and legal implications of using AI for rewards and incentives, and adhere to the relevant principles, standards, and regulations  
• Ensure that AI is used in a responsible, ethical, and legal manner, and that it is in respect, and it protects the rights and interests of customers/employees/partners

Conclusion

AI is not only transforming the way we work, but also the way we reward and motivate people. Businesses with larger volumes of data are at an advantage in leveraging AI tools to offer more personalized recommendations, gamified experiences, and create new opportunities to engage with customers, employees, and business partners. Businesses that use AI strategically will have an edge in an increasingly crowded and competitive market, while those that ignore it will fall behind.

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The content of this article does not reflect the official opinion of Edgar, Dunn & Company. The information and views expressed in this publication belong solely to the author(s).