How to advise without manipulating or spying consumers

If artificial intelligence can be a consumer ally to recommend products to them, they should be handled carefully. Because if the consumer wants to be advised, he does not want to be manipulated. Nor do you feel spy on.

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Recommendation systems using artificial intelligence (AI) are no longer reserved for global giants such as Amazon or Netflix. They become available to companies of every size. For example, in France, a company as La Redoute Or CdiscountTake advantage of AI recommendations to personalize your clients’ shopping experiences online.

These investments indicate the importance of these technologies in the development of digital trade. According to the Statita report from 2024 (Statistics report 2024), These systems affect almost 35 % of online purchases showing them a significant impact on consumer behavior. However, French consumers are demanded and attached to their privacy. AND A survey conducted by PwC France He revealed that two -thirds of French consumers are worried about sharing their personal data. For buyers and other platform managers, it is necessary to success in drawing all the benefits of these fresh recommendation systems, without consumer anger.

Very strict frames

This challenge is emphasized by the strict legal framework in France and the European Union, in particular in the case of the GDPR (general provisions on data protection), DSA (Act on Digital ServicesDSA) and the exploit of consent management platforms (Consent management platformCMP). These provisions force companies to guarantee the transparency of algorithms and to respect the consent of users when collecting and processing their personal data.

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In addition, CNIL (National Data Protection Commission) ensures the stringent application of these principles in France, thus strengthening business responsibility for consumers in terms of confidentiality and autonomy. In this context, finding a balance between personalization of experience and respect for privacy is an crucial challenge for companies. The key to this balance is to understand two critical aspects:

• intuitiveness of experience, which guarantees polished and satisfactory interactions;

• And the invasion that risks annoying users and harm relationships with the brand.

Technological well -being

In ours testPublished in Journal of Consumer BehaviourWe conducted interviews with consumers to investigate the impact of AI recommendation systems on their “technological” well -being. Five key features have been identified that shape consumers’ answers:

• Information optimization: to improve the importance and quality of recommendations. For example, the book recommendation system may consist not only of previous purchases, but also on information such as previous opinions, time spent on each page and current trends. This guarantees suggestions that accurately correspond to the tastes of the person;

• Automation simplifies the election by reducing the effort to make decisions. For example, a streaming platform, such as Netflix, automatically generates a personalized reading list. This reduces the time and effort necessary to make a decision what to look at;

• Personalization offers users the opportunity to adapt their experience, while increasing their satisfaction. In this case, you can imagine an example of an online store in which preferences are regulated, such as choosing specific colors or sizes, the goal is to see only products that correspond to your personal criteria;

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• Predictability is aimed at inspiring trust thanks to coherent and precise suggestions. The online food purchase service provides for your needs according to regular purchases and offers offers of frequently bought products, such as your favorite coffee brand;

• “Humanity” sets a system that is approaching human behavior to create a sense of acquaintance, such as a vocal assistant who uses a balmy and addictive tone, causing the impression of discussing a man, not a computer program.

Intuitive, but not intrusive

Our results show that generally perceived systems as intuitive improve user satisfaction and decision making. On the other hand, systems considered intrusive – in particular those that excessively collect personal data – undermine trust and generate frustration.

In particular Graphics below It shows the positive and negative effects of artificial intelligence recommendation systems on consumers, emphasizing the advantages and risk of these technologies. On the one hand, aspects such as optimization of information and personalization are presented as strengths. For example, recommendations allow users to find products or content that interests them faster. Personalization also improves their satisfaction, adapting suggestions to their specific tastes, thanks to which their experience is more pleasant and engaging.

However, the chart also emphasizes some risk. Excessive automation can give consumers the impression that they lose control over their choices. Similarly, excessive exploit of personal data without transparency can cause a feeling of distrust or invasion of their privacy.

To sum up, this chart shows that although AI systems can offer significant advantages of consumers, companies are necessary for them to take advantage of their caution, respecting privacy and avoiding their becoming too intrusive.

FLUD FLUCT EXPERIENCE

Therefore, our results show that companies can improve the intuitiveness of AI systems, focusing on simplicity and meaning. For example, a wine seller could exploit artificial intelligence to suggest wine and introduce earlier purchases, thanks to which shopping is simpler to customers.

In order not to stretch customers, companies should limit the frequency of notifications generated by AI and ensure the transparency of data exploit. For example, they can offer very clear options for controlling or deactivating recommendations. In this way, they can hope to strengthen their clients’ trust.

https://www.youtube.com/watch?v=hwixpeqnu70

Control

Companies can also give their consumers the opportunity to adapt the parameters of their recommendations to augment the sense of control. For example, an online fashion store can allow users to filter products by style, ensuring that suggestions correspond to their preferences.

True and reliable recommendations are equally necessary to obtain consumer trust. Regular updates of algorithm, based on user feedback, guarantee that the system is evolving according to the needs of consumers.

However, our research also emphasizes that even intrusive recommendations can sometimes improve user satisfaction – provided that they are very crucial. For example, a system that offers vacation offers at the right time can be welcomed by an undecided customer.

Simplify without overwhelming

AI recommendation systems are powerful tools that, if used, can stimulate customer satisfaction. Our results emphasize that companies using such systems should include three key elements:

• They must promote the impression of users by designing systems that simplify decisions without overwhelming users with notifications;

• They must focus on the transparency of their systems, clearly communicating on the collection and exploit of data;

• They have to invest in personalizing these tools to enable clients to personalize their adaptation recommendations.

Companies that recognize the proper balance between usefulness and respect for customer autonomy will stand out on a very competitive digital market.