By Christina Widner

Artificial intelligence (AI) is now present in practically all areas of our lives, although its influence is especially notable in the retail sector. Crucial to this are recommender systems based on AI algorithms that determine to a significant degree the success of e-commerce platforms. Particularly in the toy sector, these systems can play a key role by offering personalised recommendations that make the purchase process easier for parents and improve the play experience for children.

Explainer: recommender systems

Recommender systems are used to recommend products, services or content for different user groups. They may be based on preferences, prior behaviour and/or parallels with other users. Recommender systems are deployed in various areas, including e-commerce, streaming services and search engines.

The true picture: the importance of recommender systems in the toy sector

These systems have already assumed an important role in e-commerce as they help customers to discover products that are relevant to their interests and preferences.

In the toy sector in particular, parents and children can often be overwhelmed by the choice on offer. Personalised recommendations are especially useful for taking equal account of their needs. The systems analyse user behaviour in order to identify preferences and suggest toys that match the individual requirements.

How do recommender systems work? One factor: data-driven personalisation

Data analysis is crucial to real effectiveness in the toy sector. By collecting and analysing data, such as previous purchases, search requests and ratings, algorithms can identify patterns and predict future preferences. 

Such data-driven personalisation enables recommender systems to make tailored suggestions that meet the individual needs of each customer. One special aspect of recommender systems for toy purchases is the requirement to consider the needs of both parents and children.

Improved customer experience = increased customer retention

Personalised recommendations help customers to find what they are looking for more quickly and easily. But that’s not all – they also improve the overall shopping experience. 

Recommender systems are like personal assistants that suggest what customers might wish to buy based on what they have liked in the past and so on. When such suggestions are tailored to their interests and preferences, customers feel better understood and appreciated.

This can lead to increased customer retention and greater customer satisfaction, which in turn fosters brand loyalty and repeat business.

Challenges and ethical considerations

There are many good things about recommender systems, but there are also challenges associated with them. These include concerns about data protection and privacy, as such systems collect and analyse sensitive customer data.

It is very important for companies to communicate openly about the data they collect and use as well as ensure that customers have full control over their own data. 

There is also the risk that customers may only be shown products that meet their previous interests. This can lead to a bubble effect and reinforce stereotypes, because customers are not then confronted with other views or ideas.

Outlook: what companies can expect

Toy recommender systems are still in their infancy, but the future holds exciting prospects. These systems may soon be able to make even more accurate suggestions thanks to improved technology, such as machine learning and artificial intelligence.

In addition, new technology like augmented reality (AR) and virtual assistants may influence how we interact with and seek out toys.

Despite the few obstacles to be overcome, toy recommender systems are an exciting way to make toy shopping better and more personalised – for both parents and children.

Bottom line

Recommender systems based on artificial intelligence play a key role in personalising how we shop for toys. Through data-driven analysis, these systems can offer tailored recommendations that cater to the individual preferences and needs of customers. 

While these may improve the customer experience and boost sales, it’s important to consider ethical matters, such as data protection and diversity. With further advances in the technology, the future holds the promise of even more exciting developments in the area of personalised recommender systems for toy purchases.

About the author:

BASIC thinking is an online magazine and one of the widest-reach tech portals in the German-speaking world. The editorial team reports daily on social media, marketing and business topics. This article was written by Christina Widner from BASIC thinking GmbH and BASIC thinking International.