Why personalisation in marketplaces is key in 2023 - All about AI

McKinsey predicts that by 2030, 70% of all companies might adopt AI-driven solutions to streamline operations and improve productivity. These numbers signify that it’s the perfect time for online businesses, marketplaces included, to embrace the power of AI.

Today's interview is with Alicja, Behavioural Data Scientist at NovaFori. With data science increasingly becoming a key driver of unlocking the value of customer interactions on marketplaces, Alicja joins NovaFori today to talk about the importance of AI and machine learning to drive personalisation and a customer-centric approach.

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What is an AI-driven marketplace?

Artificial Intelligence (AI) is a field of computer science that focuses on creating intelligent machines that solve problems; increasingly it has begun to embed itself in nearly all aspects of our lives.

The purpose of creating AI-driven marketplaces is to leverage the technology in order to gain detailed insights into large volumes of data, accelerate operations, and deliver an enhanced user experience with personalised, real-time services.

In digital marketplaces, AI solutions process vast amounts of data about users, prices, items, and transactions. Combining them with sophisticated analytical algorithms to enhance customer experience, decrease inventory management costs or increase sales.

The power of behavioural data is its capacity to help personalise the user experience and improve recommendations of relevant products, thus reducing the time to find what the customer is looking for. It can also act as an intelligent agent to match buyers with relevant products, power chatbots to help users navigate or forecast demand for products through data-driven inventory management.

AI technology in marketplaces enhances the shopping experience, generating higher profits and greater value for customers, encouraging them to continue using the marketplace.

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How can online marketplaces use AI to grow sales?

AI-driven marketplaces can break down their customer flows by specific groups of buyers. Each group will have different marketing approaches, communication patterns, and product propositions.

For instance, AI in B2B marketplace/eCommerce platforms can determine which business sector is most likely to be interested in, and subsequently purchase, a particular product. Thus, it can select a group of potential buyers and approach them with well-crafted targeted marketing messages.

• With personalised product recommendations, AI helps reduce customers' time and effort to find relevant products, driving greater sales.
• With user segmentation models, the marketing messaging, including direct email or social media campaigns, can be refined, creating targeted communication with potential customers. From the marketplace perspective, it drives higher conversion or response rate, whereas from the customer perspective reduces the amount of irrelevant messaging landing in their inbox.

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AI enables better recognition to predict and anticipate buyers' behaviours

Organisations using AI can enhance business optimisation and improve users' experience via pattern recognition. Such tools allow businesses to discover common features in customers' behaviour, consumption patterns, and sentiment and satisfaction with the services or products on the marketplace. Later these insights help refine search tools, improve recommendations, and build a loyal customer base. From a business perspective it can also help with inventory planning, improving marketplace liquidity and reducing time to sell products.

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How can AI and machine learning reduce friction in the marketplace with anomaly detection?

Anomaly detection is a process which aims to identify abnormal instances or events which deviate from the norm significantly. In a marketplace, anomaly detection is critical to safeguard both buyers and sellers, detecting, i.e. fraud in financial transactions, credit card frauds, abusive auction behaviour, or handling or fake reviews. Instantly reacting or predicting likely-problematic events facilitates proactive prevention of marketplace abuse. In addition, fast and efficient responses to any site's abnormalities significantly reduces profit loss and drives customers' trust.

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What do you mean by marketplace personalisation, and what are its benefits of it?

Personalisation of search results or a particular product suggestion in the form of a landing page or email campaign, based on users’ past interactions and product preference, is one of the most common ways to apply machine learning to a marketplace business.

Based on understanding different aspects of the user's behaviour, artificial intelligence algorithms can recommend goods and services that users are most likely to be interested in.

The machine learning algorithm can drive the improvement of the user's experience. This is possible by analysing the following data:

• Personal profile
• Search history (such as previous search results and any applied filters)
• Product browsing history (such as which items were viewed, and which ones were added to the cart)
• Cart and purchase history
• Behaviour of users with similar profiles / from similar groups
• Seasonal trends (Christmas period, summer barbeque time, skiing season etc)
• Global trends

The more actively the user engages with the platform (i.e., looks for items or services, adds items to the shopping cart, buys things), the more precise information the system will have. And the more relevant options it will offer to the user.

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Conclusion

Organisations should not downplay the role of data-driven marketplaces, as they will continue to increase the quality of business results and can save them significant amounts of time and money. By adopting a data-driven approach, businesses and organisations can take sales information and leverage it as a strategic asset, generating actionable commercial insights and unleash their true sales power.

Using data science tools and products such as heat maps and analytic dashboards will help you understand how your users interact with your marketplace and develop customised marketplace experiences that can boost engagement.

Discover more benefits of using data effectively and how our Data Science products can help your marketplace scale.

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