AI in e commerce — new online store automations that pay off

PIM extensions for managing product information — more than just generating product descriptions

In most companies operating in the area of online sales, PIM (Product Information Management) systems are already standard. However, as we often emphasize while talking with our clients, it is worth remembering that the PIM system itself is like an empty shelf — in fact, the most important are the data stored in it and the ways of aggregating them. What do we gain from a good content distribution system, if the content itself is neither unique nor optimized for SEO.

That is why the automation of processes related to the aggregation of product data is becoming increasingly important. Thanks to the use of AI in e-commerce, it is possible not only to generate content, but also to generate, update and optimize it.

What data can we automatically aggregate into PIM?

1. Generate product images — modern artificial intelligence tools allow automatic generation of product photos or their advanced editing. Solutions like Nano Banana allow you not only to create product visualizations, but also to customize the background, lighting or presentation context. In situations where maintaining product authenticity is key, AI can also be used to auto-crop and optimize photos without interfering with the product itself. An example of such use of AI in e-commerce you can see in our demo of the facade configurator https://house-painter.sagiton.pl/en. All you have to do is upload a photo of the building, select a color for its individual elements (e.g. facade, windows, roof) and click “Swap colors”, and automation using artificial intelligence will dynamically generate a preview for you.
2. Product descriptions optimized for SEO — product content no longer has to involve entire marketing departments. Thanks to the use of AI in e-commerce, it is possible to quickly create product descriptions, auction titles and meta data, which are also optimized for SEO. Automation of processes in this area allows you to maintain consistency of communication and significantly speeds up the introduction of new products into the offer.
3. Technical information that we did not obtain directly from the manufacturer — not all product data is always provided directly by manufacturers. In many cases, e-commerce companies sacrifice tens of hours per month for manual search of technical information, such as parameters or dimensions of products. Thanks to the use of artificial intelligence tools such as AI bots, automatic scrapers and integrations with supplier databases via API, it is possible to fully automate this process. Data can be retrieved, processed and supplemented on an ongoing basis in the PIM system, which significantly increases operational efficiency and reduces the risk of errors.

Automation of processes related to the completion of product data in PIM systems is one of the most practical examples of the use of AI in e-commerce. It not only saves operational teams' time, but also significantly improves the quality of data that directly affects visibility in search engines and the effectiveness of online sales.

Chatbots and voicebots in e-commerce — intelligent solutions for customer service

Until recently, chatbots were associated by many users with limited, often frustrating, Q&A solutions that could not really help solve the problem. Today, however, thanks to the dynamic development of technology and especially the use of generative AI, their role in online sales has undergone a significant transformation. A modern artificial intelligence system can conduct a natural, contextual conversation that really supports the user at every stage of the purchase path.

In practice, this means that chatbots can not only answer questions, but also recommend products tailored to the customer's needs, explain more complex issues or guide the user step by step through processes such as submitting a complaint or completing an order. Moreover, they are able to analyze the behavior of users on the site and propose personalized offers or promotions at the right time. It is this aspect that forms the foundation for more advanced strategies, which you will read about in the next part of the article on hyperpersonalization.

When it comes to voicebots, we still face some skepticism from companies. Therefore, in conversations with our clients, we often recommend implementing such solutions with appropriate standards — such as an extensive knowledge base or the ability to quickly switch the conversation to a consultant (real, not AI). At the same time, it is worth emphasizing that well-designed voicebots can significantly improve customer service and support business development. They work particularly well as the first line of contact, relieving the burden on service teams, but they can also perform more advanced tasks — for example, conducting satisfaction surveys or collecting feedback from customers.

Case Study — a interesting usage of the voicebot artificial intelligence system‍

One of the companies that contacted us had a problem with making appointments for customers. When specialists were busy serving customers, it often happened that no one answered the phone, so people who wanted to make an appointment by phone simply switched to the competition. The solution to the problem turned out to be the implementation of AI automation using voicebot. When the phone rings, the automation first checks the calendar to see if one of the specialists is available - if so, it directs the call to him, if not - the appointment is made by the voicebot. Thanks to such implementation, the company at the same time retains a high quality of customer service, but also does not lose potential visits.

Hyperpersonalization — that is, personalization with AI

Hyperpersonalization is one of the latest trends in e-commerce, which has developed thanks to the possibilities offered by AI. In the classic approach, personalization is usually based on simple scenarios - for example, displaying the “similar products” section based on recently viewed categories or sending a newsletter to a specific customer segment. These solutions are effective, but fairly general and based on a limited amount of data.

For example, standard personalization may consist in the fact that a user who has purchased sports shoes will be shown other products in the same category by the recommendation system. It is a schematic and identical action for a wide audience.

AI-based hyperpersonalization, on the other hand, works much more precisely and dynamically. The AI system analyzes user behavior in real time, taking into account customer needs, interaction history, the context of the visit or previous online purchases. Thanks to this, it can adjust not only the products, but also the way of communication, the moment of contact or even the channel of arrival.

A good example from the market are supermarket chains that send SMS messages with an offer like “promotion for article Y only in your store on street X”. These types of messages are not random — they are based on data analysis, such as where the customer's loyalty card is most often used and the type of product that the customer often buys. It is the combination of different data sources and their intelligent interpretation that makes communication truly tailored to a specific person.

More about this we described in the article “AI and Hyperpersonalization in E-Commerce”.

Competitive price analysis and dynamic pricing

In e-commerce, especially in the dropshipping model and the sale of products from external manufacturers, one of the key factors affecting the profitability of the business is proper margin management. However, it is not only our margin that is important, but also the price level and pricing strategy of the competition. In an environment where identical products are offered by multiple sellers, price becomes one of the main decision factors for customers, as well as an element that influences the visibility of offers in marketplaces.

Sales platforms often promote the cheapest products or allow you to filter them by price, which further reinforces the importance of price competitiveness. At the same time, the owners of e-commerce stores need to take care of maintaining adequate profitability, which in practice means the need to constantly monitor the market and adjust prices.

Traditionally, this process was time-consuming and relied on manual analysis of data from multiple sources. Today, however, thanks to artificial intelligence, it is possible to fully automate it. Modern AI systems analyze data in real time, using Internet access and integration with the store system. They can automatically check current competitor prices, product availability or changes in marketplaces, and then compare them with our data — such as purchase prices or assumed margin. On this basis, the system can independently update prices in the store through API integration or — depending on the strategy adopted — provide recommendations for verification by the e-commerce manager.

Such dynamic pricing adjusts the store's offer to the current market conditions. For example, the system can maintain an assumed margin (e.g. 30%) while optimizing the price in such a way as to increase competitiveness and maximize sales.

To show our clients the possibilities of e-commerce automation, we have created an AI system that, based on the given EAN or SKU code, generates a competitive analysis report containing:

• List of portals and stores where the product is available
• Comparison of prices, including indication of the lowest price of competitors
• Unique product description generated according to SEO rules

Download the free report and increase the effectiveness of your e-commerce: https://www.sagiton.pl/en/e-commerce-competitor-analysis

In the report, we also include the generation of SEO-optimized product descriptions that can be directly used in the offer. The system prepares SEO title and description recommendations, supporting the consistency and visibility of the product in search engines. As a result, one report is enough to comprehensively optimize the offer of a single product.

When do process automation and AI in e-commerce give the best results?

The solutions described in the article are one of the latest directions of technological development in e-commerce, which realistically support sales scaling and operational optimization. However, it is worth remembering that each AI implementation should be tailored individually — to the business model, processes and challenges of a particular store.

In order to implement AI in e-commerce in a profitable way, it is worth analyzing the following areas of activity of an online store:

• processes that are very time consuming, and at the same time necessary to perform — such as adding product descriptions or searching for technical information; these are repetitive processes that do not directly add strategic value, but consume significant team resources, so their automation brings quick and measurable benefits
• error-prone processes that can negatively affect sales — for example, competitor price analysis; if we do not conduct it regularly or do it manually, it is easy to make mistakes or delays, which can result in a decrease in search results, loss of price competitiveness or a decrease in margin
• processes that work correctly, but do not use their full potential — e.g. implementation of personalized product recommendations based on hyperpersonalization and real-time data analysis, which allows you to better match the offer to the user, increase conversion and maximize the value of the shopping cart

If you want to effectively use AI in your online store and choose solutions tailored to your business, contact us. We will help you plan and implement automations that will translate into real sales results.