AI product analytics: revealing the secrets of unsold items

Illiquid goods are a headache for any online retailer. According to statistics, 20-30% of an average online retailer's assortment generates less than 5% of sales, blocking working capital and taking up warehouse space. At the same time, traditional methods of analysis often fail to answer the main question: why is a particular product not being sold - because of bad photos, an overpriced price, an insufficiently informative description, or an objective lack of demand?

Our AI Product Analytics service implements an intelligent system that not only detects unsold items, but also identifies the specific reasons for their low performance and offers clear recommendations for optimisation. The system analyses user behaviour, compares the performance of similar products, and applies machine learning algorithms to identify hidden patterns.

The solution is based on advanced tools:

• GA4 (Google Analytics 4) - the latest version of Google Analytics for in-depth analysis of user behaviour
• GPT analytics - specialised GPT-based models for analysing textual content and identifying problems

How our system works:

1. Integration with your CMS, PIM system and Google Analytics to collect data
2. Comprehensive analysis of each product by 15+ parameters, including
   • :View statistics and conversion rates compared to similar products
   • Time spent on the product page and depth of photo view
   • Analysis of search queries that lead to the product
   • Study of the heatmap of clicks on the product page
   • Assessment of the quality of photos, titles and descriptions
3. Identify problematic products and classify the reasons for their low performance
4. Generate specific recommendations for each product
5. Tracking the results of implemented changes

The system classifies problems into categories:

• Problems with visual representation (poor photo quality, insufficient number of images)
• Problems with content (uninformative description, lack of key features)
• Problems with pricing (overpriced compared to competitors or analogues)
• Problems with search visibility (the product is difficult to find through a search on the website)
• Objectively low demand (the product does not meet current market needs)

The service is ideal for:

• Online stores with an assortment of 1000 products or more
• Marketplaces with a large number of sellers and product items
• Wholesale companies with a wide range of products
• Manufacturers who sell products through their own online channels
• Multichannel retailers with large inventories

Key benefits of AI product analytics

Implementing intelligent product analytics provides your business with a number of strategic advantages:

Freeing up working capital. The system allows you to optimise up to 20-30% of frozen warehouse stocks, freeing up significant working capital. According to our statistics, a medium-sized business optimises its inventory by UAH 200-400 thousand within the first 3 months after implementing the system.

Increased inventory efficiency. Algorithms identify the hidden causes of low sales of specific products, allowing up to 40-60% of problematic items to be "reanimated" instead of being completely removed from the assortment. This allows you to maintain the width of the assortment while significantly improving its efficiency.

Specific personalised recommendations. Unlike general analytical reports, the system provides precise recommendations for each product: which photos need to be updated, which characteristics to add to the description, how to adjust the price. This allows you to quickly implement changes without the need for in-depth expertise.

Performance forecasting. For each recommendation, the system predicts the potential impact on sales, allowing you to prioritise changes and focus on the most effective improvements.

Automated results tracking. The system automatically monitors the results of the implemented changes, determining their effectiveness and suggesting additional adjustments if necessary. This creates a cycle of continuous improvement of the product range.

Deep segmentation. The analysis is carried out taking into account different audience segments, traffic channels, and business seasons, which allows us to identify patterns that are not available in general analysis (for example, a product may sell well through organic search but poorly convert visitors from paid advertising).

According to our clients, the implementation of AI product analytics can increase the total turnover by 15-25% without expanding the assortment, only by optimising existing items, and reduce the cost of storage by 20-35%.

Why choose digiants.agency to implement AI analytics for goods

The digiants.agency team combines deep technical expertise in AI and data analytics with practical e-commerce experience. Our approach to product analytics has the following advantages:

Tight integration with your business processes. We don't just provide an analytical platform, we create a full optimisation cycle that is integrated into your workflows. The system automatically distributes tasks among responsible specialists (content managers, photographers, marketers) and tracks their progress.

Taking into account the specifics of your industry. We train algorithms on data from your specific niche, taking into account product features, seasonality, competitive environment, and target audience behaviour. This ensures high accuracy and relevance of recommendations.

Multi-channel analysis. Our system analyses the effectiveness of products not only on your website, but also on marketplaces, social media and other sales channels, providing a comprehensive understanding of the performance of each item.

Phased implementation with measurable results. We use the "test control group" methodology, which allows us to clearly measure the effectiveness of the system implementation. We first optimise a limited part of the assortment to demonstrate concrete results before scaling the solution.

Training your team. We not only implement the technology, but also train your team to effectively use AI analytics, understand reports, and implement optimisations based on them.

Proven effectiveness. Our clients record a 22-35% increase in turnover and a 40-60% reduction in the level of unsold goods within the first 6 months after the system implementation. The average project payback period is 2-3 months.

Ready to optimise your warehouse stock and increase the efficiency of your assortment? Contact us for a free audit of your product catalogue and a demonstration of the system's capabilities. We will identify the potential for optimisation and calculate the projected economic impact of implementing AI analytics.