Maximise profits with AI: Optimised product and offer selection
Artificial intelligence is changing the way companies offer products and fulfil customer needs. Through data-based analyses and intelligent algorithms, AI helps to provide the right product and offer selection at the right time – across all channels and individually tailored to your target group. The result: higher conversion rates, lower wastage and measurably more profit.
With AI-supported software, you can optimise PIM, DAM, workflows and the collaboration of your teams – across channels, efficiently and future-proof.
How does artificial intelligence improve data quality in PIM and DAM?
The AI integrated in LAGO supports the creation of metadata, (image description) texts and translations of assets. The text suggestions can be automatically adopted across channels and in real time, which saves a lot of time and errors.
What role does AI play in workflow management?
Artificial intelligence identifies recurring patterns, optimises product planning and enables processes to be carried out more efficiently.
How do companies benefit from AI-supported technology?
Intelligent forecasting models enable companies to react better and faster to trends in order to optimise product planning.
In the highly competitive food retail sector, the right product range and offer strategy determines margins, customer loyalty and competitiveness. Artificial intelligence analyses sales data, seasonal trends, regional preferences and promotion histories in real time – and provides well-founded recommendations for product range optimisation and targeted promotion planning.
This allows you to place the right products in the right place at the right time – automated, data-driven and profit-orientated. With AI, you not only increase your sales, but also reduce markdowns and avoid out-of-stock situations.
LAGO is working with DecaSIM, among others, to create a forecasting model that can simulate customer reactions to different advertising strategies.
This innovative AI technology skilfully identifies the promotions that resonate best with price-conscious customers, resulting in higher sales, more engagement and increased profits for retail partners.
This is particularly important for advertising and marketing managers in the planning phase of a campaign. LAGO’s whiteboarding function already gives them an overview of which products should be emphasised based on criteria such as regional availability, profit margin and sales history. With the addition of DecaSIM data, they also get reliable indicators of what customers are more likely to buy, including their preferences for related or alternative products.
Artificial intelligence makes advertising media in food retail more precise, efficient and profitable – data-based, adaptive and customer-centric.
+8%
The AI-based planning approach led to an increase in weekly sales and profit growth of eight per cent (EBITA).
Advantages of LAGO with AI-supported technology
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- Higher conversion rates: Relevant offers lead to more purchases and higher promotional sales
- Better campaign planning: Prediction of campaign effectiveness depending on region, season and target group
- Reduction of wastage: Advertising materials only reach the customers for whom they are really relevant
- Automated target group segmentation: AI recognises patterns in customer and checkout data and creates dynamic target groups
- Early recognition of trends: AI identifies new demand signals before they become visible in the figures
- Reduction of overstocking and understocking: Better demand forecasts for advertised items minimise stock losses
- Continuous learning and improvement: The model continues to adapt with each campaign and becomes more precise
- 360° analysis of campaign success: Tracking the impact of advertising media down to individual product level
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LAGO’s data personalisation potential can combine customer data (addresses, recommendations and purchasing behaviour) with product information and images and display the results on any digital channel.
Download the full AI omnichannel commerce case study here!
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