Insights on e-commerce, web development and digital solutions
Ten thousand product texts in four languages overnight - technically possible, risky in business terms. This guide shows how to classify content by risk, steer the machine stage with a glossary and style rules, measure translation quality through error classes and serve the language versions cleanly - from hreflang to the update run.
Returns eat the margin in 2026. An AI return prediction estimates the return probability per cart from size, fit and behavioral signals and intervenes before checkout - lowering return rates based on data without choking revenue.
36% of shops hamper their users in lists and filters (Baymard). A dialogue-based AI product advisor leads customers to the right product in a few questions - built as a custom solution for assortments that need explaining.
Text and data mining is permitted unless a machine-readable reservation exists. How shops declare the TDM opt-out in three places – without accidentally blocking retrieval crawlers too.
A third of AI-using companies report higher costs than expected. That is rarely down to the price per token, but to context length, output length and call frequency. Seven levers and a worked example.
As soon as a shop gets an AI advisor, a new attack surface opens up: language models do not separate instruction from data. What that means in practice and which layers hold.
WebGPU is active in all major browsers in 2026. Small language models now run directly in the browser - for private shop assistants, semantic search and text snippets, offline and without API costs. We sort out the chances, limits and hybrid approaches.
A product image without alt text is invisible to screen reader users and mute to search engines.
The Model Context Protocol is becoming the standard through which AI agents talk to software. How an MCP server opens your shop to agents on your terms, instead of being scraped.
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