What a large language model (LLM) is, how it works (tokens, attention, parameters), and how a marketer can use LLMs for personalisation, automation, sentiment analysis, customer service scaling, and marketing activities.
AI & Branding Trends
The latest insights on how artificial intelligence is transforming the world of brands. We analyze trends in LLMs, generative AI, and conversational assistants, showcasing their impact on brand visibility and recognition. This section highlights the direction in which the market is heading and provides inspiration for leveraging AI in branding.
We explain what the context window of language models is and why key information can disappear from AI assistant responses. We cover tokens, the sliding window effect, and practical techniques that help maintain coherent context.
An overview of the brand digital twin concept: local AI simulations that enable message testing before publication. The text covers applications in GEO, rapid A/B testing, crisis simulations, calibration challenges, and organisational steps toward a pilot.
An overview of ads in LLMs and paid recommendations in AI: what formats will emerge, how they will affect brand visibility, transparency and measuring effectiveness, and how to prepare your strategy.
Local models (SLM) move AI processing onto users' devices, reducing telemetry and the impact of traditional marketing. The article explains Share of Model Voice, visibility estimation methods (simulations, opt-in, partnerships), and when it's worth investing.
Autonomous AI agents are taking over purchasing decisions on behalf of users. The text explains how real-time APIs, precise GEO data, inventory synchronization, and new KPIs affect brand visibility and operational risks in e-commerce.