Predictive analytics in marketing is one of the most relevant trends in today's marketing landscape, as it enables anticipating future consumer behaviour based on data. Although marketing has traditionally lagged behind other fields in using data to inform decisions, it now benefits from vast amounts of information thanks to the digital environment.
The arrival of ChatGPT in late 2022 marked a turning point across many sectors, including search engines. Since then, Google has intensified its efforts to stay at the forefront of artificial intelligence with Gemini, its most advanced model, and its integration into popular tools such as Gmail and Google Docs.
B2B companies in the tech sector face a highly competitive environment where generating high-quality leads is essential to boost sales and business growth. However, doing so manually—from identifying prospects to qualifying, following up, negotiating, and closing deals—requires a time and resource investment that’s difficult to sustain at scale.
More and more businesses are striving to offer more personalised attention to their customers, but doing so manually is time-consuming and difficult to scale. This is where artificial intelligence (AI) comes into play: thanks to its capabilities, sales and marketing teams can create highly personalised AI-powered email marketing campaigns, but on a massive scale.
Although artificial intelligence (AI) has revolutionised many areas, there's one field where it still stumbles: turning data into understandable visuals. At first glance, it seems like a solved task. But behind every visualisation lies a deeper, still unresolved challenge: how to distil complex analytical processes into a single, clear, and effective instruction?
