Guiding you to build data science projects remarkably fast, collaboratively and without writing code.
More powerful than dashboards and more intuitive than notebooks.
Why are the social media strategies of Innocent Drinks considered as the gold standard for marketing teams the world over? We collected every tweet (10,521) posted by the communication department to deconstruct Innocent's content, style, reach and engagement with a simple topic analysis.
We spoke to the data science team at Aquaservice about how they used Graphext to build a clustering model to improve the way they forecast consumer demand. Their project grouped delivery routes using over 30 factors to calculate similarity and exposed patterns in the errors made by their prediction models. Models that are responsible for forecasting the number of water bottles that should be loaded into trucks for delivery across a huge number of routes across Spain.
We collected every tweet published about the 2021 UN Climate Change Conference (COP26) to study how people have engaged with events during the summit. Using topic analysis and emotion detection, our project dives into people's visceral reactions to agreements on deforestation, commitments between China and the USA and the appearance of Barack Obama.
Customer segmentation involves splitting a customer base into distinct groups. These customer segments are defined by specific and shared characteristics, behaviours or preferences that help businesses to spot patterns and associate customers with one another. This article walks through the steps involved in a simple customer segmentation analysis. Using sales data from a delicatessen, we'll segment customers according to their buying preferences and behaviour. To achieve this, we'll use a powerful machine learning technique known as clustering.