Espresso House is a coffee shop brand with over 400 shops in the Nordics. They used Kuwala to merge internal and external data sources in order to train a model that informs the the expansion team of market potentials.
“ Instead of only using empirical observations, we now take into account data from various sources in order to take data-driven decisions.”
KoRo is one of the biggest food startups in Germany selling superfoods. KoRo started as an online store, but now also sells its products offline in 9,000 grocery stores across Europe. In Germany, for example, at Alnatura, Edeka and Rewe.
“ We strongly professionalize our marketing analytics. Hence the collaboration with Kuwala, because we want to see how we can optimize our marketing mix.”
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The city of Leipzig redefined its open data strategy towards mobility data. It was crucial to identify and leverage the status quo and create a workshop format for +50 developers at Europes biggest developer conference.
“ We thank for the very professional preparation and the unique experience at the CCC Congress. It was an important part in defining the open data strategy”
The dashboard empowers mobility providers to improve their services on the basis of AI-driven analytics and thus be able to react quickly and with certainty to the ever-changing demand and supply situation in large urban areas. The dashboard visualizes real-time information about supply and demand. We aggregated various external data-sets and predicted hotspot areas in cities
To gain better insights into customer behavior at the point of sale (POS), we have developed a dashboard that evaluates geographical data and social media information. The data can be combined with SKU data from an ERP system. This makes it possible to analyze activity and interest profiles at any location in a city. We were able to build a dashboard predicting passenger flows and recommendations for replenishment to improve the ERP system.
We analyzed over 3 Million images from social media through a computer vision algorithm and tracked the content down to a geo-location with a timestamp. Knowing what customers are preferable doing helps to anticipate event promotion plans, demand predictions, and content strategies.
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Depending on location and time of day a taxi driver gets a driving recommendation, based on our predictions, where the highest probability to pick up a new passenger currently is. The information is communicated seemless on a mobilephone of the driver.
