Projects

We increased the number of Dutch visitors to a Shopping Centre in North-Rhine Westphalia by 10% by identifying and ad-targeting relevant clusters of Dutch postal codes along an important German highway. We used geographic analysis of telecommunications / motion tracking data to find the relevant agglomerations and created an autamatically updated dashbaord for co-workers.

We analysed socio-degmographic and socio-economic data and merged them with the number of visitors per postal code for 2 Shopping Centres in Baden-Württemberg to convince a major retailer to prolong their Lease contract: we demonstrated our client's superior buying power and a proved loss of unique customers due to a lack of cannibalisation effects in the area, if the contract is not prolonged. 

We created a data platform strategy and served as project managers between Data, IT and Sales teams of a major Retailer to create a data platform that is accessible to their B2B clients for yearly subscriptions. 

We demonstrated the harmless market share of the childrens toys product category of our Commercial client within one postal code of a Western European municipality. This led to permissions from the municipality to extend the childrens toys section within our client's premisses.

We demonstrated the need for a focus on creating urban offers for persons with an upper-middle buying power and the age class of 18-25 years olds to revive the city centre of a major Western German municipality. Comparing the visitors values of the city centre to close-by shopping centres clearly served as a benchmark for the potential the municipality is missing out. 

Using Machine Learning and AI techniques, we created automated and interactive benchmark analytics across all stores of all of our client's Shopping Centres to identify outliers, i.e. irregular store sales performances and weights of costs, within seconds. This serves managers to quickly detect where to optimise contracts or other operational factors with lessees.

Working across teams for a major Shopping Centre manager, we created new KPIs by combining datasets of different departments that before worked in silos (e.g. Sustainability and Operations, Marketing and Leasing, Marketing and Development). Having broken the silos, the new KPIs created new perspectives of company performance leading to insights into the whats and whys of how performance changes over time.

We combined a large set of marketing performance KPIs of our client that manages a portfolio of shopping malls in Germany and Austria to create a complete picture of whats and whys in customer behavioural change:

​

Analysing changes in customer behaviour through physical GPS and Mobile Data Tracking, website visits and web-subsite visits we first measure where, in which customer groups and in which channels changes appeared and to what extent. Brand performance measurement, net promoting scores (NPS), social media sentiment analyses then explained how those changes arose.