We help businesses understand where their customers are in the offline world.

Whether it’s about mapping customers’ journey, defining location for a new store, driving offline-online communication or identifying points of sale with the highest sales potential – we make everyday business decisions in the offline world easier.

We collect location data from over 40M of mobile devices across Europe, process it and combine it with number of datasets that provide socio-demographic and spatial context for our analysis. Our machine learning algorithms and proprietary predictive models enable translating number of devices that share their location into number of actual customers, with over 90% accuracy.

Our analysis provides dynamic and always up-to-date insights – location data is updated every day, and allows to identify changing patterns and trends in terms of customer behaviour. When combined with data about demographics, POI, purchasing power of people residing in the neighbourhood, it provides a holistic view of a given location and its customers.

The solution is used by:

major retailers, who leverage it to grow and monitor their stores chain;
leading banks, who leverage it to optimise their branch network and feed their data systems with additional data sets (e.g. for credit risk purposes);
large media agencies, who leverage it to drive offline to online marketing and build accurate customer segments;
FMCG brands to identify optimal points of sale for product roll-outs and activation campaigns;
real estate businesses to assess potential of a given location and services available there;
entities in the smart city business to understand how people move around the city and interact with facilities;
investment companies to tap into growth of a given business, based on their customers behaviour and volume.

With Dataplace.ai our clients de-risk their decision making process, reduce time and money that comes with analysing vast data sets and optimise their cost per user reach by up to 50%.

Our clients use Dataplace.ai via web application, where they can interact with the data themselves or in the form of data feed. Our solution covers data for the entire European Union and the United Kingdom.

Data metrics that we provide include (among others):

traffic volume - number of people moving through a given area, daily/weekly/monthly footfall
traffic dynamics - rush hours, traffic distribution in time
traffic structure - pedestrian and car traffic division
traffic characteristics - average time spent in the analysed area, recurrence of people visiting the area, traffic locality, traffic division between passers-by and local customers, shared traffic between 2 locations
customer segments - e.g. people who are vegan / young & studying / active physically / customers of a given retail chain (based on presence, popularity, visit frequency)

customer socio-demographics - age and gender, education, marital and professional status
customer purchasing power - average earnings per capita
customer receipt - average spending per capita on 20 expenditures' categories
POI - location of trade & service outlets, POI generating traffic

Dataplace.ai - offline analytics companyplaceme

Dataplace.ai - offline analytics company

placeme

Dataplace.ai - offline analytics company

placeme

Dataplace.ai - offline analytics company
placeme