Technology and Innovation in Service Stations

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www.repsol.com/es_en/productos-servicios/estaciones-de-servicio/

CLIENT : Repsol

DATE : 2015,2016

Repsol is an integrated global energy company with vast experience in the industry. It carries out Upstream and Downstream activities throughout the entire world. We are present in more than 40 countries and we have a team of more than 27,000 people committed to a future project: the construction of a sustainable energetic model.

Repsol has 4,649 service stations in Spain, Portugal, Peru and Italy. In Spain there are 3,585 points of sale in the network. Of them, 70% have a strong link to the company and 29% are managed directly. There are also service stations in Portugal (440), Italy (250), and Peru (374).


Digitalization of Physical Places applied to Petrol Filling Stations

Goals

 

Repsol, the Spain’s largest petroleum company and one of the largest worldwide, is actively implementing a range of digital solutions and applications for the service stations including solutions such us contactless payments or a mobile application which enables customers to pay for fuel without stepping out of the car.

As part of its digital transformation process, Repsol wanted to explore methods to gain competitive advantages from a deeper knowledge about their service stations customers and operations performance.

Gennion Solutions accepted the challenge and proposed to monitor customer-visiting behaviours. Then, the development of an analytical methodology to profile customers based on visiting occasions and missions, as well as predictive modelling to attribute economical value (sales) to occasions and missions.

Accepting the challenge led also to consider and solve related location engineering details of such a complex scenario:

  • Deploying a technical infrastructure based on a network of sensors over a service station (inside the store and across outdoor facilities), fully compatible with industry laws and restrictions.
  • Business directed micro-fencing of the service stations based on what needs to be measured and known about operations and customers: overall station, potential traffic, petrol filling times, facilities used or sections within the store.
  • Identify key decision or interest points in a service station where it would make business sense to implement real-time interaction capabilities, and to activate the proximity technology to enable them.
  • Integrate external data such as the weather or sport events on TV to measure its influence on service stations operations.

Proposed solution

 

Gennion deployed its Smart Places solution called NUTSHELLTM. It detects, tracks and interacts with people and objects in real-time based on a network of sensors.

NUTSHELLTM provided all the necessary ingredients to achieve these objectives: Interoperability, in this case collecting sales tickets data to get a single digital ecosystem; Location accuracy, to effectively understand visitors routes based on proprietary location engineering tools and next-generation machine learning algorithms; Real Time, to collect data in real-time and model contextual events and situations of interest in the right time; Analytical Intelligence to extract value from data ingested.

Gennion collected data from these areas and run its location engineering process to shape machine learning based micro-fencing models that once validated was set to production. NUTSHELLTM starts then collecting and interpreting data in real-time giving context to it based on location, moment and specific device and analysed preferences and routines.

The resulting Wi-Fi monitoring zones were. All stations, Each Station, Pumps, Car Wash, Store (overall, shopping area and counter) and parking.

And Bluetooth Low Energy interactive micro-zones were enabled at: All stations, Each Station, Pumps, Car Wash and Store (Entry, Food products, Wines, Coffee, Drinks, Press, Cash machine and Counter).

Results obtained

 

Gennion carried out a data quality assessment of the data provided by NUTSHELLTM in order to guarantee proper coverage and representativeness of business metrics and indicators built:

  • The solution identifies and tracks accurately 81% of actual visitors of service stations
  • It correlates 88% to the number of actual visitors by minute
  • Petrol filling visit missions tracked explain 86% of petrol sales by station
  • Convenience shopping visit missions tracked explain 83% of non-petrol sales by station

Gennion defined the proper set of data indicators required to analyse service stations activity. Gennion’s data analysts took those data and mined them identifying relevant data opportunities.

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