Use Cases
Gas Station

Location based services on all trips


What applies to you, you should also consider for your app users!
Do not send push messages when there’s a high chance that a user is driving. Rather choose rest or service areas to display your push notification!

1Sarah and her daughter are traveling by car to her parents. She has installed the app of a certain gas station company on her mobile phone.

Analyze Sarah’s Customer Journey and her interests – even before she enters a gas station.

2They are passing different gas stations of other companies and do stop at a rest area.

It can be analyzed if Sarah visits gas stations of competitors to refuel the car or to buy products.


Sarah receives a push notification with an overview of the prices at the nearest gas station of the company. In addition, she gets the hint that she’ll receive a 2%-discount on the tank filling when showing her membership card. Sarah is happy and decides to go there to refuel the car.

3They reach the next gas station of the company.

The advertising effectiveness of the push notification (Use Case 2) can be measured. At the gas station itself, more information can be gathered to get a better understanding of Sarah’s interests and refuel behavior.

4Sarah stops at a gasoline pump.

She gets to know that she can now directly pay at the pump via the app. This can save her time if further articles from the shop are not needed. Today she can not use this feature as they will buy something to drink in the shop.


When paying at the pump, the company can evaluate which customer refuels what type of fuel and the appropriate amount. With additional location information, the company can scale the number of pumps for each fuel, depending on the demand at the respective gas station.

5Sarah and Emma are on their way to the gas station shop to pay for the fuel and to buy something to drink.

Infrastructure information can be shared to optimize local gas station visits and to refine analysis reports.

Use Case can be perfectly implemented with
6They enter the shop.

Sarah is reminded to show her membership card to get the discount (Use Case 2).


In the shop, more expressive data can be collected for accurate analysis.

7Emma wants to have a juice box and Sarah is thirsty too. They stop in front of the refrigerated shelf and choose something to drink.

As she holds her smartphone against one of the price tags, the website of a beverage manufacturer opens. On the page, an online game for children is offered.


A beverage manufacturer has gained access to the technology integrated into the price tags. The manufacturer uses this to display its own marketing campaigns and services.

Use Case can be perfectly implemented with ESLs from SES imagotag
8The lighting system in the shop is sending signals that trigger location-based actions.

Sarah receives a push notification on her smartphone with a 2-for-1 offer for the integrated bakery. She takes advantage of this offer and buys two pretzels.


After her visit, Sarah’s purchases can be compared with the offers made, to measure their advertising effectiveness. The lighting system enables the company to track the positions of all app users in the shop.

Use Case can be easily implemented with several lighting systems.
9They are close to the check out.

Sarah receives a push notification which contains an advertisement for a new chocolate bar of a large candy manufacturer.


A candy manufacturer whose products are offered at the gas station runs its own marketing campaigns via the technologies used in this shop.

10At the checkout, location-based services are initiated via technologies that are integrated into the card terminals.

Sarah receives the information that she can now pay with alternative payment methods (e.g. Alipay is now available).


A mobile payment app provider has gained access to the technology integrated into the card terminal. The provider wants to use it for analysis and to display marketing campaigns through its own app.

Use Case can be perfectly implemented with card terminals from
11Sarah and Emma are leaving the shop.

Sarah’s dwell-time in the shop is calculated and the exact branch she visited is documented as well, to complete Sarah’s customer profile.


Sarah receives a push message in which she is thanked for her visit.

12They are leaving the gas station and drive on. Of course, Sarah’s and Emma’s ride does not end when they leave the gas station.

Even after the visit, additional insights into Sarah’s preferences for gas stations and service areas can be generated in the background. It can be analyzed whether Sarah visits a gas station of a competitor subsequently. For this purpose, the app on Sarah’s phone doesn’t have to be open.

Offline generated data can lead to even more accurate customer profiles in the Schober databaseLogo Scober
13Sarah and Emma arrive at Sarah’s parents.

Data collected during Sarah’s journey and her stay at the gas station can be connected with additional information about Sarah.


Sarah can now look forward to more and more relevant services.

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