1. Business case & Canvas - RichiWolf/HHZ_Projekt_Measurement-of-shopping-time-in-supermarkets GitHub Wiki

The following page describes three use cases that arose during brainstorming. They have the goal of generating customer benefit or business benefits and are all concerned with the shopping time measurement. The three use cases should address three different user groups. In the following, the scenario, the associated Value proposition model (VPC) and the Business model canvas (BMC) are presented for each use case.

In this scenario the project team focus on the customer type of older consumers. A statistic of the consulting A.T. Kearney in the year 2010 shows that the group of older consumers gener-ated a total turnover of 6 trillion euro in the world. It is assumed that the generated turnover will rise to an amount over 11 trillion euro, which make them an attractive target group. In ad-dition is this target group well known for rarely using smartphones (Gerth). Indeed, 28% of persons over the age of 65 owned a mobile phone but the majority of this group doesn’t use them (Kahle).

In the first scenario the central character is Gertrud, a pensioner. She is a fictional example for the group of customers that don’t use a smartphone. Since her husband died, she lives alone. She goes always shopping in the supermarket close to her apartment. Because of this she is a regular customer in this supermarket and want to be rewarded for this. But the re-wards should not be offered via a smartphone. Due to her age she doesn’t want to use such devices. A get-together with friends at the supermarket would be nice as well.

A typical process of this scenario could proceed as follows: The customer decides whether to go to the store or to the bakery. If the customer goes to the bakery, he/she will be served by the bakery sales assistant. The customer shows the custom-er card and might be rewarded with a discount depending on the discount points the customer collected. After the bakery sales assistant cashes up, the customer might meet up with friends in the café of the bakery. At last he/she will leave the bakery. If the customer goes to the supermarket, he/she will get a shopping basket or trolley first. Passing the entrance of the supermarket, the sensor system will notice the sensor in the bas-ket/trolley and will start with the time measurement. Then the customer goes shopping the necessary products and meanwhile the sensor system tracks positions and the corresponding timestamps along the route. If the customer has bought everything, he/she goes to the cash point. The cashier requests the customer card and grants a down rounded discount (only cents) on the base price. It’s possible that the customer gets more discounts depending on his discount points. The discount points will be automatically collected when the customer buys products. The amount of the discount points depends on total purchase price and the fre-quency the customer goes shopping. This information is saved in the customer card. As soon as the cashier use the cash register system, the sensor system combines the inserted cus-tomer card data and purchase price with the tracked data of the used shopping basket / trol-ley. At last the cashier hands out the bill and the customer leaves the supermarket.

A BPMN model of this can be found here.

On the basis of the scenario and the business process the project team modeled a value proposition canvas. It summarizes the needs of the targed group (e.g. no usage of smartphones and a discount that down rounds the total basis price) and a solution that can gain values to that needs. In this case the solution is a customer card that doesn’t need to be operate with and includes a sensor technology to provide the time measurement for the retail-er.

The VPC got transferred into a business model canvas. The business model canvas com-bines the important information of the value proposition canvas with further information. For example, shows this model which factors create cost and which factors create revenue. Fur-thermore, this model helps to identify the customer segments that can be targeted with the product/service. In this case the targeted customer segments are older customers, customers that doesn’t want to use smartphones and regulars.

According to a study by the global performance management company “Nielsen” in the year 2016, one third of the Germans try to spend as less time as possible on buying food (Nielsen). The reason for that is, that most students and working persons have too less time for activities like that (dpa). Also in the “nutrition report 2016” can be seen that every fifth customer uses the smartphone during shopping in a supermarket (mbe) . Therefore, the next use case depends on the target group of busy and technophilic customers.

In the second scenario the central character is Sabrina, a medical student. She displays a fictitious role and corresponds the perfect target group for the later prototype. She is new in town and due to her study very busy. For her daily tasks Sabrina has not a lot of time. For every support that helps her saving time she would be very grateful. Shopping food is very time consuming. Nearby is a supermarket where she wants to buy food for her daily needs. It’s very large and some products are difficult to find. A navigation tool which corresponds the products on Sabrina’s shopping list and helps her to find the shortest path to the searched products would be very helpful. In addition, it would be nice if Sabrina can avoid visit the su-permarket if the products she is looking for are not available. Sabrina has always her smartphone with her. So, it would be an advantage if the desired features could be used via smartphone.

A typical process of this scenario could proceed as follows: First the customer creates a shopping list with the retailer app on the smartphone if there is a need to go shopping. After that the customer can check if all the needed products are availa-ble in a chosen branch of the retailer. Then the app scans the database of the supermarket inventory and checks if the products on the shopping list are available and informs the user about that. With this information the customer decides if he/she wants to go to the supermar-ket or another time when the desired products are available again. If the decision is to go shopping, the customer enters the supermarket. It’s possible to activate a shopping list naviga-tion with the app. If the customer uses the navigation, the app informs the sensor system, that the customer enters the shop. The sensor system begins with the time measurement and provides sensor data for the navigation to the app. With this information the app calculates the route and provides the navigation to the customer. So, it’s possible to shop the necessary products with the help of the navigation. At the same time the app tracks positions and the corresponding timestamps of the customer and transfers this data to the sensor system. The sensor system combines the tracked data with the app data and saves it in a database. At last the customer goes to the cash point and pays.

A BPMN model of this can be found here.

Like in use case one, a modeled VPC summarizes the needs and the solution with there val-ues. An example in this case is, that the solution of a mobile phone app with a product availa-bility scan function can prevent inefficient shopping when the most products are not available at the moment.

This model is very similar to the model of the use case 1. The main differences are the con-tent of the “Value Proposition” which is transferred of the VPC, the key activities and the cus-tomer segments. This model focusses on busy customer, technophilic customers, customer who need orientation help.

A survey by the “Department of public opinion research Allensbach” shows that 50% of the participants are looking for bargains (Janson). This buying behaviour can be increased using gamifica-tion. Digital natives can be motivated to go to the supermarket that offers a possibility of being rewarded with bargains via gamification features. This approach provides a strong influence on positive feelings and the decision-making of the customers. An effect like this is confirmed by many studies in this setting (Ebermann). This is the basis of the third use case scenario in this specifi-cation sheet.

In the third scenario the central character is Jochen, a 40 years old bargain hunter and he loves games. He likes to go to a supermarket with many discounts. But mostly the supermar-kets are too big to find all good discounts. It’s also boring and exhausting to find these dis-counts and it’s far away of being enjoyable. He would be happy about an app that shows all available discounts and where to find them. It would be perfect if the app shows him the dis-counts in an enjoyable way in form of a game.

A typical process of this scenario could proceed as follows: The customer goes shopping in the supermarket. There the customer would like to play a game and find some good discounts. On the smartphone he/she starts a gamification app and begins with the bargain hunter game. The app informs the sensor system that the customer enters the shop and start time measurement. The game provides the first discount puzzle to the user that need to be solved. After the customer solve the puzzle he/she will be rewarded with a discount. This discount can be kept or can be used immediately. During the dissolving process the app tracked positions and the corresponding timestamps of the customer. If the user wants he/she can solve another puzzle. The previous process will be repeated or the game ends, depending on the decision of the customer. If the customer finishes the game and closes the app, the app transfers the tracked data to the sensor system. The sensor sys-tem combines the tracked data with the app data and saves it in a database. At last the cus-tomer goes to the cash point, pays and leaves the supermarket.

A BPMN model of this can be found here.

This VPC shows the needs of the targeted group like the transparency of discounts that can be satisfied with a smartphone app that shows the available discounts without searching for them in the supermarket or a prospect. The VPC also highlights the interesting and enjoyable way of finding discounts via the gamification features of the app.

This model is also similar to the models of use case 1 and 2. The main differences are the content of the “Value Proposition” which is transferred of the VPC, the key activities and the customer segments. This model focusses on bargain hunter, technophilic customers, cus-tomer who love games and children.

For the realization of the solutions in the use cases specific features are necessary. These features are:

• Measure shopping time: Like the title of the project points out, this is the main feature that is needed in all use cases.
• Evaluate collected data automatically: This is needed because the information that time measurement and the navigation provides to the retailer are big data and shouldn’t be evaluated manual.
• Scalability: Due to the different structure of all the branches of the supermarket chain, it is necessary that the system is scalable and customizable.
• Indoor navigation: This feature helps to find the desired products faster and is the main feature of use case 2.
• Calculate estimate shopping time: Is a feature that provides additional information to the customer and can motivate to go shopping on an opportune moment.
• Show availability of products: Is needed because of the same reasons as the feature above.
• Use gamification: Is needed to implement a solution as mentioned in use case 3.
• Show offers: This feature makes the searching for discounts more transparent.
  
  
  Not all features are needed in the different use cases, so the following table shows the as-signment of the identified features to the use cases:

The table shows that the most features will be covered by use case 2. That’s the reason why use case 2 will be the central use case. Further work will build on that use case. The feature that is not required for use case 2 will be anyway considered as an optional feature.