Usecase Identification - DigiBP/DigiBP-SIMME GitHub Wiki
Restaurant preorder system
Customer journey and why this is a good idea!
General digitalization
Restaurants use waiters to get the custom orders of each client. Digitalizing the ordering process would reduce the waiters needed to fully operate a restaurant, as the ordering process would not need any human involvement, as long as the client has all the necessary tools to order the desired menu.
Preordering of a menu
People with e.g. rather short lunch breaks have to give up on the option of having lunch in a restaurant, due to time related factors such as travel, the ordering procedure and especially the time it takes to prepare certain meals. To remove any possible time spent in the restaurant ordering and waiting, our application allows customers to preorder a menu at a given restaurant for a certain time. This allows for the meal to be served shortly after the guest has sat down, cutting down on the guests wait time and the average seating time per guest, allowing the restaurant to potentially increase daily guests (new customer group). Additionally, the customer benefits of shorter waiting times and a faster service, if the guest does not fancy to have a lengthy restaurant experience.
Restaurant review system
Guests can leave a review for a restaurant via app, and this information can be accessed to scout for good restaurants or avoid certain ones.
Use of conversational AI
- Preorder food: enable customers to use common services (google assistant, cortana, facebook messenger) to book a table or to preorder a given menu at the restaurant of choice for a given time.
- Social media presence (has been implemented as a test): Twitter account that promotes our product and interacts with potential clients of our product. All onboarded restaurants will be marketed via our account to increase awareness of the product.
Product features
- General restaurant reservation system for restaurants
- Preorder and scheduling functionality to attract new customer groups
Undesired cases
- User preorders restaurant at a given restaurant and doesn’t show up. The price for the given order will be booked at the confirmation of the preorder to avoid scam. Solution: Payment on order confirmation