Use case identification - Restaurant

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.

To facilitate menu choices, a decision support system is integrated, which, according to the selected parameters, returns images and descriptions of menus fitting the chosen criteria. Relevant parameters include: Kind of meat, Vegetarian, Vegan, Side dish choice (more?). Special needs can be satisfied by including options such as allergies and seasoning wishes, as well as meat options regarding doneness, to ensure customer safety and satisfaction.

If a user chose for example: Meat: Fish, Side dish: Potatoes, appetizer: Salad, no special needs

Menus including those ingredients will be displayed with additional information on them.

After finishing the meal, the user has the possibility to rate the menu (1-5), to further improve the decision support system by showing higher ranked menus more frequently.

Possibility:

• App that allows the user to create his personal profile regarding food preferences, and upon sitting down in the restaurant, the user scans their QR code, to load his preferences and serve it to him.
• Preorder food and appoint a time to get it delivered in the chosen restaurant at the chosen time. Possibility to give update on delays (up until 1 hour before food arrives – maybe have to think of another solution to the problem “customer orders, doesn’t show up” -> has to pay/has not to pay)

Service possibilities:

Payment “database” -> Integromat writes to an excel sheet, to keep record of all transactions

Receipt -> Integromat sends an email to the guest or a notification to the application regarding his order. Non onboarded users can choose if they want a print-out version or a digital one (email)

Decision Support System -> mongoose aggregation on database, to return desired rows according to input.

Incentive for feedback -> offer coupons for feedback, like 5% on the next order, or after 20 recommendations receive one coupon with 50% off or a free meal. Rating helps overall quality of the recommendation system -> desired!

Possibility (for preorders) to use any voice recognition service (e.g. google assistant) to place the order, as well as to update the restaurant on an upcoming delay.

Use of Conversational AI (Dialogflow):

• Social media presence -> Twitter bot that answers to common questions.
• “Can we contact you/phone/email” etc. requests will be replied to directly on twitter with our contact details.
• “Advertisement” for companies that chose our product, if the bot is tagged with “Your product is great” or similar, our bot posts about the restaurant using our service (limit to once per restaurant per week or something?)
• Preorder food via conversational AI -> 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.