1. Fetching Available Stylist:

Finding a stylist was one of the major issues as you need to assign a list of stylists based on their availability on the same date and location mentioned by the user. An array of stylists were sorted out based on their special availability corresponding to the user location and service date to resolve this issue. Our backend team managed this filtration through its custom filtration algorithm. This makes the entire process streamlined for both customers and beauty professionals.

2. Set Reminder:

Once when a customer books his/her appointment, the appointment time needs to be fed in the user's device's inbuilt calendar. Here, users are fired notification an hour before to remind them about their appointment. To maintain the overall app scenario in iOS and notify the user regarding their appointment was difficult. The iOS app developers managed such complex scenarios with the implementation of Alarm Interface along with their custom algorithm.

3. UTC Time Zone Management:

Here, the technician set their availability in the technician app, which is displayed to the customers during service selection. But, if the technician is positioned in another country and sets their availability for another country, maintaining UTC zone synchronization was necessary. It was getting difficult to maintain uniformity of the available timezone. A user selects a particular shift to say noon shift, which is converted into morning shift as per another country's current UTC zone. Our developers managed their scenario quite smartly through their customized UTC conversions and maintained uniformity in selected availability shifts.

4. Auto Stylish Assessment:

If a customer books his/her appointment with a particularly stylish, then a request notification is sent to that specific stylist. However, in any case, if that stylist does not approve the request within 10 minutes, it is auto declined, and the list of other available stylist is fetched as per the user's selected date and time shifts. The entire filtration process to list out the rest of the available professionals based on users' selected date and time shifts was quite complex and rigid. With their custom algorithm, our developers managed the filtration that helps the system auto-assign the task to the available stylist from which the user can select the best available stylist.