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Appointment Conversion

Appointment Conversion

Out of Box
Configuration
Updated:
October 30, 2024

Appointment Conversion

Appointments are registered via the In-store Calendar or Online Booking. The Appointment Conversion KPI shows the captured data with a regional, store, employee, and appointment table view.

At what levels is the data present?

Traditionally, the calculations include:

  1. Total Stores
  2. Total Customers
  3. Total Appointments
  4. Total Appt. Check-in
  5. Total Appt. Converted
  6. Total Turnover
Click on a region to see store level data
Click on a store to see employee level data
Click on an employee to see customer level data

How a conversion is made

  1. The customer books an appointment
  2. The customer arrives for their appointment xx days later, and the employee checks them in
  3. Clientela immediately sets a window, that if the customer makes a purchase xx days the appointment is converted
  4. The customer makes a purchase the following day online, or made a purchase in-store the day of
  5. Clientela checks nightly, and when it finds a new purchase, it will then attach the transaction amount and date to the appointment
  6. Now the transactions has been attributed to both the appointment, and creates context for any future occasions that generate.

We normally track this with a 3 day window after the appointment has been checked-in.

Filters

These can be configured, turn off, or completely custom:

From / To Date Picker Control the date view by month, week, or day

Market or Region Change the geographic location of your data eg: United States, France

Channel Change where customer's came from eg: eCom, In-Store, Events, Online Booking

Store Change what store data you would like to see eg: Select All, Several, One

Department Change what area of data is visible eg: Women's, Men's

Employee See data at a singular employee level

Appointment Conversion

Selfridges Appointment Conversion

Conversion attribution is configured to inspect & assign transactions to appointments based on timestamp relation. Standard Clientela rules apply to appointments.

  1. 1 - 13 days 23 hours 59 minutes time frame
  2. One:One Transaction mapping
  3. Inspection of multiple appointments, multiple transactions

Scenarios

Customer has 1 appointment, 1 transaction

  1. There is 1 transactions
  2. Transaction 1 amount comes after 3 days.
  3. We need to override the appointment with the transaction 1 because it time is less than the transaction 2.

Customer has 1 appointment, multiple transactions

  1. There are 2 transactions : Transaction 2 comes first and then Transaction 1 and Transaction amount comes after 3 days.
  2. We need to override the appointment with the transaction 1 because it time is less than the transaction 2.

Customer has 2 appointments, multiple transactions

  1. Customer has 2 appointment
  2. Transaction 2  is associated with appointment 1
  3. Transaction 1 comes in and we associate that with the appointment 2 but the expectation is:
    1. Appointment 1 with the Transaction 1
    2. Appointment 2 with the Transaction 2
  4. Clientela then swaps the values of the transactions.

Customer has 4 appointments, but only 3 transactions

  1. It will work considering the transactions time in order.
  2. Transaction 3 that is associated with appointment 1
  3. Transaction 2 comes in then we will check if the transaction 2 is less than transaction 3, then it will swap the transaction for the appointment 1 and appointment 2 (that means Appointment 1 will be having transaction 2 and appointment 2 will be having transaction 3)
    -- Now we have
    -- Appointment 2 -> Transaction 3
    -- Appointment 1 -> Transaction 2
    Transaction 1 comes in then we need to fetch all existing appointments of that customer which do not have an amount added and then we will map the earlier transaction with the first appointment and so on (i.e. in the increasing order.
  4. Here 4th appointment will not be converted.

Changes required

Currently we are not saving the transaction data at our end. We are directly mapping them with the appointment and occasions. As the transaction comes in, we pick the first appointment and associate the transaction with that appointment, If another transaction comes in then we pick the another appointment and associate the second transaction.
But as per the expectation, we need to Swap the transactions for the existing appointments for the client based on the transaction time in the ascending order. So always, the transaction will be linked in the following order.

  • Appointment 1 => Transaction 1
  • Appointment 2 => Transaction 2
  • Appointment 3 => Transaction 3

Notes

  • When transaction comes in we check previous 3 days appointments only.It means we are using the 3 days window to mark the appointment as converted. e.g. if the Transactions comes in with the transaction time in the API = 2024-10-18 11:30:00 October then we check the appointments created between 2024-10-15 11:30:00 to 2024-10-18 11:30:00 and if any appointment is available in this duration then we mark the appointment converted.
  • If the appointment is marked as converted and we need to fetch the amount, then we are not using the 3 day window, we are fetching the amount until we have the amount associated with the appointment but we start checking those after 3 days using the CRON.
    • Example:
      Appointment 1 created on 10th October then it's amount will be checked after 3 days i.e. on 13th and it will be called continuously on every 3 hrs until we get the transaction amount.
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Highlights

Configuration