Support CentreAdvanced ModulesOperations Guest ProfileProfile Match & Merge - How to Control How We Look for Matches

Profile Match & Merge - How to Control How We Look for Matches

You can control what guests we’ll try to identify duplicates for based on their status during a date range. You can also choose what rules we’ll run through to identify and suggest matches.

These settings are shown at the top of the main Duplicates screen (see screenshot below).

Statuses

  • Arrivals
    • Guests who arrived or will arrive on or between certain dates
    • Works with past, present, or future dates
  • Cancelled
    • Guests who cancelled on or between certain dates
    • Works with dates in the past and today
  • Checked out
    • Guests who checked out on or between certain dates
    • Works with dates in the past and today
  • Departures
    • Guests who departed or will depart on or between certain dates
    • Works with past, present, or future dates
  • In house
    • Guests who are in house (today only)
  • Reservations made
    • Guests who made reservations on or between certain dates
    • Works with dates in the past and today

Date Ranges

For all the following, a day is defined as the 24 hour period from midnight to 11:59 PM for that calendar day (in the time zone that was defined for the property in RoomKeyPMS setup).

Keep in mind that the longer the date range you specify, the more results there will be, so the longer it will take to show you the full set of results.  

  • Last 30 days
    • Includes the previous 30 days (not including today)
    • For example, if today is Mar 27, 2017, choosing “Last 30 days” would show results from Feb 25 – Mar 26, 2017  
  • Last seven days
    • Includes the previous seven days (not including today)
    • For example, if today is Mar 27, 2017, choosing “Last seven days” would show results from Mar 20 – 26, 2017
  • Today
    • Includes today only
    • For example, if it is Mar 27, 2017, choosing “Today” would show results from midnight to 11:59 PM on Mar 27, 2017
  • Next seven days
    • Includes the next seven days (including today)
    • For example, if today is Mar 27, 2017, choosing “Next seven days” would show results from Mar 27 – Apr 2, 2017
  • Next 30 days
    • Includes the next 30 days (including today)
    • For example, if today is Mar 27, 2017, choosing “Next seven days” would show results from Mar 27 – Apr 25, 2017
  • Custom… 
    • Allows you to set a custom date range
    • For example, choosing Feb 1, 2017 to Mar 31, 2017 would include results from both Feb 1, 2017 and Mar 31, 2017 and all the dates in between.

Matching Rules

Show exact matches only

Strict matching. Fastest and most precise.

Only includes guest records where the contents match exactly based on at least one of the following:

  • Name & Email
  • Name & Phone
  • Name & Address (City, State/Province, Country, Zip/Post Code)

Allow up to one misspelling

Tolerant matching. May take a while to process but helps to find records with small mistakes.

Includes exact matches (as above) and also looks for records that have up to one misspelling in each field. Suggested records match on at least one of the following:

  • Name & Email
  • Name & Phone
  • Name & Address (City, State/Province, Country, Zip/Post Code)

Allow up to two misspellings

Loose matching. Takes even longer to process. Finds matches with multiple entry errors but may also show false positives.

Includes matches based on the above rules and also looks for records that have up to two misspellings in each field. Suggested records match on at least one of the following:

  • Name & Email
  • Name & Phone
  • Name & Address (City, State/Province, Country, Zip/Post Code)

What we omit

We do a few things to avoid suggesting false positive results, i.e., records that are not a match:

  • We omit empty fields from being considered as matching.
    • For example, if first and last name match but phone number is blank in both records and no other fields match, we won't show those records as suggested matches
  • We use some rules to hide matches based on invalid data. Specifically, we won't show matching records if the values that matched were not valid. Some examples:
    • First name or last name matched but contained only one character
    • Email addresses matched but weren't valid (i.e., no email address contains the "@" symbol)
    • Phone numbers matched but were not valid (i.e., no phone number with seven digits or more)