Strict Standards: Declaration of JParameter::loadSetupFile() should be compatible with JRegistry::loadSetupFile() in /home/content/94/5783694/html/intelligencia.co/libraries/joomla/html/parameter.php on line 512

Warning: Cannot modify header information - headers already sent by (output started at /home/content/94/5783694/html/intelligencia.co/libraries/joomla/html/parameter.php:512) in /home/content/94/5783694/html/intelligencia.co/plugins/system/jat3/jat3/core/parameter.php on line 107
Identify likelihood of return

Thanks For Your Feedback!

Email
Subject
Message
Five plus seven is? (answer as number)
Open/Close

Facebook Comments

Click to open/close fB Comments
RSS

Intelligencia.co

Identify likelihood of return

In addition to having some information that helps determine to which offers a patron is most likely to respond, it would be nice to know exactly when a patron was planning on making their next trip. Although we might not know exactly when a patron is likely to return, fortunately we can make a pretty good prediction about it. There are a variety of methods that range in complexity that can be used to assess when a patron will return, including frequency analysis, regression, and survival analysis. Knowing when a patron is likely to return is beneficial as it helps to identify patrons that haven’t made a trip in the expected amount of time and are at risk of leaving. First, the business needs to have an idea of the average or median time between trips. This might need to be segmented based on geography, worth, or even historical frequency. Patrons that have not made a trip within the decided amount of time for their segment are subsequently flagged and dealt with appropriately.  

Historical data can help identify segments of patrons that are expected to make trips weekly, monthly, quarterly, annually, bi-annually, and so forth. Marketing can integrate information from predicted worth, optimal offers, and time to next trip to maximize campaign success in a number of ways. The business can save money by adjusting the frequency of offers for patrons that are not identified as likely to come back for longer periods of time. Instead of sending the patron monthly offers, they can sent quarterly offers with longer valid windows that allow more time to book. Or, for example, if the patron only comes annually around his/her birthday, we might only send an offer annually around the patron’s birthday. Conversely, campaigns might be created with the goal of increasing the frequency of visits from higher worth patrons. Casino marketing should have the goal of generating trips sooner than expected and converting patrons into more frequent visitors. Additionally, time to next trip analysis can be used to identify when it has been too long and the business is at risk of losing the patron. In this case it might be useful to send an offer using “last chance” or “we miss you” messaging. The offer might also need to be slightly better than what the guest has received in the past. By knowing when a patron is likely to return, casinos can adjust marketing strategies appropriately in order to save money on mail costs, retain guests, and increase loyalty.

&