Real Time Offer Management

realtime_img-1A year or so ago for family reasons I needed to head back to Europe from a fantastic job at Marina Bay Sands in Singapore.  The experience of working in an Integrated Resort (Hotel, Casino, Retail, Conference Centre) is one that is still the high point of 30 years of working in IT.  Heading back to Budapest and wondering what to do with my time I decided to embark on a private project I called “Realtime Offer Management” hoping to get it into a startup.  While the startup part has yet to materialise the experience of building out a PoC for the concept has been enlightening and highly instructive on how to approach these type of applications.  Version 0.1 of the PoC is finished and I am now building v0.2 to capture the feedback received over the year and also refine the rough edges of v0.1

This is the first of a series of blogs about the application I am building and my thoughts on this area of focus for Hotels, Casinos, and virtually any organisation that has interactions with guests, patrons, customers in a manner that they want to provide rewards based on an immediate response to interactions with elements of their organisation.

So first to clarify what is “Realtime Offer Management”, in essence it is the ability to act immediately on any interaction of a customer with your property/business, examples would be;

  • Checking in/out of a hotel
  • Paying for a meal
  • Carding in/out of a slot machine/table in a casino
  • A spin on the slots, hand of cards
  • Parking your car, or using the valet service
  • Walking into the property/business
  • Being in a specific place
  • etc

Each of these activities is in essence an “event” and has a set of information (actually quite small) that is of significant relevance when plotting customer engagement with your business.  By having that ability to capture these “events”, register the individual pieces of information against a known entity you can build a set of rules to react to customer engagement and trigger relevant offers based on history, preferences and location.

To put it in context, simple examples would be;

  • Reward a person for the n-th visit to the Hotel, Restaurant
  • Reward a person for visiting X restaurants and spending an average of Y in Z days
  • Incentivise a person to remain on the property based on events such as good/bad luck in the casino
  • Interact with people while they are on property or even within their gaming environment
  • Incentivise a person to return to your property
  • +++

The Enterprise Architecture approach to this challenge has pretty much always been in one of the following formats;

  1. Build out custom code to monitor for specific events
  2. Use “big data” to massage the operational deluge of data and then write code to work off the results
  3. Use a combination of BPM, Event Management, ESB software (such as Tibco, etc) to build event management suites
  4. Use commercial rules engines and build out complex algorithms to meet individual requirements

Each of the above is not a wrong approach but is an approach that involves “building code”,  “analysing operational data” and is pretty much “invasive” to the operational landscape, they are also fairly expensive to implement.  They also have these drawbacks;

  1. Highly customised and requires coding to making it work for each individual event
  2. Needs significant investment to make if work fast and also falls prey to time lag due to ETL, analysis and other constructs of a data analysis environment
  3. Again whilst touted as code free, this approach is highly IT dependant and rarely free of some (or lots) of coding for decision making nodes
  4. Same as 3.

I decided to take a step back and try to look at the problem/opportunity in a completely different manner, the first was to rethink how we view data about a person within the organisation, the second was to look at how to structure rules focused on the specific problem domain that is “Hospitality and Gaming” within a “Realtime Environment”.  The third and most important was to try and arrive at a position where marketing could configure Offers without resorting to pseudo-coding or IT assistance.

Over the next few articles prior to the release of v0.2 of the PoC, I intend  lay out my though process for the approach to this area and in a sense document why I approached the problem-domain in the manner I have.  If you are interested in what I am doing I would ask you to please engage with me via the comments section, all opinions are welcome and will help me in the launch of the next version of the solution.

As a teaser for the next instalment  of this series, what would be your reaction if I said “that in an integrated resort (Hotel, Casino, Retail, etc) your need to monitor less than 10 transactions with a total combined set of less than 70 pieces of information in total to drive an efficient realtime offer management solution, and you do not need a data warehouse or to spend $m on a solution?”.

 

 

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About Brian Maguire

Working in IT for 30+ years. Recent position was Global Enterprise Architect for Las Vegas Sands Corporation. Currently immersed in the startup scene in Budapest.
This entry was posted in Architecture, Gaming, Hospitality, IT Strategy, Product Development, Realtime Offers, Software Development. Bookmark the permalink.

2 Responses to Real Time Offer Management

  1. Pingback: rtom #2 – Design Overview | Brian Maguire

  2. Pingback: rtom #3 – Approach to Data | Brian Maguire

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