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0. Introduction


As these pictures show, Lobster Land is a fun, low-key place with a range of entertainment options.1

Lobster Land serves as the backdrop to most of the marketing analytics examples used throughout this book.

Lobster Land is not an actual place. It is a fictional theme park, based in southern Maine, approximately 90 minutes from Boston by car. Lobster Land has the basic sorts of things that you might expect to see at a seaside amusement park – rides, food, souvenirs, places for visitors to simply relax, and an arcade with video games and other types of amusements. Each year, the park opens on Memorial Day (the last Monday in May) and closes on Labor Day (the first Monday in September).

Lobster Land maintains a low-key, unpretentious seaside atmosphere. While the park is wholesome, clean, and takes pride in the professionalism of its staff, it also remains affordable and accessible to a large swathe of the local population.

The Ferris Bueller has appealed to riders of all ages, for generations. 2 

Visitors to Lobster Land use park-issued bracelets for everything from payment to ride entrance.  From a data collection perspective, these wristbands create a treasure trove of value – they enable the park to collect richly detailed information about visitors’ activity patterns during their time at Lobster Land.  Lobster Land can use this data to answer macro-level questions (e.g. During what times of day does the park see peak ridership?) as well as micro-level questions (e.g. Does this particular visitor tend to be more focused on rides, food, or games?)

Lobster Land visitors use these wristbands for ride entry, payment, and access to all park attractions.  Their usage enables rich data analysis for Lobster Land’s analytics team.3

From a marketing analytics standpoint, Lobster Land offers a myriad of opportunities.  Using Lobster Land as a business case, we can analyze the impact of e-mail marketing campaigns on merchandise revenue, segment the season pass holders into distinct groups, study the impact of rainfall on park revenue, predict the likely actions of specific customers, and much, much more.  


1 https://www.pexels.com/photo/blue-and-red-striped-mat-on-green-grass-field-5123348/
https://www.pexels.com/photo/woman-in-gray-square-neck-mini-dress-and-white-sneakers-walking-on-street-with-ferris-wheel-background-2869375/
https://www.pexels.com/photo/people-riding-on-bump-cars-4123545/

2 https://unsplash.com/photos/qcHaE3QEF90

3 https://unsplash.com/photos/GT-S3X3mSnE