Dec 15, 2018
Lessons in Analytics From Mobile Gaming — Age of Magic
Segmentation, Progression, Recursion, but It’s Just A Game
I have been a life long fan of turn-based strategy games. When I was young, that was the best you could get. But as I got older, life and family made it really convenient to play games that don’t require 100% of your attention 100% percent of the time. In fact, that family thing basically assures you will never have 100% for anything ever again. But this article is not about me or my battle with maturity, it is about the analytic lessons you can draw from mobile games. To that end, let’s talk Age of Magic.
I am also a huge fan of simulations, but TBS games rarely fit that description. There activity is discreet, where as real life is often continuous. While this is easy to recognize in a game like Age of Magic —clearly divided by turns/rounds, areas/arenas, and battles/campaigns — it is a much more illusive concept for many analysts.
Analysts model real life whether in algorithms, equations, spreadsheets, or data visualizations. Each model may utilize discreet or continuous metrics. Many analysts struggle over this distinction, sadly because they often overlook it entirely.
TBS gamers should know better.
Campaigns in Age of Magic use a discovery process. Each iterative or progressive step only unlocks when the prior step/battle has been successfully completed. Once again — the game creates a clear and easy path where analysts often struggle. Many an analyst has been frustrated in efforts to skip clearly required steps along their journey.
Also similar to analytics, Age of Magic creates strong incentives to convince players to go back and repeat prior battles and campaigns. It is often the only way to collect required gear or supplies for advancement (short of in game purchases). Recursive progression is a very real analytic process — it is great to see a game that models it. I just wish they would add a dotted line path to make identifying the step number easier (currently requires a hover).
For the FPS enthusiast, Age of Magic’s combat system might be disappointing. Positions and location do not matter even a little. The combatants line up in opposing groups. They don’t move (other than to temporarily jump across the board and smash, slice, or poke an opponent). Even front row vs back row seems trivial.
For analysts, this should feel pretty natural. With the exception of those working in GIS or with heavy geo-location based data — things don’t really move. Even for those working with a lot of geographic data, the data is typically batched, discreet, and indirect. This effectively means that position and location are just data elements — sorry analytics is only “like” a game.
Like many analytic-like mobile games, Age of Magic features plenty of scoring, segmentation, levels, and filtering. Game interfaces and engaging business intelligence tools continue to evolve closer and closer together, but this game really takes it to a high level.
Characters have classes, levels, abilities, and equipment. Each of these attributes require iteration and progression. Each is scored by addition levels and ranked on various dashboards. Along the way, they can be filtered by race, class, power, rarity, and other dimensions. It is a veritable banquet of analytic concepts.
We could certainly continue. Age of Magic provides a background story line. Is it great story telling? Perhaps not — but it would hold its own against the typical storytelling needs of analytics. Quests and challenges create an interesting array of criteria and incentives. Combat includes numerous calculations and random number generation events. Like most combat games, there is a lot of probability involved.
That said, like any good model, it is more educational to use it than to simply talk about it. So have fun playing. Thanks for reading. And keep an eye out for lessons in analytics — you never know what you might learn.
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