Be it the popularity of Mortal Kombat, Mario Kart, and now Fortnite, the global gaming industry has largely been successful in attracting and increasing its number of gamers. With over 2.3 billion active players all across the world, the global gaming industry stands at a worth of around $138 billion for the year 2018.

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Thanks to its growing pool of online games and players, the online gaming industry is generating large volumes of data on player interaction, game levels, and average scores making it suitable for some insightful data-based analytics.

Be it in improving game design or development or in visual effects, Data Science is being effective in expanding the overall reach of the online gaming industry. This is very evident in the growing popularity of the online battle game, Fortnite that is being played by over 125 million players and has generated overall revenues in excess of $1 billion since its release. Hosting more than 3 million active players at any time, the average Fornite player is spending 6-10 hours each week playing this engaging game.

So, what are the main aspects of games like Fornite and PUBG that are hooking increasing number of online players? In his best-selling book, “Hooked: How to Build Habit-Forming Products” published in 2014, Nir Eyal describes how the 4 main steps of his “Hooked model” enables technology companies to develop and use hooks that attract users to a favourite product or service and engage with them on a continuous basis.

So, how are popular games like Fornite and PUBG leveraging from both Nir Eyal’s “Hooked model” and data science to engage with increasing number of players across the globe?

Let’s first look at how the hooked model is improving user engagement particularly in the gaming industry.

How the Gaming industry is adopting Hooked model:

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In his book “Hooked”, Nir Eyal points out that just attracting users to a great product or service is no longer sufficient to building a great business. Companies need to build products that can change user habits and hook them to using the product on a daily or regular basis. Nir points out that once a user habit is formed, they are automatically triggered to use a product or service (for example, play an online game like Fortnite or look for entertainment videos on YouTube) without relying heavily on online ads or promotions.

So, what is the Hooked model and how is it being leveraged by the gaming industry?

As illustrated, the hooked model comprises of the following 4 steps, namely:

  1. Trigger

The hook model starts with the “Trigger,” that prompts users into the first action. An effective trigger is a combination of external trigger (example, a Facebook invitation, a marketing e-mail, or a friend notification on Fortnite) and an internal trigger (example, negative emotions such as boredom or the social need to connect with friends on Facebook).

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Online games like Fortnite use a lot of external triggers such as sending interesting notifications to the player’s friends to join the game. It also combines the external triggers with appropriate internal triggers that appeal to the need for socially connect with friends. In addition to inviting friends, you can do online chats with them and even watch them play the game.

  1. Action

The Trigger step of the Hook model is followed by the “Action” step that prompts an online user to be motivated enough to perform the required action (example, accept a Facebook invitation or join the Fortnite game). According to Nir Eyal, the action must be made simple enough to increase its chance of being executed and completed (example, completing just a few steps to start playing the Fortnite game).

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To ensure simplicity and ease of use, the Hook model recommends the following 6 elements (as recommended by BJ Fogg’s Behaviour model) that must be kept to a minimum to complete any action:

  1. a) Time required to complete an action
  2. b) Money or cost of completing an action
  3. c) Physical effort required to complete an action
  4. d) Brain cycles or the mental effort required for an action
  5. e) Social acceptance of the user behaviour
  6. f) Non-routine or the impact of the action on existing routines
  7. Reward

Have you ever wondered why slot machines in casino shops are so enticing to gamblers? It’s because of the unpredictability and surprise element that appeals to our human desire. The Hook model enshrines the power of the “variable reward” step that brings the same element of unpredictability into the way we interact with products (example, scrolling down our Facebook feed).

The Fortnite game leverages this element by building uncertainty or unpredictability around every game session. For example, Fortnite players are not certain of who their opponents will be in each session or the virtual terrain that they are playing on. Variable rewards appeal to the user’s internal triggers thus satisfying their need for virtual entertainment.

  1. Investment

The final step to completing the Hook model is when the user makes an investment back into the product (or service) that could be in the form of time engagement, data, or even capital investment. The investment element increases the probability of repeated user engagement with the product in the future. Example, data-based investments can be leveraged by the business to understand customer preference and to improve personalization.

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The Fortnite game improves its bottom line revenue by allowing its players to personalize their game characters by purchasing customized outfits and even their dance moves.

How Data Science leverages the Hook model

Based on the type of investment made by users in the Hook model, data analytics can derive valuable gaming insights based on how players interact with their games. Data-based insights are driving gaming innovation and design thus making games like Fortnite more appealing to new players.

How is gaming data driving game enhancement?

Along with innovative visualization and animation skills, gaming programmers are using data science technologies like artificial intelligence and real-world image recognition to create a more natural gaming environment and to replicate natural human movements within the game. Gaming companies may have a large base of online players but have few active players, which means that most players are no longer attracted to the game. Data science techniques like personalization can be used to increases player engagement and the number of active players. For instance, Fortnite implements personalization by allowing users to create their own customized playing characters.

Apart from the use of personalization in game development, personalization in the marketing of products including online games enables product companies to effectively target their desired customers. On the other hand, personalization is also desirable for online users to escape from an overload of digital advertisements or promotions. Based on the data collected from user interactions, companies can create personalized and meaningful marketing messages to be delivered to the right customer base. Personalized marketing can in turn, increase user activity and foster their habits as they respond more favourably to marketing messages.

Conclusion

The use of the Hook Model is effective in building good products (including online games) that can change user habits and improve user engagement on a long-term basis. The use of data science to create a personalized customer experience is generating higher customer lifetime value (or CLV) for companies including gaming enterprises.

The adoption of data science techniques like AI and image recognition is transforming various industry domains including the online gaming industry and is proving to be integral to game design, development, and marketing.

On that note, we complete our thoughts about the role of data science and the successful Hook model in the online gaming industry. Do let us know if you agree with the role that data science is playing in this fast-growing industry sector? Do leave behind your opinion in the Comments section below. Do also check out some of our online courses in the field of data analysis and visualization. 

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