Behavioural Analytics and the Gaming Industry


Posted By Pinar Dost ⋅ April 8, 2019

How data creates must-play mobile games

It’s official; the gaming industry is bigger than Hollywood. In fact, for eight consecutive years , games have brought in more revenue than the film and music industries combined, according to recent research. Market predictions place the global worth of the games industry at more than $180.1 billion by 2021, a staggering increase from its 2018 value of $137.9 billion.

Look no further than the phone in your hand or pocket for a reason why; mobile gaming now accounts for half the global market, and revenue has surpassed that of console and PC formats. With a ready-made mobile gaming device within reach at all times, app-based games like Angry Birds 2 and Geometry Dash have helped create a new type of gamer – less dedicated than die-hard PC or console gamers perhaps, but no less lucrative to games manufacturers.

Mobile games tend to be easier to pick up and play without much instruction, as well as being easier to dip in and out of. Simple game objectives mean producing mobile games is generally quicker and less expensive than developing a character and storyline-driven epic, but a rapidly-growing market and plentiful competition too. To give them an edge, many mobile game developers are turning to data about casual gamers and how they play to inform the game design process.   

Learning what gamers want from mobile gaming experiences enables developers to boost engagement levels in a multitude of ways, as we explore here. 

Drawing from unstructured data

The nature and worldwide popularity of mobile gaming creates huge datasets on a daily basis, but it’s very much ‘unstructured’. Unstructured data can be information in any given form; it’s a mix of different data types (text, figures, images etc) without an organisational data model or classification system – a kind of data hodge-podge. It can contain a wealth of actionable insight, but its lack of structure makes this unstructured data tricky to analyse, even when it’s all in one place.

Gaming companies like Big Fish, the minds behind Cooking Craze, have surmounted this challenge by building bespoke data analysis platforms capable of dealing with the exact kind of unstructured data their games generate. Developed alongside IBM, Big Fish’s custom-made solution enables them to crunch the unstructured data from their games, combined with relevant open data, and assess what gamers like and don’t like, and what keeps them coming back for more. They can then use this information to create new games rich in the features gamers love.

Keeping games just the right level of challenging

Casual gamers want games that don’t require major time investment to play and, while they expect a game to get gradually more challenging, there’s a limit to how many times they’ll attempt a tricky level. With so much choice out there, it doesn’t take much for gamers to lose interest in a mobile game in favour of one of its competitors.

During gamer data analysis of its smash hit Candy Crush Saga, King Digital Entertainment realised that lots of players were getting stuck and subsequently abandoning the game at the same point – level 65. Data progression funnels showed a steep drop off in engagement rates at this stage, and considering the game has 725 levels, that’s an awful lot of game not getting played. After recoding to adjust the difficulty of level 65 King saw the data start to reverse, and game retention increase.

Integrating social media and personalised ads

Like many app developers, the makers of mobile games have taken advantage of cross-app registration to support game play. As most smart phone users know, it can be far quicker and more convenient to link a social media account when registering for a new gaming app, especially when all they want to do is start playing. Connected accounts can also be used to save an individual player’s game progress to the cloud.

In return for quick and simple set up and saving, game developers can add social media information to its data sources when analysing gamer behaviour, which can add a whole new level of preference and social media listening insight. Combining data generated by their own games with that from gamer’s social media accounts not only enriches their investigations of how gamers interact with games, but allows them to tailor in-game ads depending on what individual gamers are interested in.

Research shows that casual mobile gamers have no problem with ads in principle (especially in a free-to-download game), but ‘think less’ of games that fail to personalise the content of what they promote. With the array of personal information available via social media, gaming companies can finetune what they advertise in line with their player’s consumer habits.

How behavioural analytics can refine your consumer offering

Just like game developers, other types of business can leverage the intelligence in consumer data to give their customers more of what they want. In many cases, data is held within a business yet not mined for what it can reveal – all that’s needed is the right data analysis approach.

At Quant, we can help your business sift through the data your company holds to find an investigative approach that aligns with your key business objectives – simply get in touch to find out more.

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Categories: Big Data, CRM, Insight, Seize the Data


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