How to use big data analytics to boost customer retention

Although current growth projections offer significant opportunities for gaming companies, this market in particular is fiercely competitive. Potential and existing customers are being saturated with marketing regarding new products, services and special offers of all types. Therefore, attracting new customers and understanding current ones, in order to encourage brand loyalty, is becoming more important than ever. In order to do this, it’s important that businesses are able to differentiate themselves from the ever-expanding pool of competitors.

For both providers and customers, the registration and ID verification process associated with online gaming can be somewhat of a bugbear. Last year, a Europe-wide survey of school students aged 15 and 16 found that one in eight frequently use online gaming sites, highlighting the need for strict ID verification. While in the US, security is paramount due to age restrictions and state-specific laws that differ according to which state the customer is in.

But while it is vital for online gaming companies to screen new customers and ensure that there is no illegal or fraudulent activity at play, lengthy registration adds friction to the user journey, potentially causing new customers to drop off and look elsewhere. There are customers who visit a website or an app, go through registration, and then drop off due to an inconvenient and drawn-out signup process such as requesting copies of driving licences. Even losing 10% of potential players because of this can radically harm revenue, something which is avoidable by implementing the right tools to optimise registration processes.

Big data analytics software can provide an efficient and modern form of ID verification by harnessing a customer’s existing digital footprint to drastically improve the user experience. Following consent from the user, in simple terms these tools assess both the quality and quantity of data available about an individual, ensuring it is consistent, meaningful and real. This use of big data can assess whether an individual is who they claim to be, in real-time, without affecting the experience of the gamer.

While it is relatively easy for fraudsters to create fake email addresses or accounts, it is much more difficult for them to fake an entire, active, interconnected digital existence and persona, which is why a digital footprint can be such an effective form of identification. Big data analytics tools can also be used to prefill lengthy forms with basic personal information, speeding up the application process when registering a new customer, and verifying those that may not have enough traditional data to pass standard identity checks.

While it is one thing attracting new customers to sign up to your service, it is another to retain your customer base and create loyalty by building meaningful relationships with them.

Opportunity knocks

Current processes mean that it can take months to identify patterns in consumer behaviour and spending habits in order to effectively predict future behaviour and personalise marketing activity. Gaming companies rely on analysing how players interact with games to derive insights such as “this user has bet on local cricket matches regularly over the past six months, more often at the start of the month, and only when the odds are 4:1 or better”.

While this may result in more effective marketing over time, it is a very lengthy process and the risk of losing customers in this time period is high due to attractive sign-up bonuses and first bet offers from competitors. Likewise, the time it takes to identify VIPs based on gambling habits means that you risk missing out on opportunities for maximised spending and compromise the likelihood of retention.

It is easy to miss opportunities and lose custom when relying on one-size-fits-all or impersonal offers. For example, a customer who places bets solely on horse racing is unlikely to take up your offer of enhanced odds on the Liverpool vs Man Utd match on Saturday. Sending an impersonal notification of an offer which is not relevant to their interests or hobbies may lead them to switch off their notifications, ignore future prompts, or even delete your app from their device entirely.

While, as previously mentioned, many companies do segment customers and personalise offers, they do this based on monitoring and analysing habits over time, which means that during the first crucial months following onboarding, the customer will receive generic offers, rewards, and experiences, some of which they might find irritating.

Even personalised rewards and offers can damage customer relationships if done incorrectly. Just because a customer consistently plays from Manchester doesn’t mean that they support a Manchester football team, or any football team for that matter. Similarly, sending prompts at the wrong time of the month, such as the week before payday, could mean businesses are likely to miss out on customer spending.

Through implementing big data tools which analyse an individual’s online footprint, you can gain valuable insight into gaming preferences, likes, dislikes, and life events which can then be applied to provide customers with personalised offers. For example, if someone has just had a positive life event, such as a promotion or engagement, a special discount or free game to celebrate will make them feel valued and add to their experience.

Targeted offers like this could also be used as part of a loyalty scheme for regular customers, which will further encourage brand loyalty. An individual’s online presence can also give clues about their location. This could be particularly beneficial for US companies as they could provide offers for their site while a customer is in a state that allows online gaming.

In a sector as crowded and competitive as the gaming industry, companies need to do everything they can in order to stand out – from tackling identity verification problems, to ensuring their customers are only contacted with relevant offers and information. Those companies who embrace big data quickly will drastically improve their odds of success.