Gaming

Online and offline gaming have massive potential for using analytical data to monitor, understand, optimise and personalise the player experience in real time. By doing this well, you will be able to improve conversions and customer retention metrics by building the most engaging gaming experiences.

The industry is also a common target for criminals and fraud, so it is important to detect the validity of customers and transactions and continually monitor for anomolies in how people are interacting with your site for both revenue protection and regulatory reasons. At the same time, it is important not to block genuine transactions and frustrate your best customers. Using sophisticated real time and intelligent analytics is the key for meeting this balance.

Finally, there are important social responsibility considerations in the gaming industry such as detecting vulnerable customers by monitoring spending patterns and time spent playing. Analytics can help to alert to these situations quickly in order to protect the customer and avoid reputational damage or regulatory risk.

Example Use Cases

Timeflow integrates with a range of websites, applications, APIs and other data sources across your business to identify and respond to key situations of interest. Examples specific to this industry include:

Example 1 – Vulnerable Customer

A customer logs on and makes a number of small deposits. Over time the deposits grow and then become very large and very frequent after a series of losses. Timeflow detects this and sends additional information to the customer to encourage responsible gaming. A manual review is also instigated by the relevant team.

Example 2 – Gaming Integrity

A gamer manages to achieve a win rate which stands out as an anomaly vs other similar gamers considering their time on site. The account is instantly and automatically suspended pending a manual review by a team member. Relevant alternatives are suggested to the customer whilst they wait for this to take place.

Example 3 – Customer Retention

A regular customer visits the site at least 3 times a week for at least a 30 minute gaming session. After a period of two weeks, the customer has not returned. This situation is identified and an offer is generated by email to encourage their return.

Example 4 – Dynamic Pricing and Odds Calculation

Odds are offered for betting on a sports event. One outcome is detected as having less money wagered than expected considering the displayed price. This information is surfaced to odds compilers and algorithms in real time to more accurately balance the market.