Today, we tackle calculating the average casino session duration per player, which is often challenging primarily because of the substantial data load associated with individual game spins. Systems can struggle to capture and analyse data efficiently due to the large scale of data received on the game spin level, hindering the optimisation of gaming experiences.
The Problem: player session automation challenges
Automating player session insights is a big challenge. Systems can struggle to capture and analyse data efficiently, hindering the optimisation of gaming experiences. As we all know, understanding player behaviour is vital for tailoring services to preferences. Without it you will miss out on valuable insights that allow gaming operators to tailor their offerings and services to match player preferences.
When there’s a gap in comprehending how players engage with the platform—such as not knowing the average duration of their gaming sessions or the specific games they prefer—it becomes challenging to make informed decisions to enhance their experience.
The Solution: Unlock precision with Flows
Flows revolutionise this process with no-code automation. With Flows, you can effortlessly set up workflows to automate player session insights on demand. Seamlessly capturing and processing time-related data, Flows provides a holistic view of player behaviour, empowering strategic decision-making and allowing you to transform data into a winning strategy with Flows.
Behind the scenes – How it works in five simple steps
So, how does it work? For this purpose, we will have to define three different Flows that will be interconnected between themselves.
1: Logging game start times
In the first part, Flow 1, our system kicks in when a player begins a gaming session with a spin. This marks the starting point of their playtime. Think of the first play as the kickoff, setting the following stage. As the player keeps spinning, we save this initial time, and as they continue, we save a second time and regularly update it, kind of like rewriting a note to keep it fresh. This way, we record the player’s initial gaming session and continue to save and overwrite subsequent ones.
2: Monitoring gaming times
Now, let’s dive into Flow 2, known as the Monitoring gaming times stage. Here, our system follows a set routine, running a check every 5 minutes.
In this routine, the system looks for any new gaming times. If a player decides to give the game wheel another spin within those 5 minutes, the system updates the last time the game was played.
On the other hand, if the flow stays quiet, meaning no new spins during that 5-minute interval, the system holds onto the last saved time as the final act of that gaming session, making sure no gaming moment slips away unnoticed. This way, we’re always in step with the player’s session, capturing each move.
3: The Analysis
As we approach the grand finale, it’s time for Flow three—the Analysis. This is where the magic happens. Operating as a report, it brings together the individual notes of each player’s gaming session with a pivot data stage.
A systematic loop that meticulously goes through each player’s information block ensures an efficient, thorough examination. It’s like a well-organised process, leaving no detail overlooked; before we send this data off to Slack, we get the difference between the last and first time played that we fetched with our pivot data stage. This reveals the average time each player spends in their casino session. The compiled data is seamlessly transmitted to the designated Slack channel or any other 3rd party app of your choice from our marketplace, such as Google Sheets, allowing all necessary teams to access the most up-to-date data.
And there you have it. If you want to find out more about this Flow, see it live in action or find out more about Flows and how our innovative tech can supercharge your business – get in touch.