1. Introduction
Being “Data-Oriented” means examining and organizing the data with the goal of better serving users and customers. By using data to drive actions, companies can specialize and/or personalize their messaging to their customers for a more customer/user-oriented approach.
So, we can say that being Data-Oriented is being User-Oriented.
Being Data-Oriented helps us to understand users’ needs and preferences for products. Especially for the B2C business, if your success depends on the customer, you must pay attention to the customer/user data. At the end of the day, regardless of all your technology, features, and design, it has become one of the most important user-oriented topics.
The lack of user-oriented design (campaign, pricing, marketing, etc.) can cost time and effort if we talk about mobile games and apps. That can greatly determine the success or failure of your products.
As I mentioned above, for the B2C business, your complete focus is on users. You are here for their happiness and satisfaction. They play your game because they love it. They use your application because it meets their needs.
So, the nature of mobile games or applications is human-oriented, human nature-oriented.
At this time, I try to show baby steps of being data-oriented; how to collect how store data, and use it properly. I will explain each of the three steps one by one and list the useful tools for it.
2. What is Data-Driven Solution?
After the brief definition, dive further into the concept and add more context and explanation if needed.
Data is Feedback from players. These feedbacks can be optimized later based on larger amounts of data if you decide to move from prototype to soft launch.
Integration of Machine learning results with original data into the Data warehouse will give you unique possibilities for multidimensional data analysis. Also, flexible self-service Business Intelligence (BI) tools such as Tableau, Power BI, QlikView, Domo, or Looker will be very useful. Using those tools, you can easily make any dashboard in a few minutes, set up alerts on preferred events, or be emailed when something unusual is happening. Programming knowledge here is not necessary, those tools are fully self-service. Insights can be easily shared with your colleagues inside the company or embedded into your internal applications.
3. Why is Being Data-Driven Important?
Give your readers a few reasons why they should care about the term or the concept you’re writing about. If this is a consumer-level concept, talk about the implications this could have on their businesses, finances, personal happiness, etc. If you’re writing for an audience of professionals, mention the impact this term or concept has on profit, efficiency, and/or customer satisfaction. To make the most of this section, ensure it includes at least one statistic, quote, or outside reference.
As a first step, having data is a good start; you need to put that data into context, meaning you have to find out the “who, what, when, why, and how.”
This method can completely change your perspective on a set of data so you can interpret them appropriately. Once you understand what is interesting or abnormal about a data set, you can communicate it well to the development team, designers, and users.
Why “Who” is important: If you’re conducting a study to determine what improvements can be made to your game/app, the opinions of your high retention users might differ from users who download the game/app freshly. So you’ll want to know who enrolled in the analysis and completed the events as you perform data analysis.
Why “What” is important: Figuring out what the data contains through statistical analysis is important. Comparing what is in the data set to relate the results with the actions is critical. Otherwise, your decision doesn’t make sense, it is about focusing on the actionable results.
Why “When” is important: Timing always affects data results. For example, if you are collecting data after some specific updates take place, you might see results for only a short period and limited users. Further, if you are utilizing in-app purchase analysis to data from your game/app, it’s important to recognize that the study's implications may not be valid due to the gap in time.
Why “Where” is important: Your users are from different countries or states, and their opinions and data may differ. Therefore, making global assumptions based on US data is not a good idea. Also, knowing where data was collected can help you make inferences!
Why “Why” is important: Often, confirmation bias can appear in data where researchers seek data to confirm their hypothesis. If you know a particular study is taking place to identify problems with customer service, you may want to watch out for strong data that shows no problems with customer service, as this is the information a researcher would want to bring to their boss.
Why “How” is important: Data collection techniques can often influence the data. If your sample size is incorrect or the methodology chosen is not meant to capture the data you need, you’ll find inconsistencies within your data and your conclusions may not be the right actions to take.
4. How to Collect Data, Store, and Use
All three of them are highly interactive topics. When you decide to collect your game data, you should also find the way of storage and of course, usage.
At this point, I am not talking about the User Acquisition or Monetization tools. I discuss your user behavior data, in-game/app actions, and events. These events are mostly about the sessions and actions in this session.
As a beginner, you can use %100 free analytics tools such as Game analytics,
Firebase is a real-time database. Store and sync data between users and devices using a cloud-hosted, NoSQL database. Cloud Firestore gives you live synchronization, offline support, and efficient data queries. It’s efficient for collecting and storing. With Big Query integration, you can query your data by writing SQL codes. Firebase’s pricing method is paying as you go.
Heap is a good analytics tool that gives knowledge about how people interact with your product, what features they use, and what user behaviors correlate with long-term value.
# Real Examples of Current Customers
# Tips and Reminders for Game Studios
Last But Not Least
In the end, data is meaningless without turning into information. And information is useless without taking action or creating wisdom. For example, through data analysis, you may realize that 95% of users switch to other applications because of the renewal price change or churn from your game based on a new update which increases rewarded video frequency. This is turning data into information. Then you can use that information to make actionable plans for reasonable renewal prices or rewarded video frequency to keep more users.
5. Don't Miss the Right Segment
Give them a fun game or application they deserve. Make your users happy, if they become happier, they stay longer they spend more. So what else do you want? Let’s start!
