Transforming the Gaming Industry with AI Analytics

In 2020, the gaming market generated over 177 billion dollars, marking an astounding 23% growth from 2019. While it may be incredible how much revenue the industry develops, what’s more impressive is the massive amount of data generated by today’s games.

There are more than 2 billion gamers globally, generating over 50 terabytes of data each day. The largest game companies in the world can host 2.5 billion unique gaming sessions in a single month and host 50 billion minutes of gameplay in the same period.

The gaming industry and big data are intrinsically linked. Companies that develop capabilities in using that data to understand their customers will have a sizable advantage in the future. But doing this comes with its own unique challenges.

Games have many permutations, with different game types, devices, user segments, and monetization models. Traditional analytics approaches, which rely on manual processes and interventions by operators viewing dashboards, are insufficient in the face of the sheer volume of complex data generated by games.

Unchecked issues lead to costly incidents or missed opportunities that can significantly impact the user experience or the company’s bottom line. That’s why many leading gaming companies are turning to AI and Machine Learning to address these challenges.

Gaming Analytics AI

Gaming companies have all the data they need to understand who their users are, how they engage with the product, and whether they are likely to churn. The challenge is gaining valuable business insights into the data and taking action before opportunities pass and users leave the game.

AI/ML helps bridge this gap by providing real-time, actionable insights on near limitless data streams so companies can design around these analytics and act more quickly to resolve issues. There are two fundamental categories that companies should hone in on to make the best use of their gaming data:

The revenue generating opportunities in the gaming industry is one reason it’s a highly competitive market. Keeping gamers engaged requires emphasizing the user experience and continuous delivery of high-quality content personalized to a company’s most valued customers.

Customer Engagement and User Experience

Graphics and creative storylines are still vital, and performance issues, in particular, can be a killer for user enjoyment and drive churn. But with a market this competitive, it might not be enough to focus strictly on these issues.

Games can get an edge on the competition by investing in gaming AI analytics to understand user behaviors, likes, dislikes, seasonality impacts and even hone in on what makes them churn or come back to the game after a break.

AI-powered business monitoring solutions deliver value to the customer experience and create actionable insights to drive future business decisions and game designs to acquire new customers and prevent churn.

AI-Enhanced Monetization and Targeted Advertising

All games need a way to monetize. It’s especially true in today’s market, where users expect games to always be on and regularly deliver new content and features. A complex combination of factors influences how monetization practices and models enhance or detract from a user’s experience with a game.

When monetization frustrates users, it’s typically because of aggressive, irrelevant advertising campaigns or models that aren’t well suited to the game itself or its core players. Observe the most successful products in the market, and one thing you will consistently see is highly targeted interactions.

Developers can use metrics gleaned from AI analytics combined with performance marketing to appeal to their existing users and acquire new customers. With AI/ML, games can use personalized ads that cater to users’ or user segments’ behavior in real-time, optimizing the gaming experience and improving monetization outcomes.

Using AI based solutions, gaming studios can also quickly identify growth opportunities and trends with real-time insight into high performing monetization models and promotions.

Mobile Gaming Company Reduces Revenue Losses from Technical Incident

One mobile gaming company suffered a massive loss when a bug in a software update disrupted a marketing promotion in progress. The promotion involved automatically pushing special offers and opportunities for in-app purchases across various gaming and marketing channels. When a bug in an update disrupted the promotions process, the analytics team couldn’t take immediate action because they were unaware of the issue.

Their monitoring process was ad hoc, relying on the manual review of multiple dashboards, and unfortunately, by the time they discovered the problem, it was too late. The result was a massive loss for the company – a loss of users, a loss of installations, and in the end, more than 15% revenue loss from in-app purchases.

The company needed a more efficient and timely way to track its cross-promotional metrics, installations, and revenue. A machine learning-based approach, like Anodot’s AI-powered gaming analytics, provides notifications in real-time to quickly find and react to any breakdowns in the system and would have prevented the worst of the impacts.

Anodot’s AI-Powered Analytics for Gaming

The difference between success and failure is how companies respond to the ocean of data generated by their games and their users. Anodot’s AI-powered Gaming Analytics solutions can learn expected behavior in the complex gaming universe across all permutations of gaming, including devices, levels, user segments, pricing, and ads.

Anodot’s Gaming AI platform is specifically designed to monitor millions of gaming metrics and help ensure a seamless gaming experience. Anodot monitors every critical metric and establishes a baseline of standard behavior patterns to quickly alert teams to anomalies that might represent issues or opportunities.

Analytics teams see how new features impact user behavior, with clear, contextual alerts for spikes, drops, purchases, and app store reviews without the need to comb over dashboards trying to find helpful information.

The online gaming space represents one of the more recent areas where rapid data collection and analysis can provide a competitive differentiation. Studios using AI powered analytics will keep themselves and their players ahead of the game.

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CodeRyte

CodeRyte has over 115 clients including 30 academic medical centers and large integrated delivery networks, 50 single-specialty practices and 30 billing companies. Our natural language processing engine processes more than 2.7 million reports every month and has coded more than 70 million records since CodeRyte began.

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Airbyte | January 30, 2024

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Read More

Data Architecture

SingleStore Announces Real-time Data Platform to Further Accelerate AI, Analytics and Application Development

SingleStore | January 25, 2024

SingleStore, the database that allows you to transact, analyze and contextualize data, today announced powerful new capabilities — making it the industry’s only real-time data platform. With its latest release, dubbed SingleStore Pro Max, the company announced ground-breaking features like indexed vector search, an on-demand compute service for GPUs/ CPUs and a new free shared tier, among several other innovative new products. Together, these capabilities shrink development cycles while providing the performance and scale that customers need for building applications. In an explosive generative AI landscape, companies are looking for a modern data platform that’s ready for enterprise AI use cases — one with best-available tooling to accelerate development, simultaneously allowing them to marry structured or semi-structured data residing in enterprise systems with unstructured data lying in data lakes. “We believe that a data platform should both create new revenue streams while also decreasing technological costs and complexity for customers. And this can only happen with simplicity at the core,” said Raj Verma, CEO, SingleStore. “This isn’t just a product update, it’s a quantum leap… SingleStore is offering truly transformative capabilities in a single platform for customers to build all kinds of real-time applications, AI or otherwise.” “At Adobe, we aim to change the world through digital experiences,” said Matt Newman, Principal Data Architect, Adobe. “SingleStore’s latest release is exciting as it pushes what is possible when it comes to database technology, real-time analytics and building modern applications that support AI workloads. We’re looking forward to these new features as more and more of our customers are seeking ways to take full advantage of generative Al capabilities.” Key new features launched include: Indexed vector search. SingleStore has announced support for vector search using Approximate Nearest Neighbor (ANN) vector indexing algorithms, leading to 800-1,000x faster vector search performance than precise methods (KNN). With both full-text and indexed vector search capabilities, SingleStore offers developers true hybrid search that takes advantage of the full power of SQL for queries, joins, filters and aggregations. These capabilities firmly place SingleStore above vector-only databases that require niche query languages and are not designed to meet enterprise security and resiliency needs. Free shared tier. SingleStore has announced a new cloud-based Free Shared Tier that’s designed for startups and developers to quickly bring their ideas to life — without the need to commit to a paid plan. On-demand compute service for GPUs and CPUs. SingleStore announces a compute service that works alongside SingleStore’s native Notebooks to let developers spin up GPUs and CPUs to run database-adjacent workloads including data preparation, ETL, third-party native application frameworks, etc. This capability brings compute to algorithms, rather than the other way around, enabling developers to build highly performant AI applications safely and securely using SingleStore — without unnecessary data movement. New CDC capabilities for data ingest and egress. To ease the burden and costs of moving data in and out of SingleStore, SingleStore is adding native capabilities for real-time Change Data Capture (CDC) in for MongoDB®, MySQL and ingestion from Apache Iceberg without requiring other third party CDC tools. SingleStore will also support CDC out capabilities that ease migrations and enable the use of SingleStore as a source for other applications and databases like data warehouses and lakehouses. SingleStore Kai™. Now generally available, and ready for both analytical and transactional processing for apps originally built on MongoDB. Announced in public preview in early 2023, SingleStore Kai is an API to deliver over 100x faster analytics on MongoDB® with no query changes or data transformations required. Today, SingleStore Kai supports BSON data format natively, has improved transactional performance, increased performance for arrays and offers industry-leading compatibility with MongoDB query language. Projections: To further advance as the world’s fastest HTAP database, SingleStore has added Projections. Projections allow developers to greatly speed up range filters and group by operations by introducing secondary sort and shard keys. Query performance improvements range from 2-3x or more, depending on the size of the table. With this latest release, SingleStore becomes the industry’s first and only real-time data platform designed for all applications, analytics and AI. SingleStore supports high-throughput ingest performance, ACID transactions and low-latency analytics; and structured, semi-structured (JSON, BSON, text) and unstructured data (vector embeddings of audio, video, images, PDFs, etc.). Finally, SingleStore’s data platform is designed not just with developers in mind, but also ML engineers, data engineers and data scientists. “Our new features and capabilities advance SingleStore’s mission of offering a real-time data platform for the next wave of gen AI and data applications,” said Nadeem Asghar, SVP, Product Management + Strategy at SingleStore. “New features, including vector search, Projections, Apache Iceberg, Scheduled Notebooks, autoscaling, GPU compute services, SingleStore Kai™, and the Free Shared Tier allow startups — as well as global enterprises — to quickly build and scale enterprise-grade real-time AI applications. We make data integration with third-party databases easy with both CDC in and CDC out support.” "Although generative AI, LLM, and vector search capabilities are early stage, they promise to deliver a richer data experience with translytical architecture," states the 2023 report, “Translytical Architecture 2.0 Evolves To Support Distributed, Multimodel, And AI Capabilities,” authored by Noel Yuhanna, Vice President and Principal Analyst at Forrester Research. "Generative AI and LLM can help democratize data through natural language query (NLQ), offering a ChatGPT-like interface. Also, vector storage and index can be leveraged to perform similarity searches to support data intelligence." SingleStore has been on a fast track leading innovation around generative AI. The company’s product evolution has been accompanied by high-momentum growth in customers and surpassing $100M in ARR late last year. SingleStore also recently ranked #2 in the emerging category of vector databases, and was recognized by TrustRadius as a top vector database in 2023. Finally, SingleStore was a winner of InfoWorld’s Technology of the year in the database category. To learn more about SingleStore visit here. About SingleStore SingleStore empowers the world’s leading organizations to build and scale modern applications using the only database that allows you to transact, analyze and contextualize data in real time. With streaming data ingestion, support for both transactions and analytics, horizontal scalability and hybrid vector search capabilities, SingleStore helps deliver 10-100x better performance at 1/3 the costs compared to legacy architectures. Hundreds of customers worldwide — including Fortune 500 companies and global data leaders — use SingleStore to power real-time applications and analytics. Learn more at singlestore.com. Follow us @SingleStoreDB on Twitter or visit www.singlestore.com.

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