I Analyzed 71K+ Games to Find the Best Content Strategy for Steam
Uncovering keyword and tag patterns in Steam games page using NLP
As game developers and marketers, optimizing your Steam store page is crucial for discovery. But what actually works? Using Natural Language Processing (NLP) to analyze over 71,000 game descriptions, I uncovered some fascinating patterns in how successful games present themselves.
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Dataset Description
The SteamGames (71k games) dataset contains comprehensive information on a large collection of games on the Steam platform from 1997–2025, including unreleased games. The dataset consists of 39 columns and 71,171 rows, providing information about game genres, price, number of player and more. This provides a valuable opportunity to delve into the dynamics of the Steam marketplace and observe store page content trends through the years and across different genres.
Data Source: https://www.kaggle.com/datasets/mexwell/steamgames
Methodology
I conducted two separate analyses:
Keyword analysis of Action games (the most popular genre)
Analysis of the top 1000 games by peak concurrent players
To do this, I utilized Python’s spaCy and NLTK libraries to:
Cleaned and preprocessed game descriptions
Removed stop words and performed named entity recognition
Analyzed word frequencies, bigrams, and trigrams
Generated single, bigram, trigram word clouds to visualize key terms
Key Findings for Action Games
One term stood out significantly in successful Action game descriptions:
“Procedurally Generated”
The prominence of this term reveals several important insights about the Action genre player base:
They highly value games that offer unpredictable and unique experiences. The combination of randomized content with skill-based gameplay creates a compelling value proposition.
They specifically seek out titles that challenge their adaptability. This aligns with the genre’s emphasis on mastery and improvement.
Action games featuring procedural generation tend to maintain higher concurrent player counts.
The data suggests that highlighting these features in the store description could resonate with the Action game audience.
Analysis of Top Performers
When I analyzed the top 1000 games by peak concurrent players, two interesting patterns emerged:
“Steam Trading Cards”
Games with trading card support appeared consistently in the top 1000 games by peak concurrent players. The frequent mention of trading cards suggests they’re more than just bells and whistles. This feature serves multiple engagement purposes:
Players can sell the cards on the Steam marketplace, which creates a secondary economy within the Steam ecosystem
Provides additional motivation for players to invest time in games
Offers tangible rewards for gameplay progression
Can be converted to Steam wallet funds, creating real value for players
“Single Player Campaign”
Despite the industry’s heavy investment in live-service models, successful games consistently highlight their single-player content. The 2023 Game Development Report, made in partnership with Rendered VC, surveyed 537 studios from across the globe, and revealed that 955 of game developers are making or maintaining a live-service game. However, the word frequency analysis shows “single player campaign” as a top-performing term. This suggests an important market gap:
Players still strongly value dedicated single-player experiences
The most successful games often combine both approaches
Pure live-service games might be missing out on a significant player segment
Data-Driven SEO Strategy for Steam
Based on the NLP analysis and part 1 of the Steam Data Analysis series: What 15 Years of Steam Data Tells Us About the Gaming Industry, here’s how publishers can optimize their store presence:
Genre-Specific Keyword Optimization
Genre-specific terminology matters more than generic gaming terms. By using the NLP model, developers and publishers can target specific genres to view the popular keywords used. For instance, Action games should emphasize procedural generation and replay value.
Lead with your strongest genre-specific keywords and use tags to highlight special or popular game features
Balance technical features like “VR mode”, with gameplay experience descriptions like “addictive”
Consider including platform-specific features as keywords or tags, such as: “steam trading cards”
Beyond SEO: Understanding Market Position
In addition to SEO strategies, the keyword analysis also revealed insights about a game’s market position and the trend of popular or successful games:
The success of hybrid games (combining live-service and single-player) suggests a sweet spot in the market
Platform-specific features like trading cards can significantly impact player engagement
Final Thoughts
My findings provide a data-driven framework for developers and publishers to optimize their Steam store presence, potentially increasing visibility and engagement in an increasingly crowded marketplace.
As someone who's watched the gaming industry evolve from both a professional’s and gamer’s perspective, this data feels like a peek behind the curtain of what makes games truly resonate with players. It is actually reassuring to see that the appeal of unpredictable procedural worlds or the timeless draw of a compelling single-player journey stays relevant throughout these 15 years of Steam data.
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