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The Problem with Video Game Recommendations and How the E-Commerce Industry can Improve Them

Have you ever browsed through what seemed like Steam’s entire catalog trying to find a game you might like? Have you spent more time on Netflix trying to decide what you want to watch as opposed to watching something? These are problems most of us have faced or are facing, and are a result of several factors, especially lack of personalization.

Personalizing your products for your customers is critical in today’s world. One can see an average increase of 20% in sales when using personalized experiences. Companies want their customers to be aware of how they are catering specifically to user needs. For example, if you’ve played a shooter game, you might be recommended to play another just because other people who liked the first game you played also enjoyed this. Your reasons for playing the former might differ from the others and thus, the latter might not be a good fit for you. The lack of good video game recommendations reduces trust in these companies to provide a good service experience. 

From the companies’ end, good customer experiences help in generating income, as well as differentiating themselves from the competition. An e-commerce company needs to focus on three things to thrive:

  • Increase the acquisition rate of new users
  • Increasing conversion rates of your users
  • Ensure that users don’t leave (reduce churn)

The Importance of Recommendations

Personalization has become a major factor in the success of e-retail companies. Whether it is addressing customers by name in communications or providing them with special offers based on their interests, online stores are increasingly focused on improving this.

Recommendations are the deepest level of personalization and are a necessary feature to be added to their portal. They are integral for both customers and the companies which cater to them for a multitude of reasons we will look at. For a customer, they provide the following benefits:

  • A significantly better user experience
  • A sense of being understood and seen
  • More personalized benefits and deals

For companies, the benefits are just as tangible if not more so:

  • Improved customer engagement
  • Significantly increased customer retention
  • Larger levels of web traffic
  • Better sales and revenue

Below are some examples of companies that thrive based on their recommendation systems.

 

Case Studies

Let’s take a look at one of the world’s most successful companies, Netflix. While Netflix started as a movie rental service, today, they stream movies and have over 200 million paying customers across the globe. A key part of this evolution is their personalized recommendation system. 

Understanding Video Game Recommendations: Netflix's Recommendations
Netflix's recommendation system suggests a variety of content you might enjoy.

Netflix’s recommendation systems have been developed over years by hundreds of engineers after analyzing millions of users. When a new subscriber joins, Netflix asks them to pick shows/movies they like, and as they watch more over time, the suggestions are powered by these as well as some additional factors like:

  • Viewer history
  • Viewer ratings for prior shows
  • Information like title, genre, category, and more
  • Other viewers with similar preferences and taste
  • Time an episode/movie lasts vs time duration of a viewer watching a show
  • The time of the day you’re watching
  • The device on which you’re logged in

Closer to home, we have Steam, which is a digital game distribution system, with more than 120 million monthly active users and a catalog of over 50,000 games. It is also home to a powerful video game recommendation system that helps gamers find games they will love.

They recommend games based on your played games, purchase history, store browsing history, and games that other players with tastes similar to yours love.

Understanding Video Game Recommendations: Netflix's Recommendations:Steam's Recommendations
Steam's recommendations are based on a variety of factors like games you've previously played, browsing history, and the like.

However, neither of these do a perfect job. Let’s look at why.

The Problems with Recommendations Today

We’ve looked at the importance of personalization and the role recommendations play in this. However, despite online stores realizing how vital a good quality recommendation is, they still haven’t perfected the art of suggesting the right products. Here are some of the common problems faced by customers while trying to find what they need.

Wrong recommendations: Thanks to imperfect algorithms or lack of high quality data, sites can often suggest irrelevant or incorrect recommendations. These reduce customer trust, engagement, and overall, is a waste of a good opportunity.

Impersonal communication: We all buy products and services for a variety of reasons. However, distributors still use generic and non-engaging messages most of the time while communicating with users. Messages such as “You might like Item X” without mentioning why you might like it can turn your customers off.

Choice overload: Too much choice can be a detriment to your customers. A recent consumer report discovered that more than half (54%) of consumers have stopped purchasing products from a brand or e-retailer website because choosing was too difficult, with 42% admitting to abandoning a planned purchase altogether because there was too much choice. These problems are a result of sub-optimal recommendation systems on websites.

Behavior Vs Motivation

The reason for inadequate online recommendations is that these mechanisms are primarily driven by behavior as opposed to motivation.

If several people play the same game, they might do so for different reasons. Let us take one of the most popular games which came out in June 2020, Valorant, as an example. Valorant is a 5v5 tactical first person shooter (FPS) where the characters you play as (agents) all have unique abilities. It has a monthly player base of at least 12 million throughout 2021, making it one of the most popular current FPS titles. Let’s analyze the different possible motivations that drive people to play Valorant:

Satisfying the urge to compete, dominate, and win: A large number of people play video games to compete against other skilled players and dominate the leaderboards for a sense of achievement. Valorant has this in spades with its highly competitive online multiplayer nature and detailed rank progression.

Strategizing for the win: Gamers enjoy certain games because they involve a great deal of planning and strategizing to be victorious. With its deeply tactical nature, Valorant satisfies this motivation.

To play with friends or meet people: A significant portion of players like games for their socialisation aspect. Whether it is being able to play with your buddies, meeting new like-minded strangers you can have fun with, or working as a team, Valorant fills these socialization shoes very well.

Current state of product recommendations
Nothing hits the mark like playing games with your squad.

For an adrenaline rush: Gamers often get motivated by the rush of adrenaline or dopamine they get as they play games that excite their senses, and this is what keeps them coming back to the game as well. Valorant certainly fits this criterion.

Aggression: Some people like playing video games for the violence and ferocity that come as a part of the game, especially shooters and hack & slash games. Valorant satisfies this urge.

The behaviour here in common is people playing Valorant. However, as you can see, their motivations may be completely different. For instance, in terms of story and lore, Valorant is found lacking compared to Overwatch, another popular competitive multiplayer title. Thus, people who play Overwatch because they like its lore and narrative aspects might not be as interested in Valorant.

How can you Improve Video Game Recommendations?

Gamer motivations are a culmination of their emotional and psychological makeup while also covering traits like values, personality, and life situations. To revolutionize video game recommendations, you will need to start by understanding the games you’re recommending, and why people play them. Next, look at your user base and try to understand each individual at a fundamental level. Finally, once you have an understanding of the games as well as your user, see why people play what they do, and use that to provide a video game recommendation. As a result of this, you will:

  • Provide fewer recommendations: This will keep you from overloading your customers with choice.
  • Give better recommendations: When you understand your users’ motivations, you can suggest games that are aligned with their motivations every time.
  • Personalized recommendations: Each of your recommendations will effectively communicate why a particular game is right for your user, as well as address their needs.

Apart from the above, you can improve e-retail personalization in general by:

  • Refine your search pages. You can use metadata to improve product descriptions and make it easier for your algorithms to match products to customer preferences and needs.
  • You can use referral bonuses to improve signups and good email marketing that conveys personalized deals and offers to your customers to increase retention.
  • Ensure your home page, product pages, and promotional offers are tailored to your customers’ needs based on data you’ve collected and their preferences.
  • Intelligent machine learning algorithms combined with high quality data are your best friends. The next section will go into detail about recommendation models you can use in conjunction with them.

Recommendation Models

Below are the models most commonly used by e-commerce companies:

Popularity-based: These are products that are best-selling currently. For example, Among Us blew up in 2020 and was a game that popped up on Steam’s bestseller list. These also include games that have been popular for a long time, such as Counter-Strike: Global Offensive. It is meant primarily for new users on the website.

Quality based: The games which have a high number of positive reviews and ratings show up here based on this model and are recommended to users. However, this might not be the best method as peoples’ tastes can drastically differ, and a game might have ‘boosted’ reviews. Also, newer games might not have enough reviews to show up, despite possibly being something your user might love.

Content-based: This model recommends products based on their similarities with other products. It leverages the description and content of items and an understanding of the user’s consumption history. For example, Valorant is recommended to players who love Overwatch and Counter-Strike: Global Offensive, since it has similar characteristics to both these games.

Collaborative Filtering: In the newer, focused sense, collaborative filtering is a method of making automatic predictions (filtering) about the interests of a user by collecting preferences or taste information from many users (collaborating).The system generates recommendations using only information about rating profiles for different users or items.

Of course, hybrid recommendation systems which use a mix of these models are your best bet to provide personalized recommendations to your customers. Going back to Netflix, they make recommendations by comparing the watching and searching habits of similar users (i.e., collaborative filtering) as well as by offering recommendations that share characteristics with content that a user has rated highly (content-based filtering). 

Metadata is crucial to fuel understanding of your products. This will help you organize your product database, as well as categorize it better. High quality and comprehensive metadata gives personalization algorithms more data to train on. If you want to know more about the importance of video game metadata and managing it, this blog might help you.

Conclusion

Personalizing recommendations is the best way for e-commerce companies to improve revenue as well as stand out among their competitors. When it comes to video games, understanding the motivations as to why people play the games they play is integral to making good suggestions. Gameopedia’s quality-checked and extensive metadata as well as our intelligent sentiment analysis tool can help with optimizing your content and website for better personalization and improving video game recommendations. Contact us to learn more about what we can do for you and your business.

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Everything You Need To Know About Metadata For Video Games

What is Video Game Metadata?

Metadata describes an item, i.e. it is any information that summarizes basic details about the item, which can make finding and working with particular data easier.  For example, the ingredients listed behind a box of cookies is metadata describing the contents of the cookie. 

Similarly, video game metadata refers to descriptors about the game that not only give you an overview of the game like the developer’s name, publisher’s name, release date, game description, and so on, but it also helps the people using this video game data easily understand what the game has to offer without having to purchase or play the game themselves.

What Constitutes Video Game Metadata

Video game metadata could be any information that gives the reader insights about the game. From the release date to the game franchise it belongs to, any information that tells us something about the game can be considered game metadata.

Let’s take the example of Borderlands 3 – an action role-playing first-person shooter. The metadata for this game would look something like this.

Metadata for video games

The information above may appear to be basic but its applications are invaluable to certain sections of the industry. 

This leads to our next question:

Who Needs Metadata For Video Games?

Everybody that is a part of the gaming ecosystem, from the retailer to the consumer, uses video game metadata at some level. The format in which the data is presented and how it is used can vary depending on the requirement. Let us explore this in detail. 

e-Retailers & App Stores

A retailer’s goal is to engage their customer and attend to their needs or solve a problem they have. 

Your first thought might have been retailers want to sell more but it might be more prudent in the long run to gain the trust and loyalty of their existing user base. And gamers are a loyal bunch.

The best way to gain a gamer’s trust? Understand what you are selling inside out. 

With detailed and descriptive metadata and good metadata management policies, the store can display the right games to the customer most likely to buy them. What are these “right games”? They are games which have the features that a customer wants, or a game by the same developer whose earlier work the customer enjoyed for example. This is information that the customer needs to make a decision. By offering the right games, the store improves not just the customer’s user experience but also instills a certain sense of loyalty in them. You gain their trust by putting the customer first with recommendations and search results that solve their problem.

Let’s consider the example of Cyberpunk 2077. Even though it was the most anticipated game of 2020, not everybody was looking forward to the game. This segment of your user base would prefer not to be inundated with content and promotional material regarding the game. For these users, “Cyberpunk 2077” is the definition of not being the “right game”.

Metadata for video games - Cyberpunk-2077

Combining comprehensive game metadata with user behavior, your game store can display content that actually appeals to the audience, making their experience more personalized and improving conversions. But above all, you put the customer first, building their trust in you and retaining their loyalty.

For more information, have a look at our video game metadata offerings for e-Retailers.

Advertisers

People use the same item for different purposes. These purposes are defined by the users’ requirement. For example, while a gamer could be looking for a mouse suitable for gaming, an office employee will look for a mouse more suited for day-to-day use. Depending on their requirement, the features they are looking for can also change.

This means that to advertise the right product to the right consumer, it is vital to understand the “why” and not just the “what”. That way, you don’t just show the user the item that they were looking for, but you also solve their problem.

Let us look at this through the example of a game. The “Mario Kart” franchise is an incredibly popular series of games, having sold over 150 million copies worldwide. These games are enjoyed across all age-groups, by gamers who have different expectations from their gaming habit. 

Mario Kart 8 Deluxe Metadata

Some gamers play because they like to win. They like competitive games.  There are those who play games purely as a social activity that they indulge in with family or friends. There’s another group of gamers who have a hard day at work, and would like to unwind in the evening, without having to worry about complex plotlines or learn advanced gameplay mechanics. 

The beauty of “Mario Kart” is that it has something for all the types of gamers described above, but an advertiser can’t expect to use one campaign to reach out to all three groups. Trying to sell a game in the “Mario Kart” series requires using a different pitch to sell to each of these three kinds of gamers. To do that, they need to understand how to appeal to these target demographics. What keywords do they look out for when making a game purchase? What features do they expect from a game? Do they expect their games to look simple, or photorealistic with complex mechanics?

Hence, the advertisers should not only align with “what” the consumer is looking for but also the “why”. With comprehensive game metadata, ad networks can improve their targeting, making it more personalized while providing context to why the said product is best suited for your needs, and not just the best on the market.

Advertisers can learn more about our data offerings that can benefit their campaigns.

ACR Platforms

With the rise of OTT platforms, we have seen a significant need for Automatic Content Recognition (ACR) – identification technology that utilizes a large database to recognize content (video, audio, or digital images) played on a media device. Using this technology, ACR platforms can not only extract user-specific viewing data like time of viewing, show title, and genre, but also prevent third-parties from pirating online content.

For example, major appliance providers like LG and Samsung do not have a way to track what content is being played on their Smart TVs via gaming consoles, making it difficult for these brands to understand user behavior and interests. Instead, they have to depend on the device manufacturer or third-party providers for this information.

In a world where gaming has become everyone’s new favorite pastime, this information is gold, and paying for this data is not feasible in the long term. This led to manufacturers using ACR to bridge this gap. 

ACR platforms utilize thousands of “fingerprinted” content to use as a reference in identifying the viewer’s on-screen content. With comprehensive game metadata, ACR platforms can tag game videos and screenshots with descriptive tags that describe key characteristics or elements that can be used to identify a specific piece of content.  

Read more on our data offerings for ACR Platforms.

Why Do You Need Metadata For Video Games?

Improve Search Results and Product Discoverability

In a study carried out by Kotaku, 40% of purchased games are never even played. From this information, it is clear that there are people to play games but they can never find the right one. So, to get the right game to the right individual, it is important to catalog these games properly using specialized video game data and metadata management practices.

With an exhaustive game metadata repository, you get access to descriptive tags and information that provide an in-depth understanding of the gaming product or service you are offering. This allows you to improve product placement and discovery.

For example, if a customer is interested in purchasing a popular RPG game called “The Witcher 3: Wild Hunt”, they would understand from the description that the game is an open world Action RPG with a medieval setting. But if they wanted to understand to what extent the open world and RPG elements are present in the game, they could be presented with additional information by using descriptive tags. For this game, some tags would be, “Open World (Defining)”, “Action (Key Feature)”, and “Role Playing (Defining)”. 

From these tags, the customer understands that the game heavily features open world and Role Playing features, while Action elements are strongly present without being the main focus. This additional layer of information can strengthen the customer’s resolve to purchase the game.

Understand and Use Your Data Effectively

The most common problem faced by people working with video game data is that it is not ‘clean’, i.e. it is not organized and easy to understand. This makes working with data difficult and time-consuming. 

With comprehensive metadata, people can make sense of the data presented to them quicker. This reduces turn-around times, and improves the quality of insights derived from the data. Conventionally sourced data would require a great deal of fact-checking and cleaning before you’re sure it’s employable. However, using an organized and quality-checked dataset and good metadata management practices, such as the ones provided by Gameopedia, means you can utilize it right away. 

Improve Trust in Your Data

Organized game data and information, collected in a standardized manner, means that the data is immediately ready for use and its in-depth nature provides transparency that would have been difficult to achieve otherwise.  Gameopedia has a proven track record in delivering standardized metadata consistently, with all the definitions and use cases being agreed upon by a team of gaming experts.

Properly managed video game metadata can help organizations better trust the collected data because they know that the information is curated in an organized manner.

The video game data that we collect can be used for a variety of purposes. How much data you collect and how you use it is at your discretion.  Powerful, descriptive metadata and proper metadata management makes the data easier to understand and use irrespective of the volume.

At Gameopedia, we look to provide informative game metadata to every member of the gaming ecosystem in order to empower their efforts and capture the gaming market. Reach out to us to leverage the power of our data that encompasses over 180,000 games spanning 200 platforms. 

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