Steam : PLATFORM THAT CHANGED PC GAMING FOREVER

Steam is a digital marketplace and is owned by Valve Corporation. Valve Corporation was formed by ex-Microsoft employees and after launching critically acclaimed games like Half-Life and Counter-Strike, they set out their eyes on retailing software through the internet.  

History of Steam

Steam was launched as a standalone software client in September 2003 as a channel to provide automatic updates for their games.  It pioneered the digital distribution of the software. Before video games used to be physically owned and any kind of updates and patches were very cumbersome to implement.  As owning music CDs became obsolete similarly owning games in physical media became a rare thing. As internet speeds increased, this meant that downloading games over the internet became easier, and having a single library where the users can access all their purchases has now become the norm.

Later it expanded to provide software by third-party developers to become a full-fledged distribution platform. The developer of Steam is Valve Corporation.  As of today, it is one of the most profitable privately owned corporations in the world.

Steam’s business model is very similar to the model that Apple uses in its app store. It operates a commission-based business model. Steam takes a percentage cut from all the sales made on its platform (30%)

How Steam grew from its initial years?

During In its initial years, Steam provided a freemium model.  It offered its games for a free-to-play model. It helped Steam to reach a wider audience and increase its growth.

Steam has benefited a lot with its network effect. As more and more game publishers and smaller indie game developers joined the platform. Steam increased its titles library. New developers got a medium to publish their games without the hassles and cost of hosting and maintaining the games. With the help of free games and new value units being added all the time, new users joined the platform at an ever-increasing rate as well.  Now consumers could access their whole game library in a single place. Thus benefiting both these sides of the core interaction.

Currently Steam has 100 million monthly active users and over 30,000+ games listed on its platform.

In the initial years Steam solved its chicken and egg problem by providing free games and free demos of games. The strategy of seeding by providing free updates and discounts that were not available in physical media helped Steam to become a viable option. The Same strategy is also followed by the Fortnite developer and Steam rival Epic Games Store which was launched in 2018. It gives away a free game every week. This has helped Epic to get a significant foothold in the market dominated by Steam. Even though Epic games store lacks in the number of feature layers that Steam provides. Valve had realized that its user base is a very valuable asset. To increase the engagement in the platform it added community forums. Where fellow users could discuss and help each other with any topic. Steam also introduced many new features including statistics tracking system and friend list. Now Steam was shaping up like a social media platform over its core interaction as a mere platform.

In 2008 Steam introduced a filtering system. That helps users to better find their desired product. Now the catalog could be browsed according to the genre. In 2012 Steam introduced Steam Guard.  This included two-factor authentications to curb frauds and also launched its mobile app. In 2012 Steam introduced Steam Guard.  This included two-factor authentications to curb frauds and also launched its mobile app. In 2016 Valve introduced the support for VR headsets. It collaborated with HTC to introduce the Vive headset.  Later extending support for Oculus Rift.

Present and Future

Recently Steam launched a new VR title, Half-life: Alyx with the introduction of its new VR headsets. It’s one of the best virtual reality applications to date and the game received critical acclaim from reviewers and users alike. Valve is again trying a paradigm shift for pushing Virtual Reality to the mainstream and so far they have been successful in it.

Steam was one of the first digital marketplaces and they are continually working on improving their platforms. Even with new competitors, Steam has been a relevant force for over 15 years. New technological ventures and platforms can learn a lot from Valve with its drive to be innovative and ambitious in its approach.

References:

How artificial intelligence is transforming the future of digital marketing

From smart search options and personalized messaging to being used in campaigns and marketing, AI and machine learning are increasingly being used in digital marketing.

Digital marketing relies on leveraging insights from the copious amounts of data that gets created every time a customer interacts with a digital asset. Algorithms optimize various factors and data points that influence digital marketing success.
In 2020, we anticipate a significant uptick in the mainstreaming of AI and machine learning use cases in digital marketing across several areas. 

Search will get very smart

In the past year, online search has had several AI and machine learning developments. Google is leading the pack with exciting applications in information retrieval. For example, Google’s BERT technology can process a word in the context of all the other terms in a sentence, rather than one-by-one in order. BERT also enables anyone to train their own state-of-the-art question answering system.  

Customization of search results and the results page based on learning from past interactions and preferences of a user is another application of machine learning used in search.

AI-driven personalization of messaging 

Several attach companies have been focusing on using AI and machine learning to find the right audience to write better ads than humans, and to increase conversion rates and engagement with the target audience. There are also several AI-led developments in the area of creating dynamic ads and landing pages to personalize marketing messages on the fly. 

AI has an application in content creation in terms of determining the logic of personalization as also crating content specific to an individual, using techniques such as natural language generation (NLG).

Use of machine learning in campaign operations 

Platforms such as Google and Face book have been at the forefront of AI/ML applications in marketing. Starting from smart bidding and smart campaigns to auto-generated ads, Google is making it easy for advertisers.

Smart bidding options such as TROAS, TCPA, and others use advanced machine learning algorithms to train on data at a vast scale to make accurate predictions about how different bid amounts might impact conversion or conversion value and assist advertisers in optimizing without getting into too many details. 

Google factors in a wide range of contextual signals (through search data) to predict user behavior and to influence auction time bidding as per the goal set by advertisers. Facebook has also incorporated machine learning across campaign planning and execution, as also in ad placements and ad delivery.

Similarly, on the organic search side, machine learning-based product ALPS reverse engineers Google’s ranking algorithm, and is able to accurately quantify ranking drivers, provide precise recommendations for changes, and predicts the impact of SEO actions before they are implemented.

Similar technology to drive improved ad copy testing in digital marketing exists. These help in evaluating ad copies and landing pages on various parameters like relevancy, use of action promoters/inhibitors, urgency inducers, page layout, load times, etc., to gauge the impact on ad relevance, expected CTR, and landing page experience. 

Future trends 

AI will also have additional application in digital marketing with the uptick in the adoption of technologies such as VR and AR, as commercial use cases of these technologies find wider adoption in retail and other sectors.

Many retailers are also testing AI and VR/AR technologies together to make the user experience personalized to an individual.

Other areas of impact include voice search. We will increasingly see ads about things which we just said or talked about, but haven’t searched for yet. Similarly, image search is also being used by many brands for their consumers to match patterns and identify products using image search. 

The coming years will continue to unfold newer potential uses of AI in digital marketing.