The Future of Monetization with Web 3.0

As of April 2021, the global gaming value exceeded $300 Billion. While a substantial chunk of it is due to the rapid adoption in the recent pandemic and the availability of a plethora of mobile games, gaming is no more a child’s play. A sustainable, long-term monetization strategy can’t just be an afterthought but an essential building block for gaming, media, and entertainment businesses.

It’s 2022, and we are entering a new dimension with bleeding-edge innovations across industry verticals. The line between gaming, the media and entertainment is getting thinner by the day. Seamlessly integrated experiences may have sounded fancy a couple of years back, but now it’s a bare essential. 

We’re about to enter the next generation of seamless connected-tech experiences, thanks to Metaverse. It’s time for content-based enterprises, from small indie studios to large AAA studios and OTT platforms, to reconsider their monetization strategy.

The Current State of Monetization 

Monetization in games, media, and entertainment has evolved over the decades.

Games were sold as finished products in cartridges and then on physical discs. They used to be one-and-done products for which the customer got the most for their spend. 

With the shift towards digital game stores like Steam, Epic, GOG, and others, the monetization landscape saw a transformational shift.

For once, studios and publishers saved a lot of money since they didn’t have to print, package, and transport the physical game copies. They could also rely on fixing game bugs and patching them via Over-The-Air updates post-release, and then there’s Downloadable Content.

All these had a budget constraint and limited the possibilities for smaller players.

However, the paradigm shift in monetization came with mobile games. They brought in a shock and awe effect by leveraging the freemium models and using in-app purchases, in-game ads, and paid games to bypass the ads and paywalls compared to free games.

In media and entertainment, the advent of streaming platforms saw a similar dynamic, and the typical commercials saw a shift. Traditional media houses were left behind with a significant gap as OTTs ruled the roost.

But now, we are about to witness another shift that will affect the current monetization strategies of the gaming, media, and entertainment industries.

The New Era of The Internet is Changing Everything

We have too many digital game stores and streaming platforms, and the users are starting to feel the pinch. Subscription fatigue is starting to set in, making monetization challenging for businesses.

On top of that, we’re on the verge of a new version of the internet, one where entertainment will be an intertwined concept tag-teamed with gaming. Metaverse will be at the helm, and digital transactions and monetization methods will witness a rapid transformation. Saurabh Tandon, President & Board Member at Affine, recently shared his thoughts on this.

We now have blockchains in the mix, which can change the whole economy of monetization for both creators and businesses. Like it or not, the metaverse might very well become a crucial player in the world economy.

Physical and Virtual Lives will Bridge for a Unified Experience

XR (Extended Reality), an amalgamation of Virtual Reality, Augmented Reality, and mixed reality technologies, will pave the way for our future entertainment content requirements.

So, what does this mean for businesses? Big Tech giants rule with an iron fist, and content moderation is a grey area in the current climate.

“With the next generation of the internet, we are looking at decentralization and a leap of technology,” said Christopher Lafayette, Founder and CEO at Gatherverse, when he recently spoke at a virtual summit.

Advertising has already changed since its inception, and today it’s focused on content creators and consumers.

With content creators and influencers, advertising has taken center stage and helps ads find takers among the form of consumers with their large subscriber base.

Non-Fungible Tokens (NFTs) are now trending and are set to be a digital form of payment, letting users buy and trade digital assets. With users creating communities for such “digital marketplace,” the playing field for monetization is in dire need of an update and can’t rely on traditional practices.

What is the Future of Monetization?

The future of monetization with web 3.0 may be questionable, but the majority of web3.0’s focus is on decentralization. User is at the core; and will be the driving force, be it content, ads, or monetization. Adaption is the need of the hour for businesses.

Sure, the traditional payment methods will remain. But businesses have to acknowledge the fact that blockchain will be thrown into the mix and change the dynamic of the digital economy. Rafael Brown, CEO & Co-Founder at Symbol Zero, who was a speaker in a recent tech symposium, said, “PC and Mobile gaming have established a monetization economy. As technology changes with time, we need to revisit our assumptions. The need of the hour for blockchain technology is to create sustainable monetization.”

The tech summit brought together more than 20 world leaders from Gaming, Media & Entertainment to participate and unravel the direction we as humans powered by tech are headed with web 3.0. With discussions on monetization, metaverse, subscription fatigue, OTT platforms, and many more interesting topics, the virtual event was a hit around the globe. 

Watch the enticing session recording here

Affine combines the hyper-convergence of AI, data engineering & cloud with deep industry knowledge in manufacturing, gaming, CPG, and technology. Affine demonstrates thought leadership in all relevant knowledge vectors by investing in research through its highly acknowledged centers of excellence and strong academic relationships with reputable institutions.  

Reach out to us to put a robust and sustainable monetization strategy in place for your business!

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How AI Analytics Will Lead the Way for the Game Industry

Analytics in gaming is a compelling prospect. 

Gaming went from being a niche hobbyist culture to becoming a reckoning mainstream phenomenon. Today we have close to 3 billion gamers around the globe, which answers the simple question of the need for analytics in gaming for businesses.

The plethora of data! That’s a rich repository of insights to be leveraged.

The gaming industry was worth $178 billion in 2021, projected to exceed $268 billion by 2050. Gaming has shifted its weight on cloud technology, for its backend services over the years. Mobile gaming turned out to be a successful phenomenon, onboarding even casual players and turning it into a lucrative segment.

With the pandemic, gaming skyrocketed in demand. Mobile games saw such a spike that even the streaming giant Netflix has decided to dip its toes in mobile gaming. Who can blame them?

The mobile gaming market will cross $272 billion by 2030, according to Global Data!

Smiling young man playing game on smartphone isolated over yellow background, looks happy and concentrated, looking smiling at his device’s screen, spending spare time indoor, guy holding mobile phone

With such high stakes, there are a couple of behind the scene factors attributing to the smooth functioning and success of the video game industry.

Let us dig deeper and understand how cloud technology will accelerate AI (Artificial Intelligence) analytics adoption in the video game industry.

What is Gaming Analytics?

On average, an online gaming company generates close to 50 Terabytes of data in just 24 hours. Managing such a significant player base is no easy task, and we’ve already seen how the cloud functions as the bloodline for backend gaming infrastructure and managed services.

Such a mammoth repository of gameplay data may contain vital elements that game studios can leverage using gaming analytics. 

Gaming analytics may mean many things to many organizations. The use cases are far too many with every service, but game studios need to understand their respective problem statements. 

In broader terms, gaming analytics leverages the user data from games for business decisions, marketing activities, and product improvement.

Use cases of analytics for gaming include improving the game design, monetization for increased revenue, effective marketing strategy, and many more.

The 4 Steps of Gaming Analytics

There are stages to analytics called analytics maturity models that describe them based on their criticality. Let us classify these into four stages:

Stage 1: Descriptive Analytics

Descriptive analytics is a solution when a gaming organization is trying to answer the question, What happened?

Descriptive analytics through the depiction of available data provides an understanding of the present situation, giving a realistic view of current events and potential opportunities.

The effectiveness of power-ups, health packs, and save points in certain game levels can be determined using descriptive analytics.

Stage 2: Diagnostic Analytics

Diagnostic analytics is the solution to the question, – Why did this happen?

It is used in determining the relationship between two variable elements by analyzing historical game data. One of the most vital outputs of diagnostic analytics is to find an organization’s effectiveness, “How are the results compared to the efforts?” 

Why does one of the players get such a lower score than the others in one of the challenges? Diagnostic analytics provides the answers, even for end gamers in games like Hitman, where there are parameters for completing particular achievements.

Stage 3: Predictive Analytics

We are now entering the meatier part of game analytics. Predictive analytics falls under the advanced stage territory of analytics. Unlike descriptive and diagnostic analytics, predictive analytics plugs in and tracks gamer behavior in real-time.

By creating forecasts, predictive analytics can measure and foresee the consequences of various actions.

There are patterns and trends in the gameplay data that can be used to understand the elements that make the game great and areas where improvement is necessary.

On the marketing side, predictive analytics can help gaming businesses identify target users for user acquisition; all these factors help optimize their marketing budget.

Here is an example of a mobile gaming company using predictive analytics to find target customers.

With the marvel of predictive analytics, gaming companies can foresee their business scenarios as active participants, making sustainable and profitable business decisions while providing excellent gameplay to players, resulting in increased play-time and in-game spending.

Stage 4: Prescriptive Analytics

Prescriptive analytics is the final boss of the analytics game. The stages of analytics till now can provide a gaming business with tons of information, painting a picture that tells a story. 

Prescriptive analytics leverages these stages and helps businesses take action, turning the data into results with fruition.

While machine learning and artificial intelligence are just thrown around everywhere on the internet, prescriptive analytics uses machine learning algorithms to make optimum decision recommendations.   

There is no need to wonder about the right course of action. Prescriptive analytics uses artificial intelligence and machine learning algorithms to run millions of simulations with precision and recommends the best outcome, leveraging the prowess of Big Data.

Prescriptive analytics is so robust that it can dive deep and shed clear light on data patterns and trends. Not only is this useful in games, but it can also help understand the pulse of consumers and help companies improve customer engagement.

Game Analytics is a Driving Force for Game Studios

A plethora of challenges plagues the present-day video game industry. Studios have to deal with a million variables in player preferences and design mission levels that engage the vast userbase across the globe.

The gameplay experience is one area where game analytics will be the game-changer. Studios always face the uphill task of designing the perfect difficulty levels for their games. Developers have to develop their game levels to maintain the right balance between challenge and progression.

Game UI is also an area that studios cannot overlook. It impacts the gameplay experience and affects the time spent by the player.

Game analytics may seem overkill at first glance, but we live in a data-fueled generation with an ever-increasing dependency on the internet. We saw what the pandemic did to many industries. It also helped us understand the importance of being ready for the unknown.

Gaming is one industry that had the fortune of seeing an upward trend during the pandemic, making an even more compelling argument for implementing game analytics.

With the increased number of gamers, spending on games has also increased, and game studios must leverage the potential. To do that, every decision must be weighed not only in terms of business optimization but also in providing value to the players. Understanding the player sentiment is the key to cracking the monetization strategy, non-intrusive and engaging ads, while tapping into potential player spending using fair practices, resulting in increased ROI. 

Game analytics is not a fancy service. From lndie to large AAA, every type of studio can leverage game analytics to have a foolproof system in place, guiding them with well-informed business decisions resulting from precision with no room for human error. 

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Cloud Analytics to Improve the Clout of Indie Games

Indie games were once for a niche crowd that enjoyed the retro-styled game design and mission progression. Low-key passionate developers who made the quality-of-life mods for popular games, or some brave heart developer who would try to cook up a game with an archaic code and a sub-par computer, made indie games back then. Even if someone managed to make an indie game with the minimum resources, there would be no buzz around the game since no major studio entertained such games.

Today, the Indie game scene is thriving and mainstream, with a sizeable audience. A lot has evolved to an extent that the term “Indie games” has been redefined.

Games like Hollow Knight, Terraria, and Among Us weren’t just chartbusters; they made the Indie space a mainstream one with a solid audience and substantial foothold in the market. What further echoes the success of Indie games is the fact that their development requires a significantly lower budget compared to mainstream AAA, RPG, and Sports games. Their pricing is competitive, aimed at garnering more takers and relying on mass sales volumes. Raking high revenue with a low budget is a guaranteed blueprint for maximizing ROI. But with a limited budget, Indie developers have a set of daunting challenges developing and releasing games in the long run.

The Rise of Indie Games

Many factors have contributed to the rise of Indie games.

The unsung hero here is the digital download platforms powered by cloud backend that make game downloads easier and more economical while helping indie games foray into the average gamer’s library.

Unlike large studios, Indie developers fell short of the budget to churn out physical copies in copious amounts, restricting the reach and exposure of their games no matter how good.

With Steam, GOG, EPIC, and other digital storefronts backed by cloud infrastructure and data centers worldwide for local downloads, it is just a matter of uploading their games to the cloud and letting gamers across the world download them.

Digital platforms became mainstream, and indie developers didn’t have to worry about manufacturing expenses owing to making physical game copies eating into their profits.

Indie Marketing – A Challenge That Cloud Can Address

We see a regular churning out of tons of indie games. The segment is one of the most competitive. For successful indie titles like Celeste and Minecraft, hundreds of games go unnoticed.

Multiple factors are at play here.

Marketing is one key aspect where Indie studios lack the resources to reach a global audience. Like with large studios, volume-based marketing may be impossible for small studios, but effective data-based marketing is not only possible but imperative.

Efficient targeting is the lifeline of successful marketing. Bombarding social media platforms with ads without a proper marketing plan will not result in user acquisition or brand engagement. You must understand your target base before going all out on digital marketing.

Marketing and user acquisition in this day and age is an omnichannel affair. Video games have a global audience, and studios cannot afford to overlook this factor.

Improving the reach of games requires a well-crafted marketing plan that covers all grounds.

Analytics-based marketing is the core to ascertaining the audience base for game studios. The keyword here is data-collecting data at every avenue, and online touchpoints are vital to understanding customer behavior and patterns.

But it is also the first step toward the logical marvel of data-powered analytics

Data Collection, Analytics, and ROI (Return on Investment)

With the advent of digital marketing, the term “marketing” is thrown around like confetti, and small, less experienced businesses like indie game studios find it challenging as much is lost in translation.

Indie studios must focus on collecting vital data like game metrics to understand their players’ behavior and data from social media platforms that can help them tune their marketing campaigns for maximum efficiency.

Combining the accrued data with cloud analytics helps studios with ROI-based marketing, giving them a real-time view of what’s going on with their marketing activities instead of a “what went wrong?” meeting.

This way, real-time tweaks to the digital marketing efforts are made possible, and studios can focus on targeting prospective leads on particular social platforms rather than unnecessarily advertising on every platform and user.

Since indie studios have a limited marketing budget, effective ROI-based marketing is the ideal balance to help achieve brand recognition and user acquisition.

Game Analytics – A Must-have Solution for Indie Game Studios

We saw the advantages of cloud-based analytics solutions for marketing. Now, let us look at game analytics that can help indie studios tweak their games and release updates and patches that result in increased player engagement and game lifetime overall.

Game metrics can help studios offer users a dynamic gameplay experience.

Player fatigue, monotonous gameplay, and challenging levels play spoilsport in the long run and affect the gameplay duration of players. DLC and additional content can help here, but it involves resources like budget, development, and workforce.

With game analytics, studios can read real-time game metrics, analyze them, and improve gameplay so that players will put more hours into the game. All this comes without worrying about the additional development cost and human resources for DLC.

There are plug-n-play game analytics solutions that overcome the infrastructural challenges and initial setup costs. Even the maintenance is done on the service provider’s end so that studios can focus on improving the player gameplay experience, the true intent of these solutions rather than logistics.

Indie studios can avail such game analytics solutions on a Netflix-like subscription model from pioneers in the analytics industry, with impressive track records and pedigree working with industry giants.

Cloud Solutions for Indie Game Studios are Not Only Imminent, but Imperative

Even the Silicon Valley giants have acknowledged that the cloud is paving the way for gaming and have introduced multiple cloud-based gaming services.

In 2020, Google introduced a managed service program called Game Servers. Unlike Stadia, Game Servers isn’t a game streaming service but a backend cloud server infrastructure that helps game developers build and scale backend servers for their game titles. So, unlike the common misconception that the cloud in gaming only means streaming, the cloud also plays a vital role in acting as a backend infrastructure for all types of games.

With a considerable stake in gaming and its recent acquisition of Activision Blizzard, Microsoft has revealed its new product, ID@Azure, which lets indie game developers develop their games from scratch for the cloud platform.

Large studios have already made this transition and are reaping its benefits, not only in terms of cost but also in the elimination of managing the backend infrastructure. Why spend time and resources on it, when many service providers like AWS (Amazon Web Services), Microsoft Azure, Google and others can take care of it while developers adapt to the subscription cost model and focus only on making quality games?

A German indie mobile game studio, Coldfire games, eliminated its backend management efforts due to adopting an efficient cloud infrastructure. It is the only time before other indie developers follow suit and adopt cloud infrastructure as a backend to their games.

Then we have the cloud gaming phenomenon, which is set to gain significant traction over the next few years, with players like Netflix getting into gaming and giants like Google and Nvidia having services in place. Just like streaming became mainstream, cloud gaming will set a benchmark in mainstream gaming, and developers need to adapt to this, providing games at a subscription model.

From marketing to game analytics and backend infrastructure, cloud solutions are highly beneficial to game studios, particularly Indie developers who don’t necessarily come equipped with the resources, team, and technical know-how for game marketing and analytics. But it can be challenging to choose the right ally for your game analytics requirements. Affine is a pioneer player in the AI analytics arena, working with large and indie gaming organizations to synthesize game analytics into efficient and effective business outcomes

.Get game analytics for your business

The passion for developing exceptional games is all an indie studio needs, for cloud-based solutions are plenty with simple implementation techniques and measurable ROI-based results that will assist them in every step.

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How to Create the Best Work Culture in a Startup

As the tech industry witnesses high attrition rates, work culture is in the spotlight again. Given the abundance of funding in the ecosystem, startups have to offer more than just the best compensation; the right work culture may just be the differentiator that attracts high-quality talent. Let’s first start by understanding what “work culture” actually entails.

Work culture is a combination of vision, attitude, values, that defines the way your people act and react to different scenarios. This builds the overall atmosphere in a workplace. Typically, in start-ups, the culture is strongly influenced by the founders of the company vs. the larger organisations where the culture is promoted and invested in heavily with conscious effort.

Spoiler Alert: You Already Have a Work Culture

Work culture is crucial from the time we set up a company and hire the very first employee because this becomes the organization’s foundation to overall happiness, productivity, and growth.

In the initial stages of startups, founders are usually busy setting up their business, and more often or not, culture gets neglected. They believe it’s something they will focus on down the track, when they hit 50 employees, 100 employees or more.

Little do many realise, that they have a culture from the moment they take on an employee. In fact, your culture has already kicked in if you have two or more founders. You may be unaware of it, but there’s already a culture attached, and it is up to you to help craft a strong, positive one.

Key Benefits of Positive Work Culture

Work culture is as vital as your business strategy because it can either strengthen or undermine your objectives.

· Employees can get on with their jobs, improving productivity, rather than focus on what is going wrong with the organization and the leadership team.

· Employees are proud to work for positive organizations and share their experience with their social networks, enhancing the company brand.

· Knowledge and experience are shared between employees, which improves efficiency, productivity, and performance.

· People enjoy coming to work and are more committed to the organization, reducing the immense costs of turnover.

· Employees go home happier and more satisfied, which impacts their families and friends.

Work Culture

Examples

”People Over Process.”

Netflix has a set of ideals in which they strongly believe and want their employees to live out in their job.

“Culture of Camaraderie”

Customers are embraced as part of their culture; they even bake a cake each time a new customer goes live.

HubSpot’s Culture Code Treats Culture Like a Product

Transparency and trust are essential to HubSpot’s success, operating with a default to open policy.

Employees are considered insiders, ensuring they know everything that affects the company before the press or investors do.

HubSpot’s culture is built on the foundation that power is gained by sharing knowledge, not hoarding it.

Airbnb: A Culture Where Anyone Belongs

Airbnb has managed to build a culture that is not only committed to its purpose and core values but also, a relentless belief in candid two-way communication.

The thumb rule is that nobody should hear about anything externally until they are first told internally.

The perfect example of this are leadership meetings – employees get the notes of everything that was discussed just 24 hours after each executive meeting.

How to Set up the Right Work Culture?

· To start building the work culture of your dreams, first, emphasize your core values.

· These should be the foundation of everything that happens at your company and guide your organization’s evolution.

· Dedicate as much time as necessary to ensure everyone is aligned and include leadership, long-term employees, and HR representatives so all significant parties can weigh in.

· In the end, you should have a concise list of values that accurately reflects your current company culture and long-term goals.

· Then, think about the type of work culture you want to create. Consider everything from the physical layout of the office to how frequently employees interact with their colleagues, managers, and members of the C-Suite. From there, the real work begins.

In Summary

Creating a positive, strong company culture at a startup is one way to help ensure the longevity of your business. Taking time out to find out how the team is feeling and what your shared values are is an excellent start towards building a company culture that will last as your team expands and your business gets bigger.

Even at an early stage, you are creating a culture, whether consciously or not, so set aside time to nurture it the way you want it to grow. At the Affine DeepCamp accelerator program, I mentor startups to establish a framework for a workplace culture that can sustain and fuel the high pace growth momentum.

Cloud’s Role in the Rise of Gaming

Gaming is one of the fastest evolving industries, with considerable technological advancements. We’ve come from retro arcade games to LAN parties and playing portable smart gadgets on the go.

In terms of graphics, we saw the evolution from pixel art to 2d, and then 3d models. While PC has always been able to do justice to the visually exquisite-looking titles, current-generation consoles have changed the dynamics of the graphics race. Ultra-realistic graphics with reflective surfaces and interactive environments give users an immersive gaming experience. All this before even dipping toes into Virtual Reality, which is yet to hit mainstream status.

The pandemic witnessed a sudden spike in the interest in gaming. People flocked to play games, which served as an interactive pastime compared to streaming shows and movies. The aftermath? The gaming industry raked in revenue of $156 billion as of September 2021, and the global video game market is forecasted to cross $200 billion as of 2023!

Cloud is the Backbone of the ‘Always Online’ Culture

The lack of proper infrastructure in the previous generation limited gaming options to local play, offline games, and LAN parties at best.

Massively Multiplayer Online games were a pipe dream back then. But with the turn of the millennium, things changed. 

Small data centers became multiple server farms with global CDN (Content Delivery Network) for maximum scalability.

Multiplayer games have gained significant traction over the years and are now a norm. Today we have a plethora of multiplayer online titles, with single-player games providing multiplayer options for players who want to explore beyond the original storyline.

Titles like Rainbow Six Siege made bank for Ubisoft with lifetime sales of over 1.1 billion as of 2021, with a player base of 70 million as of 2021.

The cloud infrastructure in place for a feat like this speaks for itself, which would have been impossible a decade back, simply owing to the lack of tech infrastructure.

Single-player games significantly depend on the cloud infrastructure thanks to the paradigm shift from DVDs to digital game stores like Steam, Epic Games, and GOG. Pre-loading games, cloud saves, day one updates, and DLCs are standard practices in the gaming industry now. The days of waiting in long lines for days before the next GTA release is a thumbnail in history. With millions of players downloading at a time across the globe, sustainable cloud infrastructure is at the heart of gaming infrastructure.

Gaming on Demand will be a Reckoning Force in the Future of Gaming

Gaming on-demand or gaming as a service is growing by the day and will shape the path of gaming as it did with content consumption via streaming. Steam link, Nvidia GameStream PS4 RemotePlay and many such services offer gaming to the end-user on reasonably fast internet. Gaming hardware bundled with free games and discounts still comes with the invisible baggage of limitations owing to short cycle yearly tech upgrades in the gaming industry, nullifying the economy factor in gaming. 

Developing games for multiple platforms is also an arduous, time-consuming task for game developers, which results in inconsistent gameplay experiences for the player. We’ve seen releases like Watchdogs, CyberPunk2077 looking graphically inferior in their release versions compared to the announcement versions. While many factors are at play here, the challenge to develop games for a previous generation platform alongside the next generation of consoles with high-end hardware causes compatibility issues in the game build and adds to the development cycle. Gamers also have to wait a long time since the release dates keep getting pushed to accommodate fixes to the build.

The high upfront cost for purchase and scarcity of vital hardware components like storage, RAM, and Graphic Cards create an opportunist and hobbyist culture in gaming. Thankfully, the advent of Gaming on-demand will address the issue. While it may take some time for global adoption, the end result not only provides every gamer the opportunity to high-speed gaming, game makers get access to the end-users without the hindrance or hardware barrier.

Cloud Gaming will be the Netflix of Games

While Netflix is testing waters and entering the gaming domain with mobile games, cloud gaming is an underlying phenomenon that will transform the industry and cement its position as the next chapter in gaming.

Stadia may have fallen short of wowing the gaming community, but there are perils to being an early adopter. For one, the number of mobile gamers in recent years has seen an alarming spike thanks to PvP games like PUBG and Fortnite captivating the masses and converting non-gamers into serious, habitual gamers.

This opens the doors for cross-platform play, which is currently a pipe dream with rare working examples, but all this will change with the cloud technology at the center stage.

With cloud gaming at the helm, the industry envisions a platform-agnostic gaming ecosystem powered by high-speed internet, primarily relying on robust cloud infrastructure for inclusive, sustainable and affordable gaming.

Currently, there is a global hardware draught from the pandemic’s disruption of manufacturing & supply chain, in addition to scalpers grabbing available stocks. This is a testament to how the dependency on hardware for gaming has reached a saturation point.

By eliminating the storage and graphical requirements that are a roadblock for many aspiring gamers, cloud gaming (gaming on demand) brings the biggest USP to the table for gamers, developers and studios. Gamers don’t have to break their bank going on a hardware shopping spree for next-gen graphics or order terabytes of high-performance Solid-State Drives for games that cross the 100GB mark. 

Developers don’t have to fret over the game’s performance fidelity across multiple platforms or downgrade the graphics so that players can achieve decent frame rates across different types of devices. There’ll also be a significant reduction in the development period, which could help release games as per the dates advertised!

Studios can increase their target audience from hardcore gamers to even new players since the hardware barrier is no longer an issue. A feasible subscription gaming model will onboard a significant number of new gamers, and studios are looking at a rise in their user base with an imminent increase in ROI and a sustainable business model.

Cloud gaming emphasizes safety which is vital in online gaming. Player information leaking on the internet is nothing new, and even the top-of-the-crop studios like Bethesda have had this misfortune with Fallout 76. Cloud-based gaming models have bulletproof online security, which reduces the chances of player databases getting breached by external attacks and information leaks across the web.

Conclusion

Spending for modern hardware every 2-3 years at inflated astronomical prices in the current economy is not practical for players. Not to mention the pile-up of hardware junk which is not sustainable for a green future. A subscription model, in the long run, is a better alternative.

For businesses, the cost advantage is obvious. Setting up new infrastructure that requires frequent upgrades is a messy and costly affair that entails enormous resource consumption. The big cloud players offer these services for a fraction of the cost with unlimited scalability options and an ‘only pay for what you use’ model. 

Cloud is not all hype. We’ve seen its role in streaming, and the technology has shaped up the OTT platforms today, providing access to quality content within the press of a button to users across the globe. The question is how long until it becomes mainstream in the gaming space. Sure, hardware-based gaming will not go extinct. But a shift towards cloud gaming is imminent. 

Cloud and gaming go hand in hand. If the present is anything to go by, the dependency on cloud is only going to go up with time. 

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Accelerator or Incubator, Which One is Right for Your Startup?

Bringing ideas to life and transforming them into a business requires time, effort, and patience. It is crucial to have a support network in place that aids in the early stages of a startup’s growth. Accelerators and incubators can be highly beneficial at this point. Many entrepreneurs rely upon these pillars seeking expert assistance in getting their business off the ground.

But first, let’s understand what the difference is between startup accelerators and incubators, and how both function.

What is an Accelerator?

An Accelerator is a program that helps startups to improve their product/solution, gain access to investors, networking opportunities, skills development, and advice from industry experts.

Usually, accelerators work with a startup’s founders over a certain period of time – typically three to six months – to ‘accelerate’ their growth and assist in the development of a business that is investment-ready and scalable.

In the early stages, startups are often given a small seed investment, which could be used to fund research, marketing, fine-tune a product, or hire new team members. In return, accelerators will usually receive a small share of the business.

E.g. https://affine.ai/affine-deep-camp-accelerator-program/

What is an Incubator?

An Incubator is an organization that helps startups and individual entrepreneurs to develop their businesses by providing a full-scale support.

These are usually non-profit organizations, often associated with universities and business schools that extend invitations to students, alumni, and members of the community to take advantage of the program.

During an incubator, founders spend time networking with other entrepreneurs, building on their idea, determining product-market fit, and getting investment-ready.

Much like accelerators, incubators offer access to industry experts who can provide guidance and training, as well as the opportunity to network with other entrepreneurs and startups in the program.

E.g. http://www.incubation.iitm.ac.in/home

Key Differences Between Accelerator vs Incubator Program

Which One is Right for You?

Accelerators advance the growth of existing companies with an idea and business model in place. These programs build on the foundations of the startups to catapult them forward to investors and key influencers.

Accelerators operate on a set timeframe, which usually lasts three to six months. During this period, startups build out their business with the support of mentors and capital provided by the accelerator. At the end of the program, startups receive the opportunity to pitch their businesses to investors.

Incubators support startups entering the beginning stages of building their company. The startups
possess an idea to bring to the marketplace, but has no business model and direction to transition
from innovative idea to reality.

Incubators operate on an open-ended timeline. They focus more on the longevity of a startup and
are less concerned with how quickly the company grows.

Incubators and accelerators are both viable solutions for accelerating the growth of your startup. Before choosing your path, make sure you do your homework and ask a lot of questions.

(P.S) It is a rare opportunity for startups that Affine’s DeepCamp Accelerator program does not expect equity stake at all for startups if the solution is a game-changer.

You can check more about Affine’s DeepCamp accelerator program here: 

https://affine.ai/affine-deep-camp-accelerator-program/

How Can Startups Implement AI in their Solution?

While building an AI strategy for startups may seem difficult, it has now become a necessity to gain a long-term competitive advantage. 

Given their limited resources, the benefits of integrating AI are more beneficial for startups. It is an excellent chance to automate, enhance, and simplify their operations. 

The following are some of the steps involved in a startup pivoting to integrate AI into their solution:  

  1. Discover - Identifying areas where AI can make a difference. 
  2. Define - Curating specific use cases that could lead to POC. 
  3. Prioritize - Prioritizing use cases that the team should focus on developing. 
  4. Develop – Getting your team geared up to develop a proof of concept.  
  5. Test and Validate - Testing and validation should be done internally and externally. There simply isn’t anything that replaces a client’s validation. 
  6. GTM - The solution’s final market introduction. 

Startups in different stages require a different approach. For example: 

  • An early-stage startup applies narrow AI solutions to tackle specific problems in the industry. 
  • A growth-stage startup uses AI solutions to enhance customer experience and drive more market share. 
  • An enterprise-stage startup integrates AI into its process for higher efficiency, productivity, or profit margins. 

Startups pivoting to adopt AI must ensure that all the necessary resources are in place for these pillars.  

Affine’s DeepCamp is a startup accelerator program for Tech Businesses that provide access to Affine’s Centre of Excellence (CoEs) across AI, Engineering & Cloud for cutting-edge solutions and swift market access. 

Industrial Sensors and AI: What Lays in the Gap Between MSMEs and Industry 4.0?

Global industrial automation is transcending boundaries at breakneck speed. In 2020, the market for industrial automation was pegged at USD 175 billion and is touted to grow at a rate of 9% by 2025. This has been a product of the Industry 4.0 wave.

Further, unlocking the full capabilities of IoT and AI within different workflows and frameworks has been a breakthrough trend for industries across all major sectors.

One pertinent aspect of this growth has been the role of sensors in manufacturing industries. They have been a keen driver in the shift to “smart” machinery. But before we delve further into their significance, there’s some jargon we need to get out of the way:

Making Sense of Non-IoT, IoT, and IIoT Sensors

Sensors are devices that can detect (or sense, as the name indicates) changes in an environment. 

Consider a manufacturer of sanitary napkins. Their factory floor would incorporate a wide range of sensors for different environmental conditions in their manufacturing processes. There are three possible kinds of sensors they could use. One can be a conventional humidity sensor that merely indicates the humidity in the areas where raw materials are stored. It displays the humidity level, and that’s all; there is no interaction of this data point with any other piece of data.

An IoT-based humidity sensor can track and remotely change the levels or give real-time alerts because it connects to the network. It stores humidity level recordings on a daily, weekly, and monthly basis for you to gain key business insights related to your manufacturing processes and optimize them accordingly for that factory floor.

Now consider this usage of sensor data across thousands of factory floors on a large scale. Businesses can compile all recordings in a central system and visualize the data as required.

Now that’s a step further than IoT; it’s IIoT, i.e., Industrial Internet of Things.

Automating Workflows Intelligently, Using AI 

The sheer amount of data that sensors can generate may be daunting.

You might not know how to visualize this data to make it actionable.

Machine learning models are dependent on repositories of data that they can train with. This is where an IoT sensor comes into the picture as it collects and communicates all the data it measures and run AI algorithms to deliver real-time actionable insights.

Let’s use the manufacturing industry example once more.

AI solutions can bring together all the data collected from various sensors, such as temperature data, humidity recordings, moisture content, and vibrations from machinery inside the manufacturing unit. It could even have defined thresholds to detect anomalies in the products and flag them for mitigation. AI tools can make sense of all these data streams to determine optimal conditions at each stage of the production of sanitary napkins.

The business can use IoT sensor-generated data to calibrate its workflows, make the product more consistent improve quality, and hence the revenue.

This will be dependent on capitalizing on the data collected through robust AI models.

Some Inhibiting Factors in Taking a Leap Forward

  • Integration roadblocks: Legacy systems were never meant to connect to the internet and involving such systems in the IoT or IIoT network may require adopting a network-agnostic platform. The conventional non IoT sensors cannot collect data that can be aggregated and visualized.
  • Limitations in Technology Maturity: Synchronizing various sensors and devices on an IoT platform will require niche AI expertise.
  • Capex Constraints: Many organizations are worried on making considerable hardware investment and allocation of budget towards IoT sensors to adopt AI advantage.

Does That Mean Businesses with Non-IoT Sensors Will Be Left Behind? 

No!

While it is crucial to have equipment with sensors that communicate data for AI tools to study and recognize patterns, you can achieve the same result even with legacy systems and non-IoT sensors.

You do not have to make heavy investments in IoT sensors to capitalize on sensor data. While an eventual transition to IoT or IIoT sensors from non-IoT sensors may be needed to keep up with AI advancements, below are the few techniques that help you plan for with your existing setup:

  • Use IO-Link: This can collect information from your sensor through the IO-Link Master and activate communication at the sensor level. Instead of using an IoT sensor, you integrate IoT into your traditional sensors using an IO-Link. It receives signals and data from the sensors and exports it to the manufacturing site. This process helps in predictive maintenance, thus reducing extended downtimes or overburdening of human capital; all the benefits of IoT sensors, but with conventional sensors.
Source: Omron
  • Adopt Edge Technology: Manufactures can bring system integrators that connect HMI systems using edge architecture. This minimizes interoperability issues between legacy systems and AI and other monitoring tools.

Traditional Manufacturers Have Begun their AI Journey!

The legacy systems are getting a fresh lease of life with technology interventions and manufacturers are gaining competitive advantage in the market. 

Consider this.

Here is the case of a business that provided tools for grain moisture control. These products would help farmers prevent spoilage of grain due to environmental conditions.

But a majority of farmers did not have access to the latest technology. They relied on traditional equipment with conventional moisture and temperature sensors. Their grain monitoring systems were not compatible with modern IoT sensors and cables.

Therefore, these farmers needed alternative methods to make most of these grain moisture control products.

The goal was to integrate their legacy equipment with alternate monitoring methods to achieve the same benefits of IoT systems and sensors.

The solution came in the form of a controller that incorporated a Programmable Logic Controller (PLC) system using edge-forward middleware architecture. It was connected to the farmers’ traditional sensors. Now, even without IoT sensors, the farmers could remotely monitor their grain warehouse site and track parameters such as grain spoilage, temperatures, energy costs, and more. This helped them reduce wastage and gain higher returns on their crop.

As illustrated, the potential of alternate methods that interact with legacy systems to generate data is endless. If you are a small organization with limited cloud capabilities or an MSME with traditional equipment, these solutions can help you make the most out of your non-IoT equipment.

The Stage is Set, It’s Time to Act

Traditional manufacturing industries that do not necessarily have the equipment or financial resources to invest in IoT sensors can still capitalize on AI technology and gain high returns. Start looking at your legacy systems as cost-efficiencies rather than inhibitors using alternative interventions! 

If you want to be at par with those businesses that are making headway with AI powered growth while retaining your current setup, talk to us.

5 Pillars of AI Deployment in Startups

Although AI is becoming a critical factor in the long-term success of startups, a majority of them fail to deploy it. Most of them feel that employing the best in tech would address their problems, when in reality, the lack of cultural agility and leadership stands in the way of AI adoption.

Startups should consider these five pillars of successful AI implementation before mapping out the adoption plan.

1. Strategy

Business leaders regard strategy as an essential component of deploying AI solutions. It must include elements of Customer Service Improvement, Cost of Deployment, Culture Management, and ROI to figure out the potential success of AI deployment. A clear understanding of various factors can save startups from losing millions in a failed AI deployment.

2. Data

Having access to the correct data and a lot of it is a significant challenge for startups. Some startups claim to have created the most incredible AI model, but they fail miserably when tested with clients’ data. Data must be sufficiently large to factor in all kinds of biases in decision-making. If sufficient data is not available for a problem statement, startups must avoid jumping on to create a sub-par AI model.

3. Technology

Business leaders must define the problem statement and the requirements before figuring out which technology to use. Choice of Technology & Cloud is crucial for any enterprise implementing an AI Solution. When considering a particular technology, a startup must examine a variety of parameters, including the speed of development, the cost of scaling, and the availability of skills in the market.

4. People & Talent

Today, almost every startup is struggling to hire & retain skilled employees due to the gap in demand & supply in the talent market. However, the supply problem will ease with time as more IT companies deploy internal resources to train talent. For the time being, companies may rely on empowering good employees as decision-making stakeholders for a retention strategy.

5. Governance

When building an AI model, always consider its governance. Startups failing to do so can find themselves struggling with lawsuits as a poor outcome from AI solutions that can cause potential losses to clients & partners. For example, a recent report from a leading media house highlighted how developers from a known startup had direct access to customer data from social media channels. The article highlighted that companies like Google & Facebook take strict actions in such cases.

Startups pivoting to adopt AI must ensure that all the necessary resources are in place for these pillars.

Affine’s DeepCamp, a startup accelerator program for Tech Businesses, creates an ecosystem that enables startups to innovate, adapt and improvise AI capabilities, giving them a sustainable edge over the competition.

Potential entrepreneurs can access Affine’s Centre of Excellence (CoEs) across AI, Engineering & Cloud to build cutting-edge solutions for swift market access with DeepCamp.

Is AI Creating Values for Startups?

Only the world’s top businesses could afford to invest in AI a decade ago, but things have changed drastically in the last 5-6 years. AI has become the new normal due to the advanced modernization on various fronts. Today, startups have more opportunities than ever to leverage AI for countless products and services that can bring solutions to their stakeholders on multiple fronts.

Some of the areas that startups are using AI to bring value to their process and stakeholders are:

Creating Efficiencies:

  1. Automation of processes (Complex processes have been automated, reducing the cost of the business)
  2. Analytics (Huge sets of data can be analyzed and better strategies can be developed)
  3. Development efforts (Services for code review, deployments, QA)

Increase Productivity:

  1. Manufacturing – (AI can validate whether intricate goods like microchips have been perfectly produced)
  2. Predictive & Preventative Maintenance – (AI is used for identifying PM schedules that can be optimized prior to the predicted breakdown, which avoids downtime)
  3. Production Optimization – (AI will constantly learn from all production data points to continuously improve process parameters.)

Improving Customer Experience:

  1. Better insights using AI – thus creating better product preferences for customers
  2. Customer support – Chatbots (A study says, about 65% of the agents working AI-based chatbots were able to spend more time on Complex customer problems and solve them faster.)
  3. Consumer Insights – (AI can help create customer personas, match customers’ preferences of products they are more likely to buy, and display the most relevant content to readers)

With the exponential advent of AI and its applications – it is envisaged to eliminate mundane day-to-day business operations and enhance the efficacy in business processes at startups. AI solutions are more cost-effective than other traditional methods as they take a systematic approach for every aspect. AI is a cutting edge of Innovation.

At Deep Camp, we mentor startups on various possible ways that will improvise their processes to yield better outcomes through AI. With a focus on scalability through AI, we mentor them on numerous business functions like Marketing, Sales, Finance, Operations, HR, and Strategy.

Deep Camp is a startup accelerator program that focuses Tech Businesses. Potential entrepreneurs are provided access to Affine’s Centre of Excellence teams (CoEs) across AI, Engineering & Cloud to build bleeding-edge solutions and find swift market access.

Manas Agrawal

CEO & Co-Founder

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