The Role of API Testing in Open Banking

The Role of API Testing in Open Banking

The Role of API Testing in Open Banking

Author – Mahesh C (TestOps Leader)

Understanding Open Banking

Open banking is the process of making banking information and services available to third parties via APIs, enabling them to access financial data and carry out transactions on behalf of users.

Open banking enables Fintech’s APIs to map their services to users data. With users agreement, open banking shifted from a closed data model to an open one, which allows user data sharing across third parties like software companies and other businesses.

These third parties have access to users financial data like transactions, account balances and credit transfer commencement, which is used in creating better and improved services for customers like bank account aggregation tools, budget management tools and digital lending.

Open Banking provides flexibility to customers and creates a more complex competitive environment 

 

Open Banking vs Traditional Banking

 

Role of Open APIs in fintech industry and how they are transforming Banking Experience? 

Open Banking has been an integral part of European regulation for electronic payment services and is based on utilization of API access to users financial data and other resources.

Thanks to Open banking, fintech can elevate the banking experience and is now delivering a variety of effective services, including less dependency and quicker cross-border settlements.

The usage of open APIs is increasing rapidly and fintech must ensure comprehensive, secure and real-time data sharing through open APIs.

Importance of API testing in Open Banking

Secure and seamless sharing of financial data and services between various financial institutions and third parties is made possible by API testing, which is essential in the context of open banking.

The role of API testing in open banking is as follows:

Security Validation – To truly elevate the Quality of Experience (QoE) for OTT users, context-aware experiences play a pivotal role in meeting their preferences and expectations across various devices.

Functional Compliance –  When adopting open banking APIs, financial organizations must follow certain rules and regulations, such as PSD2 (Payment Services Directive 2) in Europe. API testing ensures that APIs work as intended and adhere to these criteria.

Data Accuracy – Open banking, accurate and trustworthy data exchange is essential. API testing guarantees accuracy, consistency and security of data delivered via APIs.

 

Performance Testing – While dealing with millions of requests, open banking APIs must maintain a high response rate and reliability. The functioning of API is evaluated through performance testing to make sure it can manage anticipated traffic without performance deterioration.

 

Error Handling – To help end users identify the problem and developers resolve issues, open banking APIs must give clear and concise error messages. Error-handling mechanisms are tested during API testing to make sure they are efficient and clear.

 

Integration Testing –  Open banking involves a number of partners, including banks, vendors and different software programs. APIs seamless interaction with one another and underlying systems is verified through integration testing.

 

User Experience – API testing has a direct impact on application’s user experience. It ensures application reliability, security, performance, reduced downtime and scalability, which are essential to having an outstanding user experience.

Open Banking Implementation Entity (OBIE) Metrics – 

Response Time and Latency –  Average response time and latency of microservices’ endpoints.

Importance: Low response time and latency are crucial for providing a smooth and responsive user experience.

Error Rates –  Error rates or the percentage of failed requests.

Importance –  Monitoring error rates helps identify issues in the microservices’ functionality or communication.

Throughput: Number of requests processed per unit of time.

Importance –  High throughput is essential for handling a large number of requests efficiently.

Availability and Uptime –  System uptime and availability.

Importance: Microservices need to be highly available to ensure continuous service for users.

Resource Utilization –  CPU, memory and other resource utilization metrics for individual microservices.

Importance – Monitoring resource usage helps optimize microservices performance and scalability.

Scalability Metrics –  Metrics related to scaling events (e.g., auto-scaling triggers, instances added/removed).

Importance – Scaling effectively based on demand is crucial for maintaining performance.

Dependency Monitoring –  Monitoring the health and performance of dependencies (e.g., databases, third-party APIs) that microservices rely on.

Importance –  Poorly performing dependencies can impact the overall system’s performance.

End-to-End Transaction Monitoring –  Monitoring the complete flow of transactions across multiple microservices.

Importance –  Tracking transactions journeys helps identify bottlenecks and optimize overall performance.

Mean Time to Recovery (MTTR) – The average time it takes to recover from failures or incidents.

Importance –  A low MTTR indicates efficient incident response and recovery processes.

API Usage and Traffic – Monitoring API usage and traffic patterns for individual microservices.

Importance –  Understanding how APIs are used helps optimize their design and performance.

In conclusion, inclusive API testing ensures seamless sharing of users’ sensitive financial data between various financial institutions and third parties. It embeds essential authentication, authorization processes and compliance standards into the open banking system and makes sure accurate data exchange and highest API performance, providing a smooth and responsive user experience.

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Unlocking OTT Success: The Transformative Impact of QoE Validation on OTT Businesses

Unlocking OTT Success: The Transformative Impact of QoE Validation on OTT Businesses

Author – Abhilash Suryanarayan ( OTT Practice Lead)

Introduction

Over the years, Quality of Experience (QoE) validation has emerged as the backbone of success for Over-The-Top (OTT) platforms. In this blog, we explore the indispensable role of QoE validation, how it is performed through advanced solutions and its profound impact on OTT business. Reading this blog will help you ensure seamless content delivery, optimize user engagement and drive customer loyalty.

The Core of QoE Validation

At the heart of QoE validation lies the need to evaluate application performance from users’ perspective. Solutions like Witbe offers comprehensive analytics, monitoring capabilities and real-time insights into video quality, buffering, response and playback rate.

According to a study by Ericsson ConsumerLab, 75% of viewers consider good video quality the most crucial factor in their streaming experience.

 These insights empower testing teams to identify and address issues proactively, ensuring a seamless streaming experience for users.

Elevating User Satisfaction & Engagement

User satisfaction is crucial for the success of OTT platforms.

According to research by Deloitte, 79% of users cancel their subscriptions due to buffering and poor video quality.Everyone can grow in growth mindset, while fixed mindsets imprison your creativity.”

QoE validation solutions, such as HeadSpin, play a crucial role in elevating user experience and engagement. With HeadSpin’s cloud-based testing platform, QA teams can assess application performance under varied network conditions. By leveraging these capabilities, OTT platforms can proactively identify and resolve network-related issues, improve response rates, minimize interruptions and optimize user engagement.

Impact on Customer Retention & Revenue

Reducing churn rates and maximizing revenue are key priorities for OTT businesses.

Research by Conviva found that OTT platforms with excellent QoE experienced a 7.6% increase in viewing hours and a 4.3% growth in advertising impressions.

QoE validation solutions like MOZARK’s end-to-end video testing solution help platforms detect video quality degradation and buffering incidents, enabling them to optimize their content delivery infrastructure. By leveraging MOZARK’s data insights, OTT platforms can boost customer retention, reduce churn rates and drive revenue growth by delivering seamless and immersive viewing experience.

Driving Brand Loyalty & Advocacy

Brand loyalty and advocacy are essential for the long-term success of OTT platforms.

A research study by Brightcove states that 48% of consumers are more likely to remain loyal to platforms providing a better streaming experience.

Witbe, with its comprehensive analytics and monitoring capabilities, enables OTT platforms to deliver exceptional user experiences, fostering customer trust and brand loyalty. By consistently upgrading functionality backed by Witbe, platforms can solidify their position as industry leaders and build a strong community of loyal users who advocate for their brand.

Leveraging QoE Insights for Business Strategy

The insights provided by QoE validation solutions empower OTT platforms to make data-driven decisions and shape business strategies.

According to Conviva’s State of Streaming report, OTT platforms with excellent QoE experienced a 4.3% growth in advertising impressions.

GameBench, with its performance testing capabilities, allows testing teams to measure metrics such as frame rates and latency, ensuring smooth streaming experiences across different devices. By leveraging GameBench’s insights, platforms can optimize content delivery, identify areas for improvement and provide a superior QoE, giving them a competitive edge in the OTT landscape.

Context-Aware Experience: The Key to QoE on OTT Across Devices

To truly elevate the Quality of Experience (QoE) for OTT users, context-aware experiences play a pivotal role in meeting their preferences and expectations across various devices.

According to Ericsson ConsumerLab, 73% of viewers prefer personalized content recommendations.

Whether users are accessing content through mobile devices, web browsers, smart TVs, or wearables, tailoring watch experience to their specific contexts becomes essential. For instance, recommending local news in the morning or offering binge-worthy series during weekends enhances user satisfaction and increases user engagement. The ability to seamlessly continue watching from where the user left off on another device ensures a consistent and immersive experience.

Conclusion

QoE validation solutions like Witbe, HeadSpin, MOZARK and GameBench play a pivotal role in driving OTT excellence. By integrating these solutions into their workflows, OTT platforms can ensure seamless content delivery, optimize user satisfaction and engagement and drive customer loyalty.

Leveraging the comprehensive analytics, monitoring and testing capabilities of these solutions, platforms can deliver exceptional QoE, solidify brand reputation and thrive in the competitive OTT landscape.

At IGS, our specialization in quality engineering for OTT platforms brings a unique focus on the humane aspects of quality. While automated testing is essential & benchmarking tools help us derive the metrics and insights required to provide recommendations for code optimization which eventually results in better app performance, we take a pragmatic approach by also considering the user’s perspective and experience.

This is achieved as part of a manual benchmarking activity wherein the actual QoE KPIs and related metrics are captured, compared and analyzed with competitor apps.

By integrating Generative AI and emphasizing Shift-Left procedures like Ambiguity Analysis and Developing Sharper Acceptance criteria and tests, we proactively identify potential defects and optimize the user experience. Our approach adds tremendous value by uncovering issues before they impact users, enhancing customer satisfaction and reducing churn rates. With our expertise and deep industry knowledge, we provide tailored quality engineering services that prioritize user-centricity.

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The Role of API Testing in Open Banking

Evaluating the Quality of Chatbots and Intelligent Conversational Agents

Evaluating the Quality of Chatbots and Intelligent Conversational Agents

Author – Aparajita Tiwari (Program Manager)

Businesses require efficient chatbots and intelligent conversational agents in order to enhance customer experience and upscale their business. Many times, there is a struggle in building intelligent chatbots that can comprehend user intent and respond accordingly. Here is a list of various methods, processes, and tools that can be used by businesses in analyzing and enhancing the quality of chatbots and conversational AI.

Introduction:

Chatbots and conversational AI agents are being used by businesses to simulate human-like conversations with their customers using voice or text. The use of intelligent conversational agents reduces the burden on employees and negates the chances of an unpleasant customer experience. It is important for conversational ai chatbots to be emotionally intelligent to enhance customer experience and upscale business. This is where testing of conversational ai chatbots comes into the picture. They are mostly used in virtual assistance and can be improved by companies using artificial intelligence (AI) and machine learning.

Difference Between a Traditional Chatbot and Conversational Chatbot:

Businesses require efficient chatbots and intelligent conversational agents in order to enhance customer experience and upscale their business. Many times, there is a struggle in building intelligent chatbots that can comprehend user intent and respond accordingly. Here is a list of various methods, processes, and tools that can be used by businesses in analyzing and enhancing the quality of chatbots and conversational AI.

 

Chatbots and conversational AI are terms often used interchangeably. Chatbots are computer programs designed using natural language input to simulate human-like conversations with users in the form of text or voice, especially over the internet. They are rule-based, that is, chatbots are trained to answer only a specific set of questions, such as FAQs. Conversational AI agents, on the other hand, are smarter than chatbots as they use artificial intelligence and machine learning to make chatbots more capable of human conversations. They are more efficient at spotting patterns and making recommendations. Hence, chatbots require conversational AI to become smarter and more powerful.

Important Benefits of integrating AI Conversational Agents into your business:

Customer service chats and commercial social media interactions in businesses are increasingly being managed by intelligent conversational agents. Businesses can tackle customer interactions with accuracy by incorporating quality chatbots. A conversational AI chatbot can be designed through AI and machine learning to be emotionally intelligent and relevant to local culture. Some key benefits of using conversational bots in businesses are:

 

Why is Quality Evaluation of Conversational AI Important:

Conversational AI chatbots become an interface for businesses through which they interact with end users. It is important that these conversational agents understand the context of conversations and are sentimental so as to provide customer satisfaction. An emotionally intelligent chatbot forms stronger relationships with people.

How to test emotionally intelligent chatbots:

Integrating AI with emotional intelligence (EI) enables intelligent conversational agents to detect emotions in conversations and respond to them accordingly. While machine learning algorithms are used to make classifications or predictions, Testing conversational ai chatbots for EI can be done on the basis of input data, such as a questionnaire for shopping assistance and analyzing the accuracy and sensibility of the answers generated. A quality conversational bot will integrate AI and machine learning to detect the pattern of the conversation and make effective recommendations accordingly.

Quality Metrics of Conversational AI and AI Chatbot:

To maximize the potential of your chatbots and conversational AI, you will need to measure their performance. The following metrics can be used to measure the quality of chatbots:

Conversational AI agents are chatbots made more accurate and intelligent using AI and machine learning. The following metrics can be used to measure the quality of Conversational AI:

Phases of testing a chatbot:

Chatbot testing is complex and does not have a one-size-fits-all approach. Successful chatbot testing is done in two phases:

Methods of Testing a chatbot:

Chatbot testing is done by creating all possible scenarios that can take place in the conversation with the user. It is different from traditional software or mobile app testing as there is no predefined data to run through the chatbot analytics. Methods of chatbot testing are as follows:

Conversational Design testing:

This method uses tools to understand the basic user input and intent and verify the chatbot on conversation flow, intent, response, casual talk, fallback, navigation, and emotions. It tests the chatbot for the tonality of the conversation, such as positive responses, negative responses and expressions. It checks how the bot improves user experience through casual conversations and its efficiency to answer irrelevant questions in between a conversation. It creates chatbot testing scenarios for navigational cases, such as the user wanting to skip the conversation and cancel the order, and sees whether the chatbot can handle such cases. It also checks whether the chatbot is trained to understand emotions, such as happiness, anger, sadness, etc., and is able to respond accordingly.

Entities testing:

This uses entities or keywords from training phrases to check the efficiency of chatbots. In this process, the bot requests information to fulfill the user’s request. The data is used to fetch relevant information and the results are then shared with the user as a response. User acceptance testing is important to ensure the chatbot’s quality. Testing the chatbot with a number of users vastly improves the quality of the chatbot.

Tools to test the quality of a chatbot

Some of the key tools to test the quality of a chatbot are as follows:

Process of Testing an AI Chatbot:

The following process can be used in testing conversational AI chatbots:

Chatbot testing is done by creating all possible scenarios that can take place in the conversation with the user. It is different from traditional software or mobile app testing as there is no predefined data to run through the chatbot analytics. Methods of chatbot testing are as follows:

Tools to Test the Quality of a Conversational AI Chatbot:

Some of the conversational AI chatbots testing tools are:

How Conversation AI Works in AI Chatbot?

Conversational AI in AI chatbots uses deep learning algorithms and part of machine learning techniques, to imitate human responses and handle user queries. They learn from real interactions and can be trained easily using historical data. They respond to each question based on their understanding and learning acquired through the machine learning engine.

Conclusion

The quality of an AI chatbot boils down to its accuracy, precision, sensibility and specificity. AI Conversational bots are a faster way of conversing with customers and deliver greater customer satisfaction. Their ability to understand conversations outside pre-programmed commands and easily hold engaging conversations with customers are the reasons why their use in the business landscape is increasing rapidly.

 

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The Role of API Testing in Open Banking

Growth Mindset- Business growth factor

Growth Mindset- Business growth factor

Author – Naveen Belavadi (CEO)

To keep up with the fast-moving business world, organizations have to adapt to latest trends, technology and processes. Businesses that fail to embrace change will fall behind competitors and lose business opportunities.

Changes within an organisation result in numerous positive outcomes, including better business opportunities, improved processes, higher functioning teams and increased creativity. However, organisational change cannot be achieved overnight and even faces employee resistance.

 

Did you know?

According to report, 70% of change programs fail to meet their objectives and reasons behind it are employees’ resistance to change, lack of resources, budget and managerial support.

 The longer a process/technology has been in an organization, the more invested people are in it, which restricts them from adapting to changes. This type of mindset is addressed as fixed mindset. On contrary, growth mindset encourages individuals to take failure as a lesson, learn from it, and grow from it.

Mindset matters. Let’s understand how.

Carol Dweck, a Stanford University researcher, was the first to address fixed and growth mindset ideologies. According to her, people with a fixed mindset consider their intelligence is static. While those with a growth mindset believe talent, creativity and intelligence have no limits and can improve by working on them.

Everyone can grow in growth mindset, while fixed mindsets imprison your creativity.”

According to research, an employee working in an organisation with a growth mindset is:

Growth Mind strategy

  • 47% more likely to trust on colleagues
  • 34% more likely to take ownership of task
  • 49% more likely to agree that their company promotes innovation

Let’s understand the effectiveness of growth mindset within an organization.

A growth mindset encourages employees to challenge their thought processes and help achieve full potential through improved creativity, effective teamwork and increased productivity.

How does a growth mindset among employees help organisations grow?

Growth mindset can transform a stagnant workplace into a place for innovation. Employees within a growth mindset organisation accept challenges, learn from them and keep improving. One of the best examples of how growth mindset can bring massive success to an organization is Microsoft’s transition after Satya Nadella took over as CEO. He worked on the rigid hierarchical company structure and developed a company culture based on growth mindset, cooperation, learning and adaptability toward technological advancements envisioned by him.

Let’s look at the benefits of growth mindset in organizations.

  • Aligns skilled professionals to achieve team goals.
  • Encourages employees to upskill
  • Nurtures creativity and improves productivity

How do you develop growth mindset within an organization?

To develop growth mindset within an organization, we must

Learn together

Upskilling employees makes them adaptable to technology shifts, improves employee engagement and enables them to effectively handle their responsibilities. When people learn together, they tend to learn faster. Group learning also builds trust among employees and results in teamwork.

Open communication culture

Open communication between the management and employees resolves the problems/hurdles employees face and develop growth mindset within the workforce.

Embrace change

People with fixed mindsets are not open to changes and avoid taking risks as they can reveal their inadequacy. Embracing change is the key to success. Organizations aiming to grow must develop growth mindset within the workforce, which not only creates a tendency to believe they can grow but also consider hurdles as opportunities to learn.

Teams with growth mindset do not worry about looking smart but work towards bettering themselves. It is the attitude of constant learning and evolving. Not only this, agility introduced into business processes by growth mindset continuously improves interpersonal and technical skills and helps employees grow as a whole.

Knowledge Sharing and Training Mentees

It is proven that the most effective way to retain and utilize a new learning is by sharing the knowledge and training new team members on the same concept. As per the Learning pyramid, the highest retention rate of a knowledge or a skill occurs when you tutor others on the same. Therefore, two derivatives of the Learning pyramid for an organization to succeed is, for mentors to constantly acquire new knowledge and also impart or disseminate the same to the mentees. This not only allows the curation on new skill and knowledge, but also develop immense mutual respect and admiration towards each other. That is a classic recipe for establishing trust worthy teams.

Knowledge Sharing

 

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The Role of API Testing in Open Banking

Growth Triangle | Trust, Quality and Skills

Growth Triangle | Trust, Quality and Skills

Author – Nitin Mittal (VP of Sales) 

In today’s digital market, businesses are continually scaling their offerings portfolio and essentially realigning their internal organisational structure with strong emphasis on core principles like trust, skills, and quality of delivery. When an organisation has its workforce aligned towards delivering quality outcomes, it becomes trustworthy inside-out for both employees and clients.

To ensure delivery excellence for customers, attribute that weighs most is skills amongst workforce. Skilled professionals are true assets to organisations and perform major roles in project delivery, customer retention and acquisition.

Aligning skilled professionals towards the team goals is essential to achieve delivery excellence. Having skilled team members unchanneled is like 2 strong horses pulling a cart in opposite directions. The cart can only progress if both horses pull it in a same direction.

working together builds' productivity

When skilled professionals work as a team, they learn about each other’s strengths and weaknesses and work with an agenda of complimenting each other, thereby developing confidence among themselves. Team members begin relying on each other’s ability to deliver, which creates a work culture built on trust. Additionally, confidence in team also encourages upskilling, leading to improved performance and productivity of personnel. As a result, within a team of professionals, everybody grows as an individual. Consequently, faith among skilled professionals within an organisation yields premium quality products or services.

When business outcomes are channelled towards excellence in delivery, it effortlessly cultivates customers’ trust in the business. Resulting in trust within the organisation and in customers.

“According to statistics, around 72-73% of consumers say a good experience is key in inducing their brand loyalty.”

Quality work is initiated by commitment and a positive mindset towards completing tasks to the best of your abilities. When team constantly acquires new skills, they inspire each other and constantly push themselves towards levelling up their skills. It not only improves quality of work but also induces trust in the brand. Moreover, a team comprised of skilled professionals with a vision of achieving a common business objective gains confidence and works effectively without supervision from leaders, which is one of the greatest benefits of working as a team.

In this competitive market world, success of a business is dependent on work culture, internal organisational structure and employees’ skillsets. That is why organisations are constantly expanding their offering portfolios and focusing on realigning their organisational structure and core principles around delivery excellence.

 

 

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The Role of API Testing in Open Banking

How 5G and Edge Computing technologies are transcending Telco and OTT domains?

How 5G and Edge Computing technologies are transcending Telco and OTT domains?

Authors – Abhilash Suryanarayan (OTT Practice Lead), Shekar Dongdi (Test Manager)

 

The advancement in mobile internet through introduction of 5G, has laid a strong platform for Telecommunication companies to expand their customer base by infringing into various other domains like – OTT, BFSI, Fintech, E-commerce, and other domains. Currently, Telcos and OTT platforms partner with each other for a mutually beneficial monetization channel. Additionally, Telco gets the advantage over OTT’s massive content streaming globally, resulting in massive data consumption. Similarly, OTTs get the access to Telco’s huge user base, which radically decreases OTT’s user acquisition costs. This way, Telcos are meeting their growth in customer base, while OTTS are benefiting through monetizing their VOD contents with the reach ISPs have.

Consequently, for stable content streaming on cellular networks, high quality streaming is needed, which is seldom met while watching movies or longer format of contents. With 5G, users will rejoice high-quality streaming on their cellular network. Speaking of Telco, it is not always about mobile internet. Broadband also plays its part. Hence, even in broadband service, similar partnerships are being seen.

This blog addresses telco crossovers into OTTs and how advent of 5G will disrupt OTT’s Platform architecture soon and reason behind the disruption and how this may occur. Historically, Telcos have been steadfast on Quality of service, while OTTs are driving to push Quality of Experience. However, OTTs have realized Quality of Service also plays a key role in enhancing customer experience. Telcos lacked sufficient levels in Quality of Service (QoS) for offering a higher Quality of Experience (QoE) as they were ineffective on ways to improve their QoS to support an OTT use case. In this case, QoE in most common term refers to unbuffered streaming, which is directly proportional to the content playback experience or QOE.

This advent therefore is suspected to build a bridge across the pure-play CDN (Content Distribution Network) providers, meaning CDNs who were responsible to bring QoE to end users will now be threatened for business value with both Telco and OTT operators. So far, CDN’s have capitalized on the opportunity to become the liaison between the two domains Telco and OTT.

Let’s understand how CDN’s are behaving as intermediary between TELCO and OTT?

telecom testingIn the digital entertainment world, QoE is directly proportional to unbuffered streaming and other factors, but for sake of this discussion, lets focus on seamless viewing experience. OTT players lose  memberships when there is a lack in QoE. Similarly, drop in OTT  subscriptions causes dip in data traffic affecting business for Telcos. Since  unbuffered streaming is one of the critical factors for customer retention and  acquisition; CDNs are planting local servers for content distribution  globally and are using large size caching to store content regionally and  hyper locally to reduce buffering by avoiding round-trip transit to the content  server. Thereby acting as a catalyst for streaming experience.CDN’s are QoE brokers for OTT’s and play the role of market disrupters, who have pushed users to increase data and content usage. Within this ecosystem, CDN’s have become the main influencers and profit earners, as their involvement has been largely in providing local servers. They also address the Security aspects and function as Shock-absorbers for the OTT Content servers.

Since Telcos follow a content aggregator model, they do not offer original contents, but only aggregate them from different OTT providers. For instance, Vi Movies & TV, Airtel TV+ and Airtel Xstream have content from ZEE, Voot, Netflix, and other OTTs. OTT companies tunnel visioned on developing their own digital applications and contents, they too are transitioning into a content aggregation model as it has proven to be an alternate/additional monetization channel to sustain users and revenues.

Live streaming, which is one of the most popular among audiences, has 10 times longer viewership than VOD content. Consequently, it faces challenges related to quality streaming owing to consistency of network bandwidth and network coverage. CDNs help offload the excess workload from the origin servers to the network. Meanwhile it takes a lot of computing power for a single server to respond to requests, and even more so for video live streaming, CDNs protect the source servers from overload and keep it operational. With CDN adaptation, it becomes much more scalable, along with stream quality and performance improvements.

Drilling into Content Aggregation business model for Telcos

This was initially implemented by Telcos to monetize the data consumption on their network. They achieved this by accumulating contents from numerous OTTs, developing a Reco-engine, which understood user behaviour and suggested content best to match respective interests of its userbase. Now, OTTs realized they could benefit partnering with Telcos as they would be able to use the Reco-engine and promote their contents without much effort. Additionally, they could use Telcos 5G infrastructure and Edge computing technologies to enhance their QoE to their end users with a mission of increasing user acquisition without having core dependency on a CDN. CDN’s will now be more of an assist than an impact in a 5G ecosystem.

Some Insights
  • India’s 5G subscriptions are expected to reach around 350 million by 2026.
  • 5G telecom networks are expected to power up to 2% of India’s GDP which is around $180 billion by 2030.
Overview on how 5G and Edge Computing technologies are transcending Telco and OTT domains

5G networks use high-frequency bands, enabling faster data transmission between cell sites and user devices. 5G data rates are ideally expected to hit around 10 GB/s, which is 100 times faster than 4G LTE networks. CDN’s have been using the 5G technology and using them in setting up their hardware environment to cater to 5G. Virtualizing this hardware, we enter the world of Edge computing. Edge computing minimizes network distance between client and server by bringing computation to network. On implementing Edge Computing, contents can be cached on user’s device by using its computational capabilities to leverage network’s computing powers to ensure a better QoE to customers. As network infrastructure capability evolves and telcos build higher computational capability into their sim cards, the device industry will undergo an upgrade. Today people relay more than their smart phones than their laptops or computers as they have equivalent or greater computational power, both graphically and in terms of performance. Similarly, Telcos are upgrading their SIM cards to have higher computational capabilities, so a layer of processing can happen on client side as well. The combination of 5G and Edge Computing paves way to a higher network processing speeds and lower latency rates resulting in greater QoE and QoS.

According to survey, India is expected to become the fastest-growing telco advertisement market with an annual growth rate of 11% between 2020-23.

5G technology is addressing issues with respect to QoS. As it uses frequency spectrum under 6 GHz. Though the 6 GHz bandwidth range is not a significant improvement over 4G, it does offer the flexibility needed for a seamless or reduced buffered viewing experience given the frequency spectrum in which the content streaming is available. Consumer offerings use frequency bands available at 28–40 GHz, with ability to fall back to 6 GHz bandwidth range where large distances are to be covered.

Predicting the future of Telco and OTT partnership

Companies using with CDNs, would head towards disruption by exploding the data consumption with ISPs in the next 5–10 years. OTT has always envisioned to function on CDN architecture, and this will now get a boost – CDS will now be optimally exploited for higher QoE by OTT platforms. Now, all OTTs will start looking at reducing the cost of ownership with pure-play boutique CDN player and consider having a bundled service engagement with a its B2B contracts with Telcos. Telcos themselves will contest with pure-play CDN infra players and this will be an interesting phase for us to watch the disruptions.

Government initiatives for Telco industry- The Future, what’s up with 6G?

In India’s 2022-23 Union Budget, Indian government has allocated US$ 11.11 billion to the Department of Telecommunication to develop 6G technology. It has also formed a Sixth-generation innovation group and is planning to develop 100 smart city projects, where IoT will play a vital role.

While worldwide CDNs have often been able to meet demand for VOD OTT services, live OTT streaming poses more complexities. Live OTT services are causing traffic surges that are so high that they can overload networks, which has put OTT industry at an inflection point. During popular sports events, millions of people simulcast the live streaming. In such a scenario, QoE issues, such as rebuffering and low streaming quality, can arise unless network operator has forecasted extra capacity for the peak audience load.

Did you know?

OTT 5g testingThe average traffic per smartphone in India was 18.4 GB per month in 2021 and is expected to grow to 50 GB per month by 2027.The added live OTT traffic directly results in higher network costs, needing the investment in network upgrades. According to global CDN figures, peak OTT traffic is expected to grow by 70–80% on a yearly basis. With 5G, consumer messaging will be focused on higher bandwidth and lower latency, which will make multitude of streaming videos available via internet. Without a huge capital outlay, anyone with a 5G connection can be a content originator, making it possible to content creators to access their markets with higher streaming quality than ever before.

Serverless architecture will be one of those things that will come up in the future and IGS’s quality engineering perspective is all set to adapt to it. A lot of analytics will be direct to ISPs because they have richer access to analytics than a CDN. Since CDN market is fragmented, looking at Telco network, they are aggregated and are directly available to the users. Let’s not forget that they have international tie-ups in terms of roaming. Hence, there is Telco aggregation happening and therefore, global data availability in terms of data analytics is much higher than a pure-play CDN player.

The total revenue generated by mobile operators in 2021 was around 1.08 trillion US dollars and within 2025, it is expected to increase by a whopping amount – 100 billion US dollars.

From IGS perspective, we are registering these changes today and getting ready for the future, in terms of how we can put up an engineering aspect to quality, when a CDN switches from being a core to an assist mode in the 5G evolution. Our Digital Assurance lab is already procuring 5G ready and 5G inventory to enable the transformation and shifts. From testing point of view, we are realigning our engineering strategies to address these changes. We are factoring in the impacts around these towards our Effort Estimation algos and utilities developed to confirm the QoE for our OTT customers. Our entire reusability test suite for context aware transactions, Casting, Muti-device Registrations, QoE on tethered connections and Gamified feature with respect to OTTs has been reimagined and recalibrated test cases where necessary.

IGS with its vision to be future-proof and being ready to accept the advent of 5G is an intriguing case of modernization for us in OTT practice.

Stay tuned for more insights on the evolving QE adjustments, with 5G playing a significant role in OTT big bang.

 

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