This article has been contributed by Muddassar Nazar, CEO, Birla Brainiacs.
Education is the foundation of human progress since it fosters intelligence and imparts skills that last a lifetime. However, students often struggle with a range of interest and comprehension levels when taught using the typical one-size-fits-all strategy. If the subject isn’t engaging enough for them to study using the way they like, they can lose interest in it. This presents a challenge for educators who wish to offer inclusive, dynamic curricula. Because of this, Artificial Intelligence (AI) has become a disruptive force that is changing education by designing individualised learning paths for students based on their learning preferences.
Education is no longer limited to physical presence, textbooks, and classroom walls. The recognition of AI’s potential by educational institutions has led to a wealth of digitally enhanced learning resources for both professors and students. In addition to offering engaging teaching methods and dynamic learning possibilities, these tools promote holistic growth and development. According to a Certified Market Research analysis, the growing integration of artificial intelligence (AI) into education technology is expected to propel the global market for AI in education to a compound annual growth rate (CAGR) of 45.21%, reaching $21.52 billion by 2028.
Beyond doubts, AI in education has evolved from a fad to a need, enabling students to customise their learning and progress at their own pace. Personalised learning pathways may now be created thanks to artificial intelligence and individualised learning, which adapts learning opportunities to meet the needs of each learner. AI enables educators to differentiate instruction by providing them with the knowledge about each student’s strengths and limits. Instructors may tailor learning experiences to each student’s specific requirements, interests, and learning preferences by integrating AI technologies.
Analyse further how AI may enhance students’ tailored classroom experiences according to their learning preferences:
The Emergence of Adaptive Learning
In India, AI-powered systems for adaptive learning are gaining traction. Based on each student’s success, these platforms modify the assignments’ and questions’ level of difficulty. These adaptive learning systems driven by artificial intelligence (AI) look at student data such as performance, areas of strength and weakness, and learning pace. Based on this information, the system may design a customised learning path for each student that includes resources, exercises, and content tailored to their individual needs.
Driven by information Insights
The fact that AI considers a variety of learning contexts, such as logical, visual, and aural preferences, is not surprising. Beyond learning preferences, AI continuously collects and evaluates data to provide teachers with information about the progress of their students. Because of this, educators can make significant inferences from this data to comprehend each student on a deeper level. They can then utilise these inferences to decide how best to customise their students’ educational experiences. This is made possible by artificial intelligence-driven analytics.
Using intelligent teaching systems is one creative method Edtech is leveraging AI. By employing machine learning (ML) algorithms to adjust content based on student performance, these systems offer personalised learning. This approach meets a variety of learning demands, boosts engagement, and offers real-time feedback to create an interactive and personalised learning environment.
Personalised Learning Strategies
AI-driven systems offer students customised learning opportunities depending on their goals, interests, and prior knowledge. Through curriculum and speed adjustments based on student needs, these systems ensure that students receive the appropriate support and challenges to optimise their learning outcomes. While AI holds great potential, human educators remain crucial in creating supportive and inspiring learning environments. Artificial intelligence and human knowledge combined could lead to more effective and personalised training for each student.
Transcend Mainstream Teaching
There’s no reason to believe that artificial intelligence (AI) will stop permeating education. Thanks to modern technology, education can now be streamlined and made more interesting and personalized for both students and teachers. The era of AI-driven personalised learning has also come, drastically altering how pupils learn and how professors instruct them. Thus, the coming together of technology and education heralds a brighter future where each student’s unique skills are developed, leading to all-around development and outstanding accomplishments.
This article has been contributed by Mr. Lokesh Nigam, Co-Founder and CEO, Konverz.ai.
The advent of Artificial Intelligence (AI) has prompted diversified sectors to approach their operations differently and optimize processes, thus improving efficiency and modifying people`s experience with technology. Out of all the sectors that were affected, HR is what stood out as the leading beneficiary of this technological transformation. AI is no longer just a trend in HR, it has taken on the role of a strategic partner in managing human resources. AI is altering the Human Resources (HR) process whereby it (a) automates routine administrative jobs and (b) assists in delivering customized employee services. The power of AI has been extensively applied, like the use of intelligent algorithms for the HR recruitment task. Whether it’s sifting through numerous resumes to pick the best one, reducing bias in hiring decisions or predicting employee success, AI uncovers uncharted waters in talent acquisition. It is not a fad but rather a paradigm shift, which will lead to the next level of human interrelations with organizations.
The development of AI technologies is also moving forward hand in hand with the advancements in the recruiting arena, and AI tools are increasingly becoming essential software products that help organizations manage the complexity of human resources issues in the highly competitive job market. In line with the 2021 SHRM report, 88% of companies across the world are already utilizing AI in one way or another within their HRDs, driving demands for the widespread adoption of the technology. These AI systems perform this function by analyzing a large volume of data, discovering hidden patterns that human recruiters might overlook, and automating many recruitment tasks from posting job adverts to finalizing hire decisions.
AI introduces an opportunity to hold an engaging and transparent selection procedure for the candidates. Through chatbots and AI-driven platforms that interact in real time, candidates can communicate with potential employers, respond to questions, and receive instant feedback. Some transparency tools, including showing candidates whether and how their data is being used in algorithmic decision-making, may act as a guide that can help them understand how a resume is evaluated. Google is well-known for its innovation and AI technology application in different fields, and it has also designed another AI-based resume screening technology called the Cloud Talent Solution. An AI system properly trained to scan resumes, pull out keywords, assign scores, and conduct interviews are among the technical tools human resources can rely on.
Enhancing Accuracy, Efficiency, and Cost Savings
AI offers recruiters the means to take the accuracy, efficiency, and cost-effectiveness of the hiring process to new heights. Automated tools possess the capability to objectively collect a vast amount of data and make evaluations by virtue of certain criteria. For example, you may have embarked on writing job descriptions, in which case there are tools that can do it in less than 30 seconds, saving you time and effort. Furthermore, predictive analytics can tangent a sorting line of the chance of the success of a candidate in the position, this is how hiring risks are minimized. Such innovations facilitate huge time and cost cuts that result in a more accelerated and proactive process of recruiting.
Optimizing Recruitment Processes
Utilization of AI makes it possible for companies to effectively optimize different areas of recruitment, from creating job descriptions, screening CVs, and predicting the success rate of a person in a particular area of the organization, to onboarding as well. Through this optimization, the hiring process is made more streamlined, and a better match between candidate skills and an organization’s requirements is achieved, hence leading to more good placements and in turn a cohesive workforce as a result. AI-assisted algorithms can better explore the application process of job postings with higher retention and effectiveness by creating more appealing and dynamic job postings. For instance, the adoption of AI in candidate selection in the form of a chatbot that can deal with candidates, if they need any career guidance and recommendations based on their CVs, knowledge, profile, and goals. The AI bot will help candidates in making a better and well-informed decision while learning more about the company’s culture.
Diversifying the Talent Pool and Reducing Bias
A very important thing companies are putting their efforts into now is having a diverse workforce. With the help of AI, it is possible for them to find the right talent that surpasses their current abilities and form an unbiased hiring process. Through data analytics and machine learning, AI tends to discover candidates from multiple backgrounds and the ones having different skill sets. Take McKinsey & Company as another example of the company’s drive to use AI to pinpoint and insist that tech candidates are brought in from diverse educational and to-life backgrounds. In addition, AI algorithms can be customized to cut off factors that can result in biased hiring decisions, hence enhancing the fairness of the hiring process. AI’s application in this way shows that the company is placing a high priority on both inclusion and fairness in the recruitment industry.
The AI-Infused Future of Recruitment
Moving forward, recognizing limitations, ensuring ethical counseling, and welcoming, the changing patterns will shape the future for talent acquisition. According to a study by Deloitte, 67% of people working in recruitment think that with the help of AI, their work will be more effective. Utilizing an unbiased approach and addressing the issue of fairness, transparency, and diversity in the selection process is among the key priorities of AI integration as this will only improve the decision-making process. The combination of AI-aided recruitment with more extensive systems of human resources will make talent management operations seamless, as organizations will use AI-driven intelligence in different stages of the employee lifecycle. With the changing face of HR functions, they will become a vital driver of strategic recruitment, analytics, and ethical use of AI as well. AI-driven recruitment is not meant as a mere advancement in technology but as a fundamental change in how organizations identify and engage with their talent. Success in the AI era means strong ethics in the recruitment process, continuous learning, and a strategic vision for AI utilization. With the digital revolution continuously redefining the HR landscape, the principles of fairness, transparency, and inclusivity should guide the formation of AI-fuelled recruitment strategies.
This article has been contributed by Jaepy Kurian, Head of Delivery, India, Orion Innovation.
Advanced technologies such as Artificial Intelligence (AI) and Cloud Computing are transforming businesses globally. Being an early adopter offers significant advantages, and startups have the key opportunity to ride this wave of digital innovation or be left behind. However, integrating new technology is not always a straightforward process. To effectively drive value for your business, it’s crucial to be aware of the complexities, opportunities, and practical strategies involved.
AI & Cloud Offer a Wealth of Opportunities for Innovation
AI, which refers to various machines or software capable of intelligent behavior, is garnering attention across various industries. It involves various techniques, models, and tools to help businesses automate tasks, predict outcomes, and optimize processes. In India, the AI market is growing fast, mirroring global growth rates, and is expected to reach $17 billion USD by 20271. With its ability to enhance decision making, personalize experiences, and generate unique content, AI has attracted investments totaling $4 billion USD in 2022-2023 alone.
Cloud technology plays a significant role in the rise of AI and other cutting-edge technologies. As businesses navigate the complexities of AI adoption, the cloud will serve as a catalyst for agility and cost efficiency. Cloud computing involves delivering computing services over the internet, providing on-demand access to a shared pool of configurable resources such as servers, storage, and applications. It offers a cost-effective alternative to traditional, and often expensive, IT infrastructure. Without the need to own and maintain physical hardware, businesses can bring down both operating expenses and maintenance costs.
Besides cost efficiency, the cloud also allows businesses to scale resources dynamically and enable easier disaster recovery and maintenance. There is a clear need for increased efficiency across industries, and the cloud does wonders for productivity and collaboration, allowing teams to collaborate seamlessly on cloud-based tools from different parts of the world. Additionally, by leveraging reputable cloud providers, businesses benefit from improved security guardrails and enhanced protection against cyberattacks and breaches.
Biggest Barriers to Adoption
Both cloud and AI offer the potential to drive transformative initiatives across industries. Having said that, any organization looking to implement these cutting-edge technologies should consider whether they have the capabilities, skills, and even the opportunities required for a successful adoption. By addressing the most common barriers, startups can determine the right level of investment and balance out their priorities.
One of the primary challenges businesses face in AI adoption is the cost factor. Integrating AI into existing operations requires investment in expensive tools, technology infrastructure, talent acquisition, and ongoing maintenance. Perhaps the second biggest barrier is the availability of the right talent and people. Finding skilled AI professionals remains a daunting task, given the high demand for talent in this field. Notably, India is the 2nd largest AI talent base, with 4.16 lakh professionals working in various AI job functions.
Ensuring the fairness and transparency of AI algorithms is also crucial to building trust with customers and stakeholders. Biases inherent in AI models can lead to unintended consequences, such as discriminatory outcomes, hallucinations, or inaccurate predictions. Given the rise in Generative AI, verifying the accuracy of AI-generated content, images, videos, and code is essential. Additionally, because of the massive amounts of data involved in AI initiatives, adoption can also bring about several concerns in data security and privacy.
Cloud adoption presents a similar set of challenges. Security concerns, such as data breaches, improper configurations, and unauthorized access, remain top priorities for businesses transitioning to the cloud. Finding qualified personnel is also a barrier. Building and maintaining cloud systems require specialized skills that may be in short supply. And for both AI and cloud adoption, compliance with industry regulations and data protection laws adds another layer of complexity. Businesses must ensure that their AI algorithms and cloud infrastructure comply with relevant regulations governing data handling, privacy, and security.
Adopting cloud technology can also present challenges with vendor lock-in. Relying on a single cloud provider may limit flexibility, scalability, and innovation and lead startups to favor open-source or multi-cloud solutions instead. It’s also important to consider connectivity in India. Reliable high-speed internet access may be hard to come by in rural areas, impacting the value cloud technology provides.
Cloud App Market Size from 2015 to 2022
Strategies for Successful Adoption
Despite these challenges, startups can overcome hurdles in AI and cloud adoption through strategic planning and proactive measures. Investing in talent development programs and partnering with academic institutions can help build a pipeline of skilled AI professionals. These programs may include internships, apprenticeships, and training initiatives tailored to equip employees with the necessary knowledge and expertise. Additionally, fostering a culture of innovation, risk-taking, and experimentation within the organization can encourage employees to embrace new technologies and explore creative solutions to business challenges.
When it comes to cloud adoption, startups should prioritize security and compliance from the outset. Conducting thorough risk assessments, implementing robust security controls, and staying informed about industry best practices can help mitigate security risks and build trust with customers and partners.
The Path Forward
Implementing cutting-edge technology such as AI and cloud comes with both opportunities and challenges. While these technologies offer opportunities for innovation, efficiency, and scalability, they also pose challenges such as data privacy concerns, talent gaps, and cybersecurity risks. By conducting thorough assessments and risk analyses, startups can develop strategies to maximize the benefits of AI and cloud adoption while mitigating potential risks. This holistic approach enables businesses to make informed decisions and navigate the complexities of digital transformation effectively.
This article has been contributed by Mr. Ameet Patil, Tech. Entrepreneur & Founder, CEO of Ecobillz Private Limited.
The Indian hospitality sector is poised for a transformative era driven by Artificial Intelligence (AI). This isn’t just about flashy gadgets or gimmicks; it’s about fundamentally reshaping guest experiences and operational efficiency. Fueled by significant capital flow, as evidenced by the rapid adoption of AI solutions, the Indian AI hospitality market is on track for immense growth. Industry reports predict a substantial rise in the global travel AI market, exceeding $1.2 billion by 2026, and this growth will undoubtedly be mirrored in India. As AI continues to evolve, we can expect even more transformative applications that will redefine guest experiences in the Indian hospitality sector.
However, at the heart of this transformation lies a symbiotic relationship, not a competition, between AI and human expertise. While AI excels at automating repetitive tasks, highly skilled staff remains essential for providing exceptional service and building genuine connections with guests. AI lacks emotional intelligence today, and human empathy is irreplaceable in the hospitality industry. The key lies in leveraging AI to empower staff to personalize the guest experience.
Hotels are moving away from static pricing models thanks to AI. AI systems analyze market trends, competitor pricing, and real-time guest booking patterns. This empowers hotels to leverage dynamic pricing strategies, adjusting rates to maximize revenue during peak seasons and remain competitive during slower periods.
Imagine a hotel anticipating equipment failures before they happen! AI-powered predictive maintenance makes this a reality. Sensors throughout the hotel feed data into AI systems, allowing them to predict potential issues and schedule maintenance proactively. This minimizes disruptions for guests and ensures a smooth stay.
Gone are the days of waiting in line for simple requests. AI-powered virtual assistants within guest rooms allow guests to control lighting and temperature, request amenities, and access information through voice commands. This not only empowers guests but also frees up valuable staff time for more complex guest interactions.
The future of hospitality lies in hyper-personalization. AI analyzes vast amounts of guest data, including past preferences, booking history, and online behavior. Imagine a smart chatbot remembering your coffee preference from a previous stay and suggesting local attractions based on your interests. This level of personalization creates a truly memorable experience for each guest.
Tailoring AI for the Indian Traveller
Understanding the distinct consumer approaches in the global and Indian hospitality markets is crucial for tailoring AI integration strategies. Here’s a breakdown of some key differences:
Value vs. Experience: Globally, travelers often prioritize value for money, seeking budget-friendly options and maximizing their travel budget. In India, however, the focus often shifts towards a holistic experience. Indian travelers are willing to spend more for unique experiences, personalized service, and a strong cultural connection.
Tech Savvy vs. Digital Divide: Globally, travelers are generally more tech-savvy and comfortable adopting new technologies. Sparing the young generation, India, however, faces a digital divide, with a significant portion of the population taking time to latch on to the digital. This necessitates a more nuanced approach to AI integration, with a focus on solutions that are accessible even to those who are less tech-savvy.
Familiarity vs. Novelty: Globally, travelers are often accustomed to a certain level of automation and technological integration in hotels. In India, AI solutions might be perceived as novelties. Here, the focus should be on educating guests about the benefits of AI and ensuring a seamless user experience.
Hospitaility Industry In India
AI Integration: A Strategy for the Indian Market
By understanding these consumer behavior differences, the Indian hospitality industry can leverage AI to cater to the specific needs of its guests:
Focus on Value-Added Services: AI can personalize room service menus based on guest preferences and dietary restrictions, optimizing value for money. Upselling and cross-selling strategies can also be personalized using AI, ensuring they enhance the guest experience rather than feeling intrusive.
Bridge the Digital Divide: Voice-controlled assistants can be a great solution for guests who are less comfortable with touch-screen interfaces. Additionally, offering offline access to key information through downloadable apps can ensure AI benefits all guests, regardless of their internet connectivity.
Prioritize Cultural Integration: AI can be used to curate itineraries and recommend local experiences that cater to the specific interests of Indian guests. Imagine a chatbot suggesting historical sites or cultural events based on a guest’s region of origin or preferred language.
Focus on Human-AI Collaboration: While AI automates tasks, skilled staff remains crucial for personalized service and cultural understanding. Training programs can equip staff to leverage AI effectively, allowing them to focus on building rapport with guests and addressing their unique needs.
The Road Ahead: A Symbiotic Future
By understanding the distinct needs of the Indian hospitality market and tailoring AI integration accordingly, the industry can unlock immense potential. AI can become a powerful tool for enhancing operational efficiency, personalizing guest experiences, and catering to the specific values and preferences of Indian travelers.
However, it’s crucial to remember that AI is not a replacement for human interaction. The future of Indian hospitality lies in a harmonious blend of AI and human touch. By focusing on training and development, hotels can ensure their staff possess the skills to interpret guest needs, handle complex situations, and provide that irreplaceable human touch.
This human-centric approach to AI integration will be the cornerstone of success in the future of Indian hospitality. This approach ensures that AI complements the strengths of the workforce, creating a future where technology seamlessly enhances the human touch that is so crucial in the Indian hospitality industry.
This article has been contributed by Abhinandan Jain, Chief Growth Officer, Startek.
Conversational AI, the technology powering chatbots and virtual assistants, is rapidly reshaping customer interactions. Imagine a tireless AI assistant, available 24/7, that personalizes the customer journey, answers questions with ease, and even streamlines lead generation. Studies show its potential – a report revealed that 67% of U.S. millennial internet users are more likely to purchase from brands using a chatbot. However, simply deploying a chatbot isn’t enough. Seamless integration with existing systems is crucial for a smooth user experience and maximizing the benefits of conversational AI.
This guide outlines the key steps to implementing conversational AI and achieving successful integration, ensuring a positive impact on your customer experience.
Before diving into development, clearly define your objectives for deploying conversational AI. Are you aiming to streamline customer service by deflecting simple inquiries to the AI assistant? Perhaps your goal is to boost lead generation by engaging website visitors with targeted product recommendations. Identifying these goals will shape the design and functionality of your virtual assistant, ensuring it tackles the specific challenges you face.
Next, get to know your target audience intimately. Who will be interacting with this AI assistant? Are they tech-savvy millennials comfortable with messaging apps, or a demographic who prefers traditional website chat interfaces? Understanding their demographics, preferred communication channels, and common pain points is crucial for tailoring the conversational experience to their needs. Conducting user research through surveys or focus groups can help you gather valuable insights into these aspects.
For instance, if your target audience primarily consists of older adults who are new to online shopping, your conversational AI should prioritize clear and concise language, avoiding technical jargon. It should also offer multiple communication channels, such as voice and text chat, to cater to different preferences.
Choosing the Right Conversational AI Platform
With a vast array of conversational AI platforms available, selecting the right one can be daunting. Here are some key factors to consider when evaluating your options:
Ease of Use: Consider the technical expertise within your team. Some platforms offer user-friendly interfaces with drag-and-drop functionalities, while others may require coding knowledge.
Scalability: Choose a platform that can scale up or down to meet your changing business needs. As your customer base grows, your conversational AI solution should be able to handle the increased volume of interactions.
Integration Capabilities: Ensure the platform seamlessly integrates with your existing CRM system, ticketing software, or other relevant tools for a holistic view of customer interactions. This allows the AI assistant to access relevant customer data and provide a more personalized experience.
Customization Options: Evaluate the level of customization offered by the platform. Some platforms provide pre-built templates, while others allow for more granular control over the look and feel of your AI assistant. Consider the level of customization needed to align the AI assistant with your brand identity.
Generative AI Model: Look for platforms that utilize effective generative AI models with pre-trained data sets for the specific languages your conversational AI will need to understand. These pre-trained models provide a strong foundation for your AI assistant’s ability to interpret and respond to user queries accurately.
By carefully considering these factors, you can choose a platform that aligns with your business requirements and technical capabilities.
Design a Seamless Conversational Experience
Crafting a natural and intuitive user experience is key to the success of your conversational AI solution. Here’s what to focus on:
Conversational Flow: Map out different user journeys, anticipating various scenarios and questions your users might encounter. Design the conversational flow to mimic natural human interactions and provide clear guidance throughout the interaction. This includes offering multiple response options, allowing users to clarify their intent, and providing easy navigation within the conversation.
Language, Tone, and Personality: Determine the personality you want your AI assistant to exude. Should it be friendly and informal, or professional and informative? Align the language and tone with your brand voice and target audience. For example, a brand targeting young adults might opt for a more casual and conversational tone, while a financial services company might choose a more professional and authoritative approach.
Natural Language Understanding (NLU): Utilize NLU capabilities to enhance the accuracy of user intent recognition. This ensures your AI assistant understands the underlying meaning of user queries, even when phrased in unconventional ways. Advanced NLU capabilities allow your AI assistant to handle variations in language, slang and colloquialisms, providing a more natural and engaging experience.
Sentiment Analysis: Integrate sentiment analysis to gauge user emotions during conversations. This allows your AI assistant to adapt its responses accordingly, providing a more empathetic and supportive experience. For instance, if a customer expresses frustration, the AI assistant can offer apologies, de-escalate the situation and connect them with a live agent for more complex issues.
Most Important Attribute Of The Customer Experience
Development, Deployment and Integration
Once you’ve designed your conversational experience, it’s time to develop and deploy your solution. Depending on your chosen platform, development might involve coding or utilizing visual interfaces. Thoroughly test your AI assistant to identify and address any bugs or functionality issues before deploying it live. Here are some additional considerations for a successful deployment:
Data Security: Ensure the platform adheres to industry standards for data security and privacy. Customer data entrusted to your conversational AI solution should be protected with appropriate safeguards.
Knowledge Base Development: Create a comprehensive knowledge base to train your AI assistant. This knowledge base should include frequently asked questions, product information, troubleshooting guides and any other relevant content your AI assistant might need to draw upon to answer user queries accurately.
Testing and Refinement: Continuously test and refine your AI assistant’s responses. Gather user feedback through surveys or in-app prompts to identify areas for improvement. Analyze conversation transcripts to identify recurring issues or misunderstandings and update your knowledge base and conversation flows accordingly.
Integration with Existing Systems
Integration with existing systems is crucial for maximizing the impact of your conversational AI. Here are some key integrations to consider:
CRM System Integration: Integrate your AI assistant with your CRM to access customer data and personalize interactions. This allows the AI assistant to provide relevant information and a more efficient resolution of customer inquiries. For example, if a customer inquires about a previous order, the AI assistant can access their order history within the CRM and provide them with the necessary details.
Ticketing System Integration: Connect your AI assistant with your ticketing system to streamline the process of creating and tracking support tickets. This eliminates the need for customers to repeat information and ensures seamless handoff to human agents when needed. When a customer encounters a complex issue beyond the AI assistant’s capabilities, it can automatically generate a support ticket and route it to the appropriate agent.
Payment Gateway Integration: Consider integrating with payment gateways to facilitate transactions directly through the chat window. This can enhance the customer experience by offering a quick and convenient way to complete purchases without leaving the chat interface.
Monitoring, Optimization and Continuous Improvement
The journey with conversational AI doesn’t end with deployment. Continuously monitor its performance through analytics tools, tracking key metrics such as user engagement, satisfaction and conversion rates. Analyze these metrics to identify areas for improvement and iterate on your conversational AI solution. Here are some ongoing considerations:
Performance Monitoring: Track key metrics to gauge the effectiveness of your AI assistant. Monitor user engagement rates, conversation completion rates, and identify areas where users are dropping off. Analyze these metrics to identify potential issues with the conversation flow or the AI assistant’s understanding of user intent.
User Feedback: Gather user feedback through surveys or in-app prompts to understand user sentiment and identify areas for improvement. Actively solicit feedback on the clarity, helpfulness and overall experience provided by the AI assistant.
Continuous Learning: Conversational AI is a constantly evolving field. Stay updated on advancements in natural language processing and machine learning to continuously improve your AI assistant’s capabilities. Regularly update your knowledge base with new information and refine your conversation flows based on user interactions and feedback.
Conclusion: The Future of Customer Experience
By following these steps and embracing a continuous improvement mindset, you can leverage conversational AI to its full potential. A well-integrated conversational AI system can become a valuable asset, transforming the way your business interacts with customers. It can streamline processes, personalize interactions, and ultimately lead to increased customer satisfaction and loyalty. As conversational AI technology continues to evolve, businesses that embrace it early and prioritize a seamless user experience will be well-positioned to thrive in the ever-changing customer landscape. Conversational AI has the potential to redefine customer experience, offering a more natural, efficient and personalized approach to customer interactions. By implementing conversational AI effectively, businesses can build stronger relationships with their customers and drive long-term success.
This article has been contributed by Jesintha Louis, CEO, G7 CR Technologies – A Noventiq Company.
The modern business world operates swiftly, and to survive and prosper, companies must enhance productivity, optimize efficiency, and enhance commercial results. It goes without saying that cloud computing and artificial intelligence have transformed technology. When integrated into processes, artificial intelligence (AI) delivers value and impact across all facets of a company, making it the new frontier in digital transformation. Complementing it, cloud computing allows businesses to focus on their core operations since it provides scalability, agility, and cost-effectiveness.
Businesses investing in AI-powered cloud solutions will be better positioned to lead the world economy in the future. These two powerful technologies are now combining to transform businesses and, eventually, our entire way of life. Cloud providers are using their own AI innovations to generate a range of benefits, including code production, supply chain predictability, cyber threat detection and response, and productivity in business functions.
Cloud services are being quickly transformed by AI. This potent duo has the capability to boost business development across industries. Here’s how AI can be integrated with cloud to transform services and accelerate business growth:
Long-term success in a company depends on smooth operations. The ability of artificial intelligence (AI) to identify patterns, optimize processes, and automate repetitive jobs is remarkable.
Resource management: Artificial intelligence algorithms can autonomously scale up or down cloud resources based on patterns of consumption. Avoiding overprovisioning and guaranteeing adequate capacity during peak workloads maximizes cloud spending.
Self-Healing Infrastructure: AI can anticipate problems in the cloud environment and take proactive measures to resolve them. As a result, downtime is reduced and ensures a seamless experience for users.
Automated Workflows: Artificial intelligence (AI) can automate repetitive processes like data processing, log analysis, and security monitoring, freeing up human resources for more strategic endeavors.
Data-Driven Decision Making
As artificial intelligence (AI) continues to advance, it is becoming a vital tool for decision-making across a range of sectors. While it might be intimidating for humans to analyze such large volumes of data, AI can do so with ease.
Predictive analytics: AI can foresee future results, discover patterns, and predict consumer behavior by analyzing massive volumes of cloud-based data. This makes it possible for companies to make data-driven decisions that reduce risks, enhance product development, and maximize marketing efforts.
Real-Time Insights: AI can interpret data in real-time from sensors and cloud apps, giving decision-makers immediate access to actionable information. This enables companies to respond swiftly to changing market conditions and customer needs.
Customized Customer Experiences
People’s loyalty is crucial for business success, and there is a constant demand to enhance and customize their interactions with these beloved businesses.
AI-powered chatbots: Companies may use AI-powered chatbots to tailor interactions based on client data, offer round-the-clock customer assistance, and respond to often requested queries. This lowers support expenses while raising client satisfaction.
Recommendation engines: AI can identify appropriate items or services by analyzing user activity patterns. This level of customization may result in more consumer engagement and sales.
Emerging Business Models & Innovation
Businesses in every industry are seeking different forms of advantages to stay one step ahead of the competition. Promoting innovation in goods, services, or business models is essential to achieving this.
Machine Learning as a Service (MLaaS): Pre-trained AI models and tools may be used by organizations without requiring a lot of in-house experience thanks to the growing availability of MLaaS from cloud platforms. This makes AI more accessible and creates new chances for innovation.
Creating AI-powered Apps: Organizations may quickly design and implement AI-powered apps that are customized to meet their unique requirements by utilizing cloud services. They can investigate new revenue streams and obtain a competitive advantage as a result.
With the use of sophisticated algorithms, businesses may save costs, improve production efficiency, and optimize inventory management.
Cost-Reduction Strategy: Cutting costs is a major objective of incorporating AI into many organizational functions and procedures. This is made possible by AI, which gives companies the ability to do more, do it better, and manage their cloud expenditures more effectively. Businesses may identify complex trends that impact revenue and customer experience with the aid of predictive AI. This has also allowed businesses to improve client experiences while saving a lot of money.
Cloud App Market Size 2015-2022
Enhanced Operational Efficiency
Organizations may increase workplace productivity by implementing operational effectiveness and efficiency, two essential elements of successful workplace models. Cloud solutions driven by AI can help organizations become more efficient in their operations.
Natural Language Processing (NLP): Cloud-based NLP services let organizations automate customer care procedures, extract insights from unstructured text data, and communicate with consumers in their chosen language. Examples of these services include sentiment analysis, language translation, and chatbots. Applications with NLP capabilities may increase consumer engagement, boost operational effectiveness, and provide individualized experiences on a large scale.
The combination of artificial intelligence with cloud computing signifies a paradigm change in how companies use technology to spur development and innovation. IT transformation is being driven by these two technologies, and when they work together, they improve business results. Through the utilization of AI-powered insights and cloud-based infrastructure, businesses can revolutionize their operations, enhance workflows, and open fresh avenues for expansion. The possibilities are boundless, ranging from computer vision and recommendation systems to natural language processing and predictive analytics. Cloud adoption will become simpler, quicker, and more economical with AI.
In addition to these fundamental advantages, AI models may be developed and implemented effectively and at a scale by utilizing the scalability, consistency, and elasticity of cloud computing. With abstraction layers used to conceal infrastructure complexity and streamline access, AI will also aid in improving consumability and portability by delivering a consistent experience and portability features across diverse contexts. Businesses may remain ahead of the curve, adjust to shifting market dynamics, and prosper in the future digital economy by embracing AI-powered cloud services.
This article has been contributed by Ms. Karunya Sampath, Co-founder & CEO of Payoda Technologies.
When it comes to artificial intelligence, there is always a fear of missing out. However, AI is here to stay. The notion of AI has expanded so much over time that you may already be using it in your organization without even realizing it!
A decade ago, software was considered intelligent if it could send reminders or provide monthly reports. Automating complex workflows and if-else functions was so astounding that we labelled it intelligent. How clever!
Nowadays, AI has now gone beyond that. This article will discuss AI tech stacks and how to use them strategically and efficiently for your business operations.
Understanding the AI Technology Stack for Your Business
Various technologies are used for specific goals, including information management, storage, processing, and intelligent algorithms. The AI tech stack categorizes them into layers for more straightforward perception. Your AI tech stack is a collection of technologies, frameworks, and tools that address various aspects of AI implementation, from data collection to deploying AI-powered products.
Your AI tech stack has three layers: application, model, and infrastructure. Let’s look at each layer in depth.
The Application Layer
The Application Layer depicts user experience with features ranging from web applications to REST APIs that control data flow between client- and server-side environments. This layer is responsible for critical processes such as gathering inputs via GUIs, displaying visualizations on dashboards, and giving data-driven insights via API endpoints. React for the front end and Django for the back end are frequently used, with each picked for its benefits in tasks such as data validation, user authentication, and API request routing. The Application Layer serves as a gateway, routing user requests to the underlying machine-learning models while adhering to strict security protocols to ensure data integrity.
The Model Layer
For data processing and decision-making, the Model Layer serves as the engine room. TensorFlow and PyTorch are specialized libraries providing a diverse toolkit for machine learning operations such as natural language processing, computer vision, and predictive analytics. It involves feature engineering, model training, and hyperparameter optimization. Different machine learning techniques are evaluated using performance metrics, such as precision, recall, and F1-score. This layer receives data from the Application Layer, performs computations, and returns insights. The Infrastructure Layer provides resources.
The Infrastructure Layer
The Infrastructure Layer is essential for model training and inference. This layer assigns and manages computational resources like CPUs, GPUs, and TPUs. Scalability, latency, and fault tolerance are engineered at this level with orchestration technologies such as Kubernetes for container management.
Cloud services like AWS’s EC2 instances and Azure’s AI-specific accelerators are used to handle intensive computing. These services aren’t just passive recipients of requests. They’re dynamic entities that deploy resources wisely.
How the Modern AI Stack Came to Be and Its Current Relevance
Modern AI Stack aims to bring together the most excellent tools and approaches in one place to serve as a reference for:
AI leaders like managers, directors, VPs, and CTOs might learn more about new technologies/integrations and guide their teams toward the current AI stack.
ML Engineers and Data Scientists can discover new technologies by comparing them with their current stack. It will allow for optimizing business operations and staying ahead of the curve.
While it has grown dramatically, many organizations continue to find it challenging to keep up with the rapid evolution of the ML stack. Let’s dig deeper into where the current market is focusing on.
Enterprises Are Focusing More on These Modern AI Tech Stack Components
Artificial intelligence (AI) systems are built with multiple modules focusing on specific tasks but working together to ensure overall operation. This complicated stack of technologies is critical for creating AI capabilities, from data input to final application. The Open AI technology stack includes the following components:
Data Storage and Organization
The first step in AI processing is to store data safely and efficiently. Storage solutions such as SQL databases for structured data and NoSQL databases for unstructured data are essential. Big Data solutions, such as Hadoop’s HDFS and Spark’s in-memory processing, are necessary for large-scale data analysis. The storage type directly impacts the speed of information retrieval, which is crucial for real-time data analytics and machine learning.
Cloud and Scalable Infrastructure
The entire AI technology stack is typically run on a cloud-based infrastructure such as AWS, Google Cloud, or Azure. These systems provide scalable, on-demand computational resources for data storage, processing speed, and algorithmic execution. The cloud architecture enables seamless and harmonious operation of all the above components.
Natural Language Processing and Sentiment Analysis
NLP libraries, such as NLTK and spaCy, are the foundation for understanding human language. Transformer-based models, such as GPT-4 and BERT, improve understanding and context recognition in complicated applications like sentiment analysis. These NLP tools and models are frequently added to the AI stack after deep learning components for applications requiring natural language interaction.
Visual Data Interpretation and Recognition
Visual data requires computer vision technology such as OpenCV. CNNs can be employed in advanced facial recognition and item identification applications. These computer vision components commonly use machine learning approaches to improve multimodal information analysis.
Final Thoughts
As AI practitioners test and reap the benefits of the modern AI stack, new tools are being developed to meet demand. While numerous technologies are available to help you create a comprehensive AI stack, you must first complete three steps.
Is the investment in the tool much less than the cost of developing its capabilities from scratch?
Is the tool simple to learn and use, with dependable customer support? Is the tool flexible enough to accommodate additional features beyond the fundamental requirements?
Once the fundamental prerequisites have been met, other factors such as ease of use, platform infrastructure-agnostic setup, no or low code capabilities, and so on might be considered.
This article has been contributed by Satya S Mahapatra, Chief Brand Custodian and part of the Founder’s office at JUSTO Realfintech.
India’s real estate sector is on a growth trajectory with nearly 4.11 lakh residential units sold in 2023, registering a growth of over 33% from 2022. Similarly, the commercial and retail real estate segment have also witnessed phenomenal growth with rising demand within the manufacturing sector and flexible workspace, and equally supported by the increasing number of malls and organized retail outlets in the country. It is estimated that the commercial real estate segment will continue to grow at 21.1% CAGR to reach $106 billion by 2029. It is expected that the sector will reach $1.5 trillion by 2034.
The real estate sector in India, which was largely driven by sales agents, has witnessed rapid adoption of technology during the pandemic. This trend continued to evolve over the years to provide customers a more transparent and customised service solutions.
Pro-techs leveraged technology and launched innovative solutions across property search, virtual property tours, online property transactions, real-time market data & analysis, smart home solutions, sourcing online finance partners, online property listings, and property management to help ease the transactional process across the developer, channel partners, and buyers. With technology support, any potential investor or buyer can view property, access related documents, and complete the transaction from any corner of the world. However, the biggest challenge was to identify potential buyers from the crowd of leads and connect with them in a more personalized manner.
The use of AI tools in real estate has changed the approach for the developers and the channel partners while generating, assessing, and analyzing data for identifying potential buyers. In this article, Satya S Mahapatra shares insights on using AI to assess buying probability based on multiple data points.
The Top 5 Ways AI Has Helped to Generate Real Estate Leads
Here are the top five ways AI is helping generate real estate leads:
Predictive Analytics
AI tools are the most efficient in analyzing data based on factors like demographics, online behaviour, and past transactions to predict individuals who are more likely to transact immediately. Predictive Analysis uses historical and transactional data of the customers to make informed decisions.
AI can identify high-quality leads and help channel partners to focus on them for faster conversions.
Chatbots
Another challenge with physical contact is the numerous initial engagements with first-time website visitors and social media users, trying hard to convert them into potential buyers by confidently and convincingly responding to their every query. A lot of potential conversions are missed due to human error and negligence. AI chatbots are efficient in responding, sharing, and collating data with initial responders, and they are efficient in assessing and passing qualifying leads to channel partners for further follow-up.
Personalized Marketing
Personalization in communications is the key factor, and the right message can ideally convert a lead into a buyer. AI tools can collate and analyze customer data, and based on the preferences and behavior of potential buyers, it can tailor marketing campaigns that resonate with them.
Personalized communications across key social media platforms and emails can increase the likelihood of more generating leads, and convert the existing ones into buyers.
Prioritizing Leads
Assessing buying probability based on data points like past online and transactional behaviour is beyond normal human capabilities. On the other hand, AI tools process such data at a higher speed and assign a score to each lead indicating their likelihood of conversion.
By prioritizing leads with higher scores, channel partners can focus their attention on such potential buyers.
Automated Follow-Ups
AI can automate and streamline processes that would otherwise require continuous human intervention for seamless follow-up. AI tools can communicate with leads, and send personalized messages at periodic intervals to keep the leads informed and engaged on the various developments and schemes related to the property. Continuous communications can help nurture leads through the sales funnel until they are ready to make a decision.
The role of AI in generating qualifying leads has been one of the biggest differentiators for channel partners. As technology progresses, improved AI tools will help to further streamline the entire home-buying journey through a more data-driven approach. In the near future, salespeople will be equipped with AI tools that can provide real-time information, insights, and recommendations making them more effective and helping them to close leads faster.
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India’s online retail market is booming. It is expected to reach $325 billion by 2030, mainly because of the increased expansion of e-commerce in Tier 2 and Tier 3 cities. A company that is trying to make its mark by tapping into the growth of this industry is Redfynd.
Redfynd is an AI–powered shopping search engine offering a wide range of products from almost all major online stores in India. With its advanced search features, customers can easily compare prices, sizes, and availability across multiple stores.
In this article, let’s learn more about Redfynd, its founder, its business model, its revenue model, the challenges faced, growth strategies, and more.
Redfynd is an innovative AI-powered shopping search and discovery platform designed to transform the online shopping experience for Indian shoppers. Founded with the vision to simplify and enhance the way consumers shop online, Redfynd aggregates millions of fashion and beauty products from over 100 leading e-commerce platforms across India. The platform provides a seamless, user-friendly interface that allows shoppers to easily find, compare, and purchase products all in one place.
Redfynd revolutionizes online shopping with a personalized approach, using AI to recommend product deals based on individual styles and preferences. By doing so, it helps users make informed decisions quickly and efficiently, saving them time and money by helping them find the most relevant products at the best prices. Users also earn cashback for all valid purchases through the platform.
Redfynd is more than just a shopping site; it is a comprehensive shopping assistant that caters to the nuanced needs of today’s digital consumers who value convenience, variety, and informed purchasing. Redfynd’s mission is to empower users with the technology to navigate through the millions of options shoppers across stores effortlessly and make smart purchases, making Redfynd the go-to destination for online shopping in India.
Redfynd – Industry
Redfynd operates in the fast-growing Indian fashion and beauty e-commerce sectors. The fashion e-commerce market in India is expected to grow to $19.6 billion by 2024, making up 18.7% of the total e-commerce market. It is projected to expand at an annual growth rate of 12.6%, reaching $31.5 billion by 2028. Similarly, the beauty and personal care market is forecasted to generate $31.51 billion in revenue by 2024, growing at a rate of 3% annually through 2028. Within this, the personal care segment is expected to reach $14.31 billion.
Over the next five years, Redfynd plans to increase its user base from 1.5 million to 100 million. Redfynd is planning to launch a mobile app to optimize the shopping experience and attract a broader audience. The platform will continue to enhance AI-driven personalization to connect brands with their target consumers more effectively. Redfynd is also planning to partner with more brands to help improve their visibility and sales.
Manjari brings over 20 years of experience in retail and technology, having worked at some of the world’s leading retailers. Prior to founding Redfynd, she worked at Microsoft. She graduated from IIT Kharagpur in 2001 and completed an executive MBA from ISB in 2020.
Manjari has spent her career at the intersection of retail and technology building solutions for merchandising & supply chains and rolling out e-commerce websites across continents.
She is an avid online shopper and has spent thousands of hours on e-commerce as a user herself. It was a frustrating experience for her to hop across websites searching for products, filtering, and comparing to find what she needed.
Manjari saw an opportunity to create a platform that offered convenience and ease of shopping by leveraging technology. Once she set on the journey to build Redfynd, she gathered the core team of Product and engineering through referrals, LinkedIn job posts, and Internshala.
Redfynd Team
Redfynd Team Members
At Redfynd, they operate with a fully remote, 10-member team, prioritizing flexibility and autonomy. Their team members work from locations of their choice and set their own schedules, aligning daily through morning standup meetings to ensure everyone is on the same page. This daily touchpoint helps them set priorities, address challenges, and maintain team cohesion. The company’s approach fosters a productive environment that supports work-life balance and effective team collaboration.
Redfynd Hiring Approach
Redfynd’s hiring philosophy centers on identifying and empowering proactive, hands-on individuals, prioritizing practical skills and the ability to solve problems independently over traditional credentials.
Their process begins with skill-based assignments that assess candidates’s practical abilities and work ethic. This is followed by a hands-on interview where shortlisted candidates must demonstrate their previous work and tackle a live problem, showing their capability to perform under pressure. This approach ensures they select individuals who are not only technically proficient but also adaptable and resilient, essential traits for thriving in a startup environment.
Redfynd – Startup Story
The idea for Redfynd was born out of Manjari’s own frustration with online shopping. She was tired of hopping between multiple websites, comparing prices, and struggling to find what she wanted.
She realized that there had to be a better way to shop online, and that’s when the idea for Redfynd started taking shape. To validate the idea, she conducted extensive research, talking to friends, family, and fellow shoppers to understand their pain points and what they wanted from an online shopping experience.
Manjari also analyzed the market, looking at existing solutions and identifying areas for improvement. This research helped her refine the concept and create a clear vision for Redfynd.
Redfynd – Vision and Mission
Short-termVision: Redfynd aims to transform the online shopping experience in India by leveraging advanced AI-driven search and discovery tools that simplify the process of finding and comparing products across multiple e-commerce platforms. Their immediate focus is to expand their user base and enhance their technology and user experience to offer a seamless and personalized shopping experience.
Long-term vision: Redfynd’s long-term vision is to become the starting point for online fashion and beauty shopping for India’s 300 million online shoppers. The company envisions establishing itself as the go-to platform for smart shopping, where every search starts with them, leading the way in e-commerce innovation in India.
Mission: Redfynd’s mission is to empower consumers by providing a unified platform that delivers comprehensive, accurate, and real-time information on millions of products from various e-commerce sites. The company strive to make online shopping effortless, cost-effective, and highly personalized, helping users make informed decisions quickly and with confidence.
Core Belief and Motto
Innovation in Shopping: Redfynd is committed to transforming the shopping experience by integrating cutting-edge technology to enhance consumer benefits and satisfaction.
Redfynd – Name and Logo
Redfynd Logo
The name, tagline, and logo of Redfynd are deeply rooted in the essence of what its platform offers and Manjari’s personal passion for word puzzles. The name ‘Redfynd’ emerged from a playful wordplay that encapsulates their mission to redefine the shopping experience.
It can be interpreted as ‘Redfynd’, highlighting their goal to transform how consumers find and compare deals. Alternatively, it blends ‘Red’ and ‘Find’, where ‘Red’ symbolizes the hot deals and savings available through its service, and ‘Find’ underscores its core functionality of helping users discover these opportunities.
Redfynd’s logo—a stylized ‘R’ with an encompassing arrow—further reinforces this concept. The arrow signifies the ease and speed with which its users can access deals with just a ‘single click’. This visual element encapsulates its commitment to efficiency and user-friendly design, ensuring that the best deals are always easily accessible.
Together, the name and logo not only represent Redfynd’s identity but also serve as a constant reminder of its dedication to simplifying and enhancing the online shopping experience for its users. Through these creative elements, the company communicates its value proposition clearly and effectively, making it instantly recognizable and memorable.
Redfynd – Product/Services
Redfynd is an AI-powered shopping search and discovery platform that simplifies and enhances the online shopping experience. It serves as a one-stop destination where users can find a wide array of fashion and beauty products from over 100 major e-commerce platforms in India, including Myntra, Ajio, and H&M. With a database of more than 5 million products, Redfynd aims to make online shopping more enjoyable, less time-consuming, and budget-friendly.
How Redfynd Works
Redfynd utilizes advanced artificial intelligence technologies, including natural language processing (NLP), computer vision, and machine learning, to sift through millions of products online. This enables the platform to offer features like visual and semantic search and personalisation, allowing users to find products that closely match their intent and preferences easily. Users can compare prices, check available sizes, and read customer reviews across various platforms, all in one place, which simplifies the decision-making process.
Problems Solved by Redfynd
Redfynd addresses several pain points in the traditional online shopping process:
Simplifying The Choices: Helps users find and navigate through all available choices easily by filtering and presenting products that best match users’ search criteria.
Time-Consuming Searches: Reduces the time spent hopping between different shopping sites through aggregated search results.
Informed Decision Making: Provides detailed product information, price comparisons, and customer reviews to help users make better-informed purchasing decisions.
Redfynd Price Comparision
USPs and Innovations of Redfynd
Unified Shopping Experience: Aggregates products from multiple e-commerce stores into a single platform, providing a seamless and cohesive shopping experience.
AI-Driven Personalization: Utilizes AI to understand user preferences and shopping behaviors, thereby personalizing search results to suit individual tastes.
Visual and Semantic Search Capabilities: Allows users to search using images, product URLs from 100+ stores, or nuanced queries, making it easier to find the exact products they are looking for.
Pivotal Changes in Redfynd
Redfynd has changed continuously to optimize it for a better shopping experience for users, but the core focus has always remained the same, leveraging AI to revolutionize the e-commerce experience for easier and smarter shopping for Indian shoppers across the globe. They have introduced several advanced features like advanced search and filtering, real-time price and size comparison, personalized recommendations, and a Redfynd rewards program that enables cashback through the platform.
Redfynd – Business Model
Redfynd’s business model is all about making online shopping easy for users and benefitting e-commerce platforms and brands by offering them different ways to add value:
Affiliate Marketing: By acting as an intermediary platform between users and e-commerce sites, Redfynd facilitates transactions and earns commissions.
Promotional and Visibility Services: By offering listing and promotional services, Redfynd helps brands enhance their visibility among potential customers.
Data-Driven Insights: Through its analytics services, Redfynd provides valuable market insights to brands, helping them make informed business decisions.
Redfynd – Revenue Model
Here are the different revenue streams of Redfynd:
Sales Commissions: Redfynd earns commissions from partner brands when users make purchases through links on its platform.
Listing Services: The platform offers listing services to retailers and select brands, providing them with enhanced visibility and promotional opportunities.
Targeted Advertising Services: Redfynd delivers advertising that targets shoppers with high purchase intent, ensuring a high return on ad spend (ROAS).
Analytics Services: Redfynd offers subscription-based and one-time fee services for trend analysis, assortment analysis, competitive intelligence, and pricing intelligence reports.
Redfynd was initially launched as a beta version, introduced first to a network of friends and family. This approach allowed the gathering of valuable feedback and fine-tuning of the platform before the public launch.
After refining the Minimum Viable Product (MVP) based on this initial feedback, Redfynd was successfully launched to the public. A crucial strategy in acquiring the initial 100 users involved making full use of search engine optimization (SEO).
By ensuring that all data on the platform was effectively indexed by search engines, Redfynd captured organic traffic from potential users actively searching for better shopping options.
Redfynd – Customer Growth and Retention Strategies
Since the successful launch of Redfynd and the acquisition of its first 100 users primarily through search engine optimization, the company has expanded its strategies to include social media to significantly scale up its user base.
Recognizing Instagram as a crucial platform for its target demographic—tech-savvy, fashion-conscious, and bargain-hunting shoppers—Redfynd has tailored its content to engage this audience effectively. The company’s posts leverage current trends to showcase the best deals, like the Barbenheimer-inspired Bollywood outfits post, which went viral with over a million views. This not only increased brand awareness but also highlighted its value proposition of providing the best deals.
To drive traffic to the website and convert viewers into users, Redfynd launched giveaway contests that reward users for referral signups. This strategy not only boosted its user base but also encouraged community engagement and interaction. New signups gain access to several engaging features like wishlist creation, sharing capabilities, and price drop alerts. These features are designed to enhance the user experience, fostering greater interaction and repeat usage.
To reach its initial milestone of 1,000,000 users, it implemented a strategic combination of marketing efforts focused on leveraging both digital and community-based channels.
In addition to SEO, engaging content across social media channels helped maintain user interest and foster community interaction. Redfynd included personalisation and other features to improve retention. Together, these strategic efforts successfully attracted 1 million users, establishing a solid foundation for future growth.
Redfynd – Challenges Faced
Educating consumers about the benefits of Redfynd, particularly in a saturated e-commerce market, is a significant challenge. The platform, which combines cashback rewards with price comparison and personalized shopping experiences, requires clear and compelling communication to highlight its advantages over traditional shopping methods. This involves not only demonstrating immediate savings and enhanced convenience but also ensuring an intuitive user experience that can overcome consumer inertia and loyalty to established platforms.
Short explainer videos have worked very well, as they can effectively communicate the benefits of Redfynd in a visually engaging and easily digestible format. These videos simplify complex ideas—like how Redfynd’s cashback system works or the advantages of price comparison—making it easier for consumers to understand and see the value in changing their shopping habits.
Redfynd – Marketing Strategy
The ‘price comparison’ campaigns have been very effective in emphasizing the value of using Redfynd and encouraging users to routinely check the platform to ensure they are getting the best deals. By directly addressing the misconception that one e-commerce platform always offers the best prices, it draws in users who are looking to make more informed purchasing decisions.
Redfynd – Competitors
One of the competitors of Redfynd in the industry is Fashiola.
Redfynd – Future Plans
Geographic expansion to the US and Europe is on the cards, where users from across borders can discover products sold by online stores in India that ship to the user’s location. Additionally, Redfynd plans to launch advanced features like AR stylist and voice search in local languages.
This article has been contributed by Anuj Gupta, CEO of Youngrads.
In recent years, the education sector has undergone significant transformation, fueled by technological advancements and innovative approaches that enhance the overall learning and teaching experience for educators and learners. IBEF indicates that the Indian edtech market is poised to skyrocket to US$ 30 billion by 2031, a substantial leap from its 2021 figures and KPMG’s insights reveal India’s ascent as the world’s second-largest E-learning market after the US. Moreover other Countries worldwide, such as Australia and the UK, are actively embracing these technological advancements in the EdTech Sector. And at the forefront of this evolution is artificial intelligence (AI), which promises personalized and immersive learning and also fosters Edtech approaches, marking a pivotal shift in educational paradigms.
Artificial Intelligence is transforming the learning, providing groundbreaking solutions that reshape the interactions between students and educators in the EdTech space. These AI-driven tools elevate the educational landscape by tailoring experiences to individuals, fostering interactivity and streamlining efficiency. Previously burdened by work overload, educators struggled to cater to each student effectively. With AI integration, teachers globally can concentrate on delivering dynamic content and personalized learning, while also facilitating mentorship from around the world, thereby broadening students’ understanding through exposure to diverse perspectives and guiding them through uncharted territories.
How AI is enhancing the Education System and EdTech Initiatives?
As AI continues to seep into various industries, education is no exception. The sector is undergoing continuous evolution to meet new demands and embrace emerging trends. Here, let’s explore several AI trends that are reshaping the landscape, ushering in transformative changes and new opportunities :
Tailored Approach – AI algorithms analyze student data, like academic performance, interests and goals, to suggest fitting study programs. This enhances decision-making and program alignment, benefiting students. Additionally, AI personalizes in-class activities and assignments according to individual comprehension levels. This enables teachers to accommodate various learning styles and speeds, promoting inclusivity in education.
Real Time Assessment with AI – AI enhances the educational experience by analyzing student responses, offering immediate feedback and pinpointing areas for additional support. For instance, in the UK, the FirstPass online platform utilizes AI to provide real-time feedback to students as they answer open-ended questions. This approach fosters positive meta-cognition skills, as learners recognize areas for improvement and refine their work before submission. By eliminating the need to wait for teacher assessments, which can be time-consuming and delayed, students can promptly receive feedback to enhance their understanding and address areas needing improvement in both assessment and learning.
AR and VR – In EdTech, AI, VR and AR are pivotal. VR and AR foster interactive learning, elevating engagement and facilitating active participation. These technologies prioritize experiential learning, collaboration and interactive engagement over passive information consumption. They’re utilized across subjects such as engineering, science, anatomy, archaeology and anthropology. Esteemed institutions like Stanford and Harvard integrate VR/AR into their educational frameworks, harnessing their potential for enriching learning experiences.
Organising Course Material – AI significantly enhances EdTech initiatives by aiding teachers in crafting and structuring course materials, syllabi, lesson plans and assessments. Moreover, it facilitates personalized learning experiences by tailoring course content, like practice problems and interactive exercises, to individual students’ knowledge gaps, skills, and learning preferences. The generative AI plays a pivotal role in generating novel teaching materials, including quiz questions, exercises and concept explanations. This fosters the integration of contemporary educational content into syllabi, thereby bolstering students’ engagement and comprehension of modern curriculum elements.
Overall, AI’s contribution in education modernizes learning resources and also cultivates a more inclusive and effective educational environment.
Number of Indian Students Studying Abroad from 2017 to 2022
Benefits of AI in Edtech Initiatives
AI algorithms play a crucial role in the education sector, benefiting students both locally and internationally, such as those from countries like India pursuing education in popular destinations like Australia, the UK, and the USA. Through EdTech innovations, universities enhance study experiences. Here are the ways AI benefits students and teachers:
AI-powered tools offer invaluable assistance to students by simplifying complex concepts, leading to enhanced academic outcomes and higher graduation rates.
AI has the ability to tailor learning experiences to each student’s individual needs. Through constant analysis of student performance, AI algorithms pinpoint areas where students may need extra help. And offer tailored support by suggesting additional resources, recommending specific learning materials, and adjusting assignment difficulty to match each student’s proficiency level. This adaptability ensures that students are appropriately challenged and receive the necessary support to excel in their studies.
As AI and EdTech continue to thrive in the education sector, they are increasingly enticing students from India to explore international education opportunities, promising a richer learning experience and expanded career prospects. Through immersive AI and AR/VR experiences, learners gain practical, hands-on skills that bridge the gap between physical and virtual realms, offering newfound flexibility in job roles and career trajectories. EdTech, as a vehicle for social good, leverages innovative technologies to complement rather than replace traditional teaching methods. And AI plays an important role in enhancing EdTech initiatives, both in classroom settings and online processes, empowering educators to deliver more effective instruction. This synergy of technology and education facilitates access to international institutions and also fosters a culture of continuous learning, equipping students with the tools they need to thrive in an evolving landscape and chart their own paths to success.
Damini Bhandary
