Nowadays, each click and scroll generates data, shaping the virtual landscape. According to the International Data Corporation, the global datasphere could reach 175 zettabytes by 2025, a remarkable increase from 33 zettabytes in 2018. This growth quantifies the ongoing surge in data creation worldwide.
This data explosion triggers a transformation influencing user experiences and business growth. Personalization is revolutionizing marketplaces by enhancing user experiences through tailored recommendations and content based on individual preferences, leading to increased engagement and satisfaction. Matching algorithms are becoming more effective at connecting users with products or services that align with their specific needs and preferences, resulting in better customer outcomes and higher conversion rates.
Tech expert, author, and speaker Gayatri Iyengar, Head of Engineering, Logistics and Growth emphasizes that personalization has become the bedrock of modern marketplace infrastructure, not just a feature. Fueled by data-driven insights, these personalized algorithms cater to individual users by offering tailored content and experiences.
As this world explores personalization, Iyengar is a visionary leader who ensures the convergence of matching algorithms, marketplace preferences, and infrastructure scales smoothly under her expertise and leadership.
Personalization and Revolutionizing Marketplaces
Recent reports indicate that the global eCommerce market surpassed US$ 16.6 Trillion in 2022 and is projected to reach a staggering US$ 70.9 Trillion by 2028. This growth reshapes user interactions with online platforms.
Such a shift in the eCommerce marketplace and logistics companies means they are adapting to providing tailored services to their customers that may vary from giving many delivery options to a more comprehensive selection of food recommendations based on past preferences. Banks and electronic trading platforms are also optimizing their matching algorithms to provide tailored recommendations and investment strategies based on risk profiles, financial goals, and transaction history, all ushering in a new way of building personalized marketplaces.
The Power of Data
Iyengar mentions that a key differentiating factor for companies will be the data they harvest and what they do with it. The ability to build large-scale distributed systems that can collect, analyze, and leverage data effectively for sophisticated decision-making will be critical. Data like past purchases, search history, demographics, and engagement patterns will feed as input into the matching algorithms, forming a comprehensive portrait of individual preferences. Armed with these insights, personalized algorithms will enable eCommerce platforms to provide recommendations, content, and experiences that resonate personally-breaking away from monotonous standardized offerings.
Measuring Success Through NPS
The success of personalization algorithms is measured by user NPS (net promoter score) and increased engagement on the marketplace platform. Iyengar explains that higher customer satisfaction creates opportunities to sell new services or products on the marketplace, creating a virtuous cycle and enabling new products and services to be sold on the platform.
Logistics and Marketplace Trends
The future of logistics and marketplaces is not just about personalization but also significant changes in marketplace dynamics.
Intermodal Marketplace and Logistics Network
According to Iyengar, one of the standout trends in the logistics industry is the emergence of intermodal marketplaces and logistics networks. Today, many marketplaces, especially in the logistics industry, use multiple modalities to deliver their services. These could range from cars, vans, trucks, bikes, walking, to drones. Today, depending on the product people order on their marketplace, it is delivered to them through various modalities. The ability to intelligently decide which mode works best at which time, and the necessity to mix multiple methods, is a critical decision that needs to be made but is one of the indicators of a more personalized marketplace.
Locations and Supply Demand Dynamics
Iyengar explains that the real-time signals and the acute understanding of geospatial data are central to the success of matching algorithms. These factors will be critical in determining the most intelligent routes and delivery modes. The eCommerce platform of the future will need to make these decisions based on supply, demand, traffic conditions, personalization, preferences, and customer needs, all of which change dynamically.
Matching and Routing Algorithm
Matching and routing algorithms are the heartbeat of the on-demand fulfillment infrastructure. Iyengar emphasizes that the most complex part of creating these algorithms is that once every decision is made, it becomes stale and will quickly become obsolete as supply, demand, traffic conditions, personalization, and customer needs change dynamically. The marketplaces that succeed will be the ones that harness the delivery data and use that to better the routes.
The Future of Infrastructure
Building Platforms Compared to Products
The tech expert's career is marked by influential roles in building distributed systems and large-scale infrastructure that handle billions of data per second. Building successful marketplaces will require advanced technology, effective governance, and user-centric design. Cloud-based infrastructure will be essential for scalability, flexibility, and cost-efficiency. Serverless computing and containerization will be critical in managing resources efficiently with growing data.
AI and Machine Learning
AI and Machine learning algorithms will be crucial for personalization, fraud detection, recommendation and matching engines, and user behavior analysis. These technologies will be critical to providing a personalized end-user experience.
Data Analytics and Mining
As claimed by Iyengar, personalization redefines the rules of engagement as it establishes a platform where each digital interaction bears the hallmark of exclusivity, tailored to harmonize with individual preferences. Marketplaces will generate massive amounts of data. Implementing robust real-time analytics and building extensive data infrastructure will be essential to extract insights, predict market trends, and make data-driven decisions.
Reliability Will Be the Most Important Feature
Iyengar points out that to make this personalization work well, the matching algorithms and the technology that supports it need to become highly reliable and scalable. Personalization is not limited to fulfilling the best item but also opens up an entirely new world of on-demand economy in logistics infrastructure. This further means that the reliability of the underlying fulfillment infrastructure becomes very important, balancing this against constraints like cost and speed. The job of fulfilling orders and delivering services gets more complex as the underlying fulfillment platforms need to now keep many real-time signals, customer preferences, pricing, cost, network effects, and other marketplace player's choices in mind to provide the most optimal experience.
Build Global but Stay Local
Iyengar's prior experience leading global teams across the USA, India, and Lithuania as the Head of Reliability Platforms at a renowned transportation company testifies to her ability to create personalized offerings among international audiences and globally.
Additionally, her commitment to innovation and community collaboration is evident in her work on open-source platforms, solidifying her reputation as a pioneer who bridges the gap between innovation and collective advancement. She further claims that in expanding into international markets, marketplaces will need infrastructure for localization, including language support, currency conversion, compliance with local and international regulations, data protection, consumer rights, and taxation, which will be crucial.
The Catalyst for Personalized Innovation
Iyengar has taken on lead positions in prominent companies, spanning logistics, data, and financial services. She has played a pivotal role in creating marketplaces and the essential infrastructure and platforms that underpin them while emphasizing the central part of data. As the Head of Engineering and Applied Sciences, her impact resonates deeply across vital functions, from building the underlying logistics and marketplace fulfillment infrastructure to onboarding gig workers and making the eta's, maps, and routing strategies. She also oversees a specialized team of professionals, including software, mobile, and infrastructure engineers, data scientists, machine learning engineers, and operations research scientists.
From working on algorithmic financial trading platforms at a multinational investment bank to pioneering digital banking solutions, her journey is a testament to her unique blend of expertise and innovative drive, particularly in marketplaces, algorithms, and infrastructure.
Wrapping Up
While the rise of personalization algorithms promises to elevate user experiences, navigating the industry through challenges and ethical considerations is still evident. As the digital world increasingly tailors content to individual preferences, biases surrounding algorithms raise valid concerns. Both explicit and implicit biases can perpetuate existing disparities and limit the scope of users' exposure to diverse perspectives.
Moreover, personalizing user data stirs privacy concerns, with the potential for data breaches and unauthorized access. This perspective underscores the delicate balance that must be applied between offering tailored experiences and nurturing a seamless digital environment.
Iyengar builds on her commitment to mentorship, community collaboration, and technological advancement that extends beyond corporate realms. As an advisor to tech companies and a contributor to Venture Capital firms' due diligence efforts, her thought leadership drives conversations that shape ethical and inclusive personalization practices.
Amid this vast sea of offerings, the role of personalization algorithms gains significance. These advanced algorithms do more than just curate recommendations; they decipher the intricate tapestry of users' online behavior. With Iyengar at the helm of this advancement, personalization algorithms and marketplace infrastructure promise to reshape digital interactions into deeply personalized and enriching experiences.
