Asurion's Enterprise Data Service team was tasked with gathering over 3,500 data assets from the entire organization, providing a unified platform where all the data could be cleaned, joined, analyzed, enriched, and leveraged to create data products. The previous iterations of data platforms, built mostly on traditional databases and data warehouse solutions, encountered challenges with scaling and cost due to the lack of compute and storage separation. With increasing data volumes, a wide variety of data types, demand for lower latency and increased velocity, the platform engineering team began to consider moving the whole ecosystem to Apache Spark™ and Delta Lake using a lakehouse architecture as the new foundation. The previous platform was based on Lambda architecture, which introduced problems such as data duplication and synchronization, logic duplication, different ways to deal with late data, data reprocessing difficulty due to the lack of transactional layer, and platform maintenance downtimes.

AT&T, a leading communication service provider, was facing challenges with its legacy on-premises architecture. Despite having 182 million wireless customers and handling 10 million transactions per second, the company was struggling to stay ahead of fraudsters. The existing infrastructure was complex and failed to deliver the innovation required for an optimal customer experience. The company was using rule-based technology for fraud detection, which was reactive rather than proactive, making it difficult to stay ahead of sophisticated fraud attempts. The process was not only protracted, inefficient, and resource-heavy, but also expensive. AT&T also struggled to gain real-time insights and automation necessary to optimize dispatch. The company could not unify data points to match a technician’s troubleshooting skills to the customer issue and location, leading to increased operational costs and a negative impact on customer experience.

AT&T, a leading telecommunications company, was grappling with the challenges of managing a massive on-premises legacy Hadoop system. The system was complex and costly, hindering operational agility, efficiency, and the optimal use of engineering resources. AT&T needed to transition to the cloud to better support its hundreds of millions of subscribers. The company was dealing with a highly complex hardware setup, including 12,500 data sources and over 1,500 servers. The on-premises Hadoop architecture was not only expensive to manage but also complex to maintain. Operational costs were high, and additional capital costs were incurred for data centers, licensing, and more. Up to 70% of the on-prem platform had to be prioritized to ensure 50K data pipeline jobs met SLAs and data quality objectives. Engineers were spending more time managing updates, fixing performance issues, and provisioning resources rather than focusing on higher-value tasks. The physical infrastructure's resource constraints also slowed down data science activities, impeding innovation.

CARS24, a tech-first organization specializing in the buying and selling of pre-owned cars, faced a significant challenge in managing the surge in demand for its services during the COVID-19 pandemic. The company experienced a 200% increase in support volumes, with monthly traffic reaching 13 million and transactions escalating to half a million. The company was inundated with large volumes of repetitive support queries, particularly around car evaluation. The wait time for customer queries, which had extended to minutes, needed to be reduced to seconds to improve customer satisfaction. The average query resolution time also needed to be improved to enhance the overall customer experience.

CEAT, a leading tyre manufacturer, was looking to enhance its customer engagement and lead generation strategies. The company wanted to have effective and engaging conversations with its customers on a large scale, with the ultimate objective of collecting high-quality leads, amplifying conversion rates, and extending its brand presence on the messaging platforms where their target customers were most active. To make interactions smoother for their target persona, CEAT realized that accessibility and an omnichannel approach were key. They aimed to offer prompt and immediate answers to potential customers inquiring about commonly asked questions regarding tyre purchase and maintenance. The customer experience team at CEAT also wanted to offer existing customers a convenient way for logging and tracking complaints. Lastly, CEAT wanted to ensure that both prospects and customers were aware about the latest offers and promotions.

Eureka Forbes Limited, a leading health and hygiene brand in India, faced a significant increase in customer inquiries due to the COVID-19 pandemic. The surge in demand for safe water, hygiene, and sanitation products necessitated a more efficient and modern approach to customer service. The company aimed to decrease first-response time, provide swift and customized query resolution, and enhance customer engagement using AI and ML technologies. The challenge was to handle the influx of customer interest in water purifiers and provide accurate and precise brand patronage through an AI-driven solution.

Hathway Cable and Datacom Limited, a leading cable broadband and cable television service provider in India, faced a significant challenge in managing customer queries, complaints, and requests. The COVID-19 pandemic led to a surge in the number of customers using Hathway's digital platforms, including their app, self-care portal, and website. The process to analyze and answer customer queries was lengthy, resulting in slower response times, delayed resolution, and higher costs. Hathway aimed to improve the ticketing system and reduce the customers’ wait time. The goal was to reduce the first-response time and provide instantaneous query resolution. They also wanted to offer round-the-clock FAQ resolution to increase customer satisfaction and build a robust sales pipeline.

Healthkart, a leading Indian health brand, faced a significant challenge during the covid-19 pandemic. The company experienced a massive surge in user queries, which it struggled to handle efficiently. The company's goal was not only to manage these queries but also to provide high-value use cases that would drive engagement and help people lead healthier lifestyles. The main challenges included making support more self-serve and asynchronous to handle the increased user queries, positioning Healthkart as the go-to destination for diet, fitness, and immunity-related advice, and proactively educating users and recommending relevant products based on their lifestyle and fitness goals.

IIFL Holdings Limited, a leading diversified financial services company in India, was grappling with the challenge of managing a high influx of customer support queries from its large customer base of over four million individuals. The company was seeking an effective and cost-efficient solution to enhance the overall customer experience by providing faster query resolution. The growing number of customer queries was putting a strain on their call center operations, leading to higher operational costs. Even low-touch, basic queries were subject to delays in receiving support. The objective was to free up human agents from addressing low-touch queries, thereby enabling them to focus on resolving more complex queries. The goal was to minimize the necessity of human intervention and decrease the potential for errors.

Jio Digital, a leading telecommunications platform in India, faced the challenge of maintaining exceptional customer experiences while catering to a diverse and extensive customer base. The company recognized the importance of personalization and quick, accurate query resolution to set themselves apart in the competitive telecom industry. However, the sheer volume of customers and the need for efficient, personalized responses posed a significant challenge. The company needed an agile solution that could promptly respond to customer queries, prioritize efficiency, and deliver accurate solutions. Furthermore, the solution had to be designed to deliver personalization, a key differentiator for Jio Digital.

Jio Fiber, a fiber-to-home internet broadband service, was seeking to provide seamless support to its existing and potential customers. The company partnered with Haptik, a tech company known for its expertise in enhancing customer support, to build a WhatsApp chatbot. The challenges that Haptik faced included providing faster resolution to routine queries to enhance customer experience (CX), freeing up customer service agents to focus on more complex queries, and enabling a seamless experience while reducing costs by deflecting 70% of top call driving queries on chat.

Jio Health Hub, a health app by Reliance Jio, was seeking innovative ways to engage with users, improve registrations, and provide real-time support on newer channels. The team identified WhatsApp, a platform widely used across urban and rural India, as a potential medium to disseminate information and attract more users to the Jio Health App. The challenge was to offer users information and support in their preferred languages. The Jio Health Hub team also aimed to acquire users and boost registrations via WhatsApp and drive traffic to the Jio Health App. Additionally, they wanted to provide a simple way for customers to book consults and access reports.

JioMart, an online shopping platform developed by Reliance Industries, aimed to provide a simple and convenient online shopping experience to millions of Indian citizens. The platform offered a range of products across various categories such as consumer electronics, apparel, footwear, grocery, and general merchandise. As the customer base expanded, the team at JioMart recognized the importance of prioritizing customer satisfaction and convenience. They identified the need for an omnichannel approach to make shopping easy for every Indian citizen. The primary challenge was to simplify online shopping and capture a previously untapped market. They also needed to meet the increasing expectations of customers who were willing to make purchases on social platforms and expected personalized experiences. In addition to new customer acquisition, JioMart also prioritized customer retention, repeat purchases, and loyalty. They also sought to diversify beyond just groceries and promote their offerings in other categories.

Ring, a leading financial technology platform in India, was facing a significant challenge in managing the high volume of customer requests due to its extensive network of over 3000 offline merchants and more than 50 online stores. The company's primary goal was to help customers maximize the benefits of the platform and provide assistance at every step. The customers' primary expectations were prompt query resolution and a satisfactory customer experience. They sought a responsive and efficient customer support system that could address their concerns promptly. Ring recognized the importance of 24/7 brand availability in providing a seamless customer experience and was exploring solutions to enhance the rate of first response time.

Kotak Life Insurance Company, one of the fastest-growing life insurance companies globally, was seeking a comprehensive solution to streamline customer interactions across various messaging channels. The company aimed to provide personalized insurance services through WhatsApp, including comprehensive information on various policy options, the ability to ask questions, receive quotes, and even purchase policies directly through the app. The team prioritized chat channels as their main customer contact option due to its ease in maintaining context and history. They also needed to offer first-class aid and advice to potential customers, providing them with the best insurance plan recommendations. Additionally, Kotak Life was looking for an efficient solution to remind existing customers of premium reminders and policy updates.

The Government of India (GOI) faced a significant challenge in the fight against COVID-19, primarily due to the spread of misinformation about the disease. The novelty of the virus led to a proliferation of incorrect information about its symptoms, precautionary measures, and remedies, causing widespread panic among the population. The GOI needed a solution that could handle the scale and diversity of COVID-19 related queries, in both English and Hindi, to ensure that people were not misinformed about the disease. The solution needed to provide accurate, necessary information to help treat people or prevent them from contracting the virus.

Netmeds, one of India's most trusted pharmacies, faced a significant challenge during the height of the COVID-19 pandemic. The company experienced a tenfold increase in its customer base, leading to a surge in incoming traffic and a consequent increase in agent load. The company was struggling to handle the increased demand and needed to automate simple queries to reduce the load on its agents. Additionally, Netmeds was under pressure to offer 24/7 customer support to address the round-the-clock queries about medicines, prescriptions, and more. The company also aimed to improve its resolution rate and first-response time (FRT) to enhance customer satisfaction.

Pepperfry, a leading online marketplace for furniture and home decor in India, was facing a significant challenge in meeting the growing demand for instant query resolution and customer support. The company's customer base had increased fivefold, and its existing helpline number and email support services were unable to keep up with the surge in customer queries. This resulted in longer wait times and a decline in customer satisfaction. The company was also grappling with the high costs associated with the increased reliance on call centers. Furthermore, providing 24/7 information was a challenge that needed to be addressed. The goal was to reduce the dependency on call centers and long wait times, and to provide immediate solutions to customer queries.

StarHub, a leading Singapore-based communication, entertainment, and digital solutions provider, was grappling with an outdated and manual customer support system. This was negatively impacting their operational performance and overall customer experience. The company, which holds a 30% market share and serves over 2 million customers, was struggling with inconsistent issue handling, leading to longer wait times, customer dissatisfaction, and a high churn rate. The customer support agents had to switch between multiple platforms to gather information for customers, which was a time-consuming process. Furthermore, the inability to share technical diagrams and photos with customers was affecting agent productivity and the quality of support provided.

Tally Solutions, a pioneer in the business software products industry, faced a challenge as its client base expanded. The company needed a solution to keep up with the increasing demand for personalized engagement. Tally aimed to enhance its website visitor engagement by providing prompt responses to routine queries and encouraging them to schedule a demo with the sales team. However, the communication was primarily reactive rather than proactive, and the agents were handling a significant volume of low-touch, routine queries, resulting in an overload of resources. Tally sought a platform that could enhance user engagement by effectively promoting product launches, feature updates, exciting news, and alerts. The ultimate goal was to reduce the burden on live agents by minimizing their exposure to repetitive queries.

Tata CLiQ was experiencing a lower than expected conversion rate of visitor sessions into transactions. Despite driving thousands of visitors to their website and mobile app daily, the ratio of these visits converting into purchases was not meeting the company's targets. The team identified two key needs to address this issue. Firstly, they needed a scalable way to provide buying assistance to customers, especially for high-value categories such as electronics and appliances. Secondly, they recognized the need for automation and AI-powered recommendations to improve conversions without the need to scale the support team.

Tata Mutual Fund, a part of the renowned Tata group, was facing a challenge in improving customer experience, particularly for the digital-first millennials. The company aimed to reduce monthly customer calls by 70% and engage customers on their preferred channels, such as Messaging & WhatsApp. They needed an AI-driven solution that could seamlessly integrate with their existing customer support infrastructure. The primary objective was to provide faster query resolution and minimize human intervention. The solution was expected to offer an easy way for customers to get their queries resolved and be integrated into existing customer service channels.

Upstox, Asia's largest investment platform, was facing a challenge with a growing number of dormant users despite an increase in overall platform users. While the company had a successful strategy for attracting new customers, they needed to find a way to better engage with their existing, inactive customer base. The goal was to drive financial education, encourage trading activity, and convert these latent clients into frequent traders. Upstox also aimed to explore new marketing channels, such as WhatsApp, to attract and onboard new users while improving the trading experience for their existing clients. They wanted to offer a distinct value proposition in a highly competitive market by becoming the first investment platform to support IPO applications on WhatsApp. Furthermore, they wanted to ensure that every incoming lead was promptly responded to in a timely and efficient manner.

Zurich Insurance Group, one of the world's largest and most experienced insurers, was facing a significant challenge in managing the enormous volumes of queries and service requests from its large customer base. The company's goal was to cater to its customers' insurance needs effectively, especially during critical times such as after an accident, illness, or a natural calamity. Zurich sought to ensure 24/7 availability of customer care to attend to queries during and outside business hours, instantly resolve customer queries while providing relevant information and guidance, and make support seamless and easily accessible to customers, which can boost customer satisfaction.

Appsvio, a company that creates Jira apps distributed through the Atlassian Marketplace, was facing a challenge with customer communication. Initially, they handled all customer interactions via email, but soon realized they were juggling too many communication channels. In addition to email, they were using Jira Service Management and Hubspot’s live chat. However, the latter was not meeting their needs as they couldn’t track their chats in Jira Service Management. This lack of integration and tracking was causing inefficiencies and making it difficult for them to provide the level of customer support they aimed for. The challenge was to find a solution that would streamline their customer communication, make it more effective, and allow for real-time interaction.

GreenState Credit Union, Iowa’s largest credit union, operates on a lean model, relying on strong talent and highly efficient processes. The credit union aims to return the savings from their efficiency to their members in the form of better rates and lower fees. However, they faced a challenge in maintaining this efficiency, particularly in their communication with members. Traditional phone communication was not efficient as it allowed one employee to speak with one member at a time. GreenState needed a solution that would allow their employees to interact with multiple members concurrently, thereby increasing their efficiency. They also needed a solution that would integrate well with their platform, provide an excellent user experience, and come with robust reporting tools for tracking their efficiency gains.

Pioneer Millworks, a company with over 30 years of experience in crafting flooring, paneling, siding, and decking, was facing a challenge with their existing chat system. The basic chat system they were using offered limited functionality and did not integrate with their CRM, making it difficult to link customer queries to projects and assist customers in finding products or ordering samples on their website. The company was in need of a more robust system that could seamlessly integrate with their CRM and provide a more efficient and effective customer service experience. They were also looking for a solution that would not break their budget and would offer room for growth.

Sensorem, a Stockholm-based tech start-up, was facing a significant challenge with their previous live chat provider. The company, which develops safety alarms for seniors, was losing potential sales opportunities due to the lack of immediate response to customer inquiries. When their team was offline, visitors would leave the site within minutes, and the agents were unable to reconnect with them. This was causing a significant loss in potential revenue. The turning point came when Johan Danielsson, one of Sensorem’s co-founders, had a positive experience with a live chat service while shopping for shoes online. He realized that superior customer support was a key selling point for Sensorem's products and decided to replicate the service he experienced on Sensorem’s website.

Sephora, a leading beauty retailer, faced a significant challenge when they had to close their physical stores in March 2020 due to the pandemic. The company prides itself on providing a unique and professional service tailored to customers’ needs, including detailed interviews and product consulting. The closure of their stores meant they could no longer offer this personalized service. Even before the pandemic, Sephora had been considering implementing LiveChat on their website, but the lockdown in Poland, where they are based, accelerated this decision. The challenge was to replicate the in-store customer experience in a safe, online space, maintaining the same level of customer care and product knowledge.

A leading Illinois-based collections agency, specializing in healthcare and retail receivables, was facing a significant challenge in managing their after-call work. The agency wanted to minimize the time their agents spent on after-call tasks and increase their in-call productive time. The goal was to enable their agents to work on more accounts and focus more on talking to borrowers, rather than getting distracted by other tasks. The agency was looking for a solution that could help them streamline their operations, increase productivity, and ultimately, improve their bottom line.