Starhub, a leading telecommunications company based in Singapore, was facing challenges with its complex ecosystem of data and applications. The company was in dire need of better governance to manage its data effectively. As part of its broader digital transformation and IT modernization program, Starhub aimed to establish a standard semantic and data delivery layer. The goal was to streamline data management, reduce reliance on IT, and lower data infrastructure costs. The challenge was to find a solution that could deliver timely data across the organization through self-service, while also ensuring security and minimizing disruption to the business.

Sunbelt Rentals, a leading player in the equipment rental industry and the second largest rental provider in North America, was on a mission to provide an unrivaled Customer Experience (CX) for all kinds of rental customers. The company aimed to grow from the number two equipment rental company in North America to number one. To achieve this, Sunbelt Rentals needed a growth plan that could drive and support an enterprise-wide digital transformation, with data at the core of this journey. The company faced challenges in modernizing their data integration efforts and creating a single access point for the business and developer teams to access all of their data assets.

MultiChoice Group, a leading entertainment company, was facing a significant challenge in managing and integrating its geographically distributed data. The company operates in various countries in Africa and maintains relationships with different service providers, each operating in different countries and providing data in a variety of formats. This diversity made it difficult for the data and analytics team to integrate and process the data using traditional methods. The team was spending over 80 hours per month on data preparation, and the data required for reporting was almost a month behind schedule. The company needed a data integration solution that could connect to all kinds of data sources, integrate the data through a single service layer, and enrich data on the fly.

VTTI, a global energy storage services company, was faced with the challenge of managing and utilizing massive amounts of data generated from its operations. With over 10 million cubic meters of storage capacity located across five continents, the company loads or discharges around 11,000 vessels, trucks, and trains globally every year. This scale of work provides VTTI with unique insight into energy trading and product flows. However, the company needed a way to generate insights from this data and make it readily and effectively available to business stakeholders. The data was also crucial for monitoring pumps and pipes, as well as for engaging in predictive and prescriptive maintenance of the entire infrastructure. VTTI was in need of a solid analytical foundation that could serve use cases in the field of predictive and prescriptive analytics to better manage customer expectations and enable customers to better manage expectations with the rest of the value chain.

Article, a digital retail leader, was faced with a sudden surge in demand during the COVID-19 pandemic. The company, which had already embarked on a 2-5 year project in 2019 to modernize their systems by breaking up their monolith into domain applications, was forced to accelerate this process. The pandemic-induced digital shift led to a significant increase in the eCommerce share of the furniture market. Article, being a digital-only retailer, was faced with a tsunami of orders, equivalent to three months’ worth of Black Fridays. The engineering team had to prioritize protecting customer experience, optimizing order processing, tracking, and fulfillment, and improving communication services to keep customers updated on their orders. The developers also had to navigate complex questions about Apache Kafka, a technology they were using as part of their event-driven architecture.

Nuvo, a hyper-growth Medtech company, is revolutionizing pregnancy care by pioneering the future of connected healthcare. However, this innovation comes with the challenge of ensuring that engineers can access and use streaming data in compliance with regulations. The company's data products, which include wearable bands collecting biosensory data, web services for health practitioners, and AI-powered insights on fetal heart rate, roll out at an impressive rate for a heavily regulated organization. A few years ago, Nuvo completely overhauled and modernized their data infrastructure to accommodate streaming data and applications. They needed a system that could reliably capture and transform 18,000 packets of electro and phonocardiogram per minute, along with other biometric data. However, RabbitMQ did not provide the flexibility Nuvo required.

908 Devices, a Boston-based company that designs and builds portable analytics devices for chemical and biomolecular detection, faced a challenge in improving its operational efficiency. With over 200 employees and 2100 installed devices across 42 countries, the company needed to optimize its internal processes to quickly book orders and reduce delays in customer handoffs from sales to post-sales teams. The sales and field application scientist (FAS) teams required up-to-the-minute, accurate information on orders and customers to coordinate customer communications and meetings. However, they found themselves constantly switching between different systems and navigating manual processes to gather necessary customer data, which resulted in delays in providing timely post-sales support.

Cisco Systems, a leader in IT and networking solutions, acquired Meraki in 2012, a company specializing in cloud-managed network solutions. This acquisition led to a significant increase in leads for the Cisco Meraki sales team. However, the team faced challenges in managing these leads due to their existing lead management system, which consisted of six different legacy systems dispersed across on-premises and cloud-based environments. This system was prone to errors and failed to assign leads from Cisco to the appropriate Cisco Meraki sales reps, resulting in lost opportunities. The sales reps had to manually copy data from emails and paste them into Salesforce Sales Cloud as new opportunities, a process that was both time-consuming and error-prone. The IT and sales teams were often diverted from their core responsibilities to diagnose errors and manually assign them to the appropriate sales reps.

AXDRAFT, an end-to-end contract management software platform, was facing a significant challenge. One of their biggest clients was on the verge of leaving due to the lack of a Slack integration feature in the AXDRAFT platform. The client needed this feature urgently for them to renew their contract. The integration was required to deliver notifications to various channels within the AXDRAFT platform, enabling different teams to receive updates seamlessly in Slack without disrupting their workflows. Furthermore, AXDRAFT realized that they were missing out on potential revenue by not having this integration, as several other clients had expressed their willingness to pay for it. The company was faced with the decision of either developing the solution in-house or seeking external solutions, with the primary requirement being that the Slack integration had to be part of the next product update.

Tactic, a company providing a no-code tool for extracting actionable insights from unstructured data, faced a significant challenge after its launch in 2020. The company's product was quickly adopted by high-growth tech companies, leading to an increased demand for integration with their customers' CRM data. This demand was particularly strong for a native CRM integration, which some customers began to complain about its absence. Tactic recognized that providing such integrations would not only address customer complaints but also accelerate their sales efforts and increase customer satisfaction. However, building these integrations in-house proved to be a daunting task due to the time, cost, and effort required, as well as the need to develop specific expertise for each CRM vendor they wanted to integrate with.

Trustpage, a company that provides B2B SaaS companies with a dynamic Trust Center, faced a significant challenge in their integration strategy. They needed to ensure that their customers' sales teams could securely request and share documents within their CRMs. Additionally, they had to ensure that all teams of their prospects could effectively leverage Trustpage with the tools they were already using. This created an urgency to turn around these integrations quickly. The team began searching for solutions to offload the engineering work for their integration strategy. They needed a solution that met their security requirements, saved substantial engineering resources on each integration, was feasible for their integration use cases, and provided reliable technical and account support.

99 Ranch, the leading Asian supermarket chain in the U.S., was facing challenges in optimizing its online store’s performance in the highly competitive online grocery market. The company had launched its online shop in 2019, allowing customers to do their grocery shopping at their convenience. However, like most e-commerce websites, the challenge was getting visitors to add items to their carts and complete their checkout. The company was also grappling with the issue of how to effectively use coupons to incentivize shopping. The conventional coupon delivery systems were not yielding the desired results, as they were not targeted and were being presented to all shoppers, including those who would have made purchases regardless.

AREA 02, Taiwan's first sneaker trading platform, was facing challenges in escalating its digital transformation. The company aimed to develop personalized multichannel marketing to increase conversion and expand business opportunities. They also wanted to build good customer relationships to increase member purchases. However, they were struggling to create a personalized customer journey based on users' behavior and preferences. The company was also looking to optimize its customer journey map for customer acquisition and provide personalized services to maintain customer interactions. The ultimate goal was to increase the annual growth in gross merchandise volume, return visit rate, and reduce customer acquisition costs.

Better Milk, a Taiwan-based dairy brand, was facing challenges in integrating its offline transaction data with online user engagement data to create a more comprehensive customer profile. The brand was also struggling to enhance customer engagement and maintain its membership base. As the retail industry increasingly moved online, Better Milk needed to boost its online sales and customer loyalty. The brand was also looking to strengthen its collaboration with distributors and industry partners. However, the data from Better Milk’s offline distribution channels was highly dispersed, making it difficult to track offline customer profiles and strengthen distribution partnerships. The brand was using marketing tools that were excessively complicated and dispersed, requiring extra time and human resources to match and analyze data.

BMW Taiwan, a branch of the world-renowned automobile manufacturer, was seeking to enhance its brand awareness and increase social engagement on social media platforms. The company was particularly focused on connecting with potential buyers and existing BMW enthusiasts on Facebook. However, they faced a challenge due to Facebook Messenger’s policy, which only allows fan pages to send promotional content to users who have messaged in the last 24 hours. This policy limited BMW Taiwan's ability to reach out to its audience and engage them effectively. During the 2022 Lunar New Year holiday, BMW Taiwan aimed to launch a series of marketing campaigns on Facebook with the objective of increasing engagement with fans.

BRAND’S Suntory, a leading provider of health, beauty, and wellness supplements in Asia, faced a significant challenge in the wake of the Covid-19 pandemic. The company needed to rapidly undergo a digital transformation to adapt to its consumers’ online browsing and shopping needs. This was a significant shift from their traditional business model and required a comprehensive approach to manage its online channels effectively. Previously, BRAND’S did not have a comprehensive platform to manage its online channels holistically, which limited the overall flexibility and efficiency of its online marketing. The company was in dire need of a solution that could help them manage their online channels effectively, ensure targeted communication, and drive conversions.

Caring Pharmacy, a leading pharmacy chain in Malaysia, was facing a significant challenge in bridging the gap between its offline operations and online platforms. As a predominantly brick-and-mortar business, the company recognized the value in the rich offline data generated by its physical stores. However, integrating this offline data with the online data from its digital channels and generating actionable insights was a complex task. The company's goal was to leverage its offline data for personalized marketing on digital channels and activate offline data in recommendation models, A/B tests, and chatbots to empower users to effortlessly locate products. The urgent need for digital transformation and integration led to Caring Pharmacy's partnership with Appier.

Clarins, a leading global beauty brand, faced challenges in acquiring new shoppers and pinpointing high-value shoppers in an increasingly crowded online shopping market. The brand's lack of a marketing automation tool compounded this challenge, as it needed an efficient way to analyze millions of data signals, including user interests, behavior, and frequency, to identify high-value shoppers and display captivating messages to them at the right time. Additionally, Clarins aimed to maximize revenue from existing campaigns without offering sitewide discounts that could potentially hurt its brand image. The brand sought a strategic approach to convert more online visitors into shoppers, hoping to reach the right shoppers with the right incentive at the right time for a better conversion rate.

Formosa Optical, the largest chain eyewear company in Taiwan, was facing a challenge in integrating its offline and online data to better understand and segment its customers. The company had traditionally relied on offline data to inform its marketing strategy, which was leaving out a lot of online data that could provide insights into customer preferences and behaviors. The company was seeking an effective approach to analyze and segment customers such as high-value customers or inactive customers. Furthermore, due to local regulations prohibiting the sale of certain eyewear products online, most transactions were taking place at physical locations. However, many potential customers were discovering and learning about products on the company’s website. Therefore, Formosa Optical needed a way to track customer actions from online to offline and implement an online-to-offline marketing strategy to personalize customer service.

Funshop, a South Korean e-commerce brand, was looking to enhance its marketing outreach through personalization. In the highly competitive e-commerce industry, personalization has become a necessity for brands aiming to better target and engage their customers. However, to effectively execute personalization, Funshop needed to gather more information about its customers, their behaviors, and interests. The challenge was to find a solution that could engage customers, track their actions across marketing channels, and automatically collect on-site behavior data such as what they searched, viewed, and purchased.

Harvard Business Review Complex Chinese (HBR) has been a long-standing source of leadership, innovation, strategy, and management knowledge. However, with the rise of social apps, HBR faced the challenge of maintaining close contact with its readers and attracting them back to its website. The goal was to increase subscriptions by analyzing traffic data and obtaining reader profile insights. HBR also aimed to personalize engagement via LINE, a popular social media platform, to increase the percentage of return visits and strengthen long-term reader loyalty. The challenge was to build a convenient, easy-to-use reading platform that could offer more informative and useful articles to working professionals, while also leveraging the power of social media for engagement and data analysis.

Shin Kong Life Insurance, a Taiwan-based company with over 60 years of history, was looking to leverage FinTech and AI technologies to enhance its big data analysis and prediction capabilities. The company aimed to build comprehensive customer profiles, target high-potential customers, improve advertising effectiveness, provide personalized interactive marketing, and deeply engage with its user communities to increase brand stickiness. The challenge was to effectively integrate AI technologies into their existing systems and processes to achieve these goals. The company also wanted to expand its customer base and increase sales success rates while ensuring precise customer acquisition.

SK Rent-a-Car, a leading long-term car rental company in Korea, faced challenges in driving conversion and maintaining customer engagement. The company needed to move beyond generic messages to attract its consumers’ attention with personalized engagement and boost satisfaction and conversion rate. The process of renting a car was perceived as tedious by customers, leading to a high bounce rate due to the long application journey. The company needed a solution to engage with on-site customers on a real-time basis to keep them on the website and encourage them to complete the application process.

Toyota Motor Philippines Corporation (TMPC), a subsidiary of Toyota Motor Corporation, was facing two major challenges. Firstly, they were struggling with insufficient site traffic to their 'Here For You' website, a platform where they share virus advisories, virtual engagement options with salespeople and technicians, at-home car maintenance tips, and details about their community support initiatives. This was particularly important as the COVID-19 pandemic unfolded and the company wanted to assure its customers of its continued support. Secondly, despite running several digital marketing campaigns concurrently, the brand was finding it difficult to expand its audience reach while maintaining cost-effectiveness.

ANZ Bank, a leading financial institution in Australia, was faced with the challenge of identifying and rectifying compliance gaps in its processes and products. The bank needed to analyze every single transaction over the past 20 years to uncover lapses, such as incorrect interest rates and fees charged. This was a daunting task as it involved sifting through approximately 10 PB of data. The challenge was compounded by the evolving regulatory landscape in Australia's banking sector, which had become more stringent since 2017. Banks were now required by law to design their products with their customers’ needs in mind and were held accountable for instances of non-compliance. ANZ Bank was committed to acting responsibly and wanted to rectify any mistakes made in the past to build customer trust.

Axis Bank, the third-largest private-sector bank in India, faced the challenge of adapting to the increasing demand for digital banking. With over 20 million customers and more than 4,500 branches, the bank needed to leverage big data and data analytics to boost profitability, manage risk, and improve operations. The shift towards digital banking services required Axis Bank to expedite its transformation to data-driven operations to meet changing customer needs. The bank needed to improve its understanding of the required data and the business problems it could solve. Simply collecting, storing, and managing data without a clear strategy or business objective would not create any real value. The bank also faced scalability challenges with its on-premises systems, which had difficulty integrating with cloud applications and could not facilitate ad-hoc analysis requirements for machine learning and artificial intelligence teams.

104 Corporation, Taiwan’s leading online recruitment solutions provider, was facing challenges due to their legacy cloud tooling and the need for a modern data infrastructure. Despite having access to terabytes of highly valuable, private data, including personal information, engagement details, and transaction information, the company struggled to scale pipeline costs effectively and spent significant resources on maintenance operations. This was slowing their ability to be truly data-driven. Their existing systems were siloed, preventing data teams from gaining relevant, timely insights for informed decision-making. The company was hampered by specialty ETL tooling like EMR and a legacy data warehouse in SAP Sybase that were disparate and complex to scale. As the company continued to expand, the increasing quantity of data became significantly more challenging to manage and utilize.

Acxiom, a customer intelligence company, was facing the challenge of managing and analyzing the increasing volume of data captured by their customers. As digital experiences evolved across various channels and platforms, reaching consumers and meeting their expectations became a moving target. The company helps brands understand people through data, enabling them to create ethical, data-driven solutions that drive business growth through better customer experiences. However, the proper collection and usage of data was becoming increasingly complex. The company realized they needed to migrate to the cloud to scale and support hundreds of billions of transactions a month, while maintaining data privacy and security. The challenge was to continue capitalizing on their long heritage of identity data management in a safe, scalable, and cost-effective manner.

Al-Futtaim, a major economic driver in the Middle East, operates and distributes a wide range of global brands, generating a wealth of data across these brands. However, their legacy systems struggled to provide a unified view of their customer due to data silos and the inability to scale efficiently to meet their analytical needs. Business intelligence was slow, forecasting was not scalable and was limited to classical algorithms, and customer insights were too generalized to affect outcomes faster. Their data teams were unable to maximize the promise of their data due to memory and CPU constraints, outdated libraries, and inflexible tooling. Data analysts had to wait four to six hours for small amounts of data to process, which slowed both time-to-insights as well as time-to-market of new ideas. The extra time, effort, and resources required to redesign, implement, test, and launch data projects added unnecessary costs, created a greater divide between business units, and ultimately slowed innovation.

Arkadium, a leading creator of online games for adults, faced significant challenges in storing and processing large amounts of unstructured and semi-structured data. The company's traditional SQL-based on-premises data warehouses were unable to keep up with the volume of data being processed, which was close to 500GB in just one pipeline. This data was crucial for analyzing user behavior and driving customer monetization, engagement, and retention. Additionally, the company's hyper-growth led to a data swamp with inconsistent data, as each team was independently storing its data in various locations. This was a major challenge for Arkadium, as they needed to unify all data for effective analysis and decision-making.