The Pennsylvania (PA) Office of Attorney General was facing a significant challenge in managing more than 1,000 accounts and hundreds of groups manually. As the organization grew, the IT staff was overwhelmed with the increasing workload of account maintenance. The integration with various versions of MS Exchange was mandatory, with the office utilizing MS Exchange 2003 for approximately 90% of its systems and MS Exchange 2007 for the remainder. The new solution needed to maintain the strict security standards of the governmental entity and not overexpose personal information. The IT team, already busy with other tasks, required a solution that would not be time-consuming in terms of deployment and learning curve. Ideally, the solution would allow end users to self-service and update directory information on their own, relieving the IT team of this responsibility.

Progress Residential®, one of the largest providers of high-quality, single-family rental homes in the U.S., faced several challenges related to the security and availability of Exchange Online. The company needed to detect rogue actors before a data breach could occur and ensure readiness for Office of the Comptroller of the Currency (OCC) audits in a timely manner. The challenge was to maintain the security of their Exchange Online system, detect any suspicious activities, and prepare for audits faster. The company needed a solution that could provide clear insights into activity across Exchange Online, such as changes to user properties, group permissions, server rules, and mailbox access attempts.

Carter’s, a leading children’s clothing brand in America, was facing a significant challenge in managing and analyzing vast amounts of performance marketing data from various sources, including Google SA 360 and Facebook. The team was overwhelmed with the manual task of collecting data using spreadsheets, a process that was not only laborious but also considered low-value. The need for a more efficient approach to manage and process data was evident, as the team sought to understand customer interactions with their campaigns and improve future performance. The goal was to examine specific data points to gain insights into potential and existing customers' behavior.

Dassault Systèmes, a global software company, relied heavily on LinkedIn lead generation forms (LGF) to acquire new customers. They ran high volumes of campaigns from over 20 different markets. The challenge was to convert this campaign information into usable datasets for the sales team, which involved manually collecting and transforming the data. Each dataset had to be downloaded, formatted with tracking, and imported into Adobe Campaign, a process that took more than 10 days to complete. This time-consuming process hindered the company's ability to move quickly. Additionally, the lead forms contained personally identifiable information (PII), which required prioritizing customer security, adding to the complexity of handling the data. With such demanding data complexities, Dassault Systèmes needed a faster and more efficient solution to save time and produce usable, accurate data.

Digital Matter, a digital marketing agency, was grappling with the challenge of managing multiple cross-channel campaigns on various marketing platforms for its clients. The team heavily relied on data to set benchmarks, budgets, and ROI, but the process of gathering and analyzing this data was chaotic and manual, lacking a cohesive system. The consultants at Digital Matter were spending a significant amount of time collecting data and creating static reports, many of which were outdated by the time of the next extraction. The manual process also increased the risk of human error, which further fueled uncertainty in their ability to derive accurate, numbers-driven insights.

Fashionette, a leading retailer specializing in designer handbags for German-speaking markets, was facing a significant challenge in managing and integrating data from over 40 sources. The company's data integration tools were not keeping pace with the rapid business growth. The process of logging into various tools, downloading reports, and manually copying numbers into sheets was tedious and time-consuming. The company sought a solution that would integrate all the data into a single, sophisticated platform that would serve departments across the organization. The goal was to gain a comprehensive view of their entire advertising activities, enabling them to analyze and strategically increase ROI, ensuring the company's continued growth and success.

Havas Middle East, a global agency, had developed a client-facing data platform called Automated Data Analytics Manager (ADAM). ADAM was designed to handle client onboarding, target setting, and reporting. However, the platform lacked advanced tools to automate updated reports across various ad platforms. The team had to manually export CSV files to create reports, a process that was slow, stressful, and prone to errors. They also found it challenging to keep up with the constant changes from various APIs. These issues prompted the team to search for a more advanced platform that could improve data integration and analysis, enabling them to serve clients more quickly and strategically.

The Philadelphia 76ers, a top NBA franchise under Harris Blitzer Sports & Entertainment (HBSE), faced a significant challenge in managing their complex data ecosystems. These ecosystems included online advertising platforms, ticketing systems, and audience engagement data. The data team was tasked with managing and aggregating 130 diverse data sources into an Excel spreadsheet, a process that was chaotic, overwhelming, and time-consuming. It took the team 10 hours a week just to extract the data and up to a few weeks to connect to a new data source. The urgency of this task was further amplified by the fixed timelines of the events-driven industry, necessitating the ability to pull and manage data quickly.

IKEA, a global home furnishing chain, was grappling with an outdated and siloed data process. The company was manually managing large amounts of data from various sources, services, and agencies, which was labor-intensive and inefficient. This data included not only the usual localized website and sales data but also crucial customer data from the IKEA Family Loyalty program. The data team aimed to disseminate this data across the organization, allowing other departments such as finance and e-commerce to gain access. However, the existing process made it challenging to turn this vision into reality. The company needed a solution that would establish data and facts as the foundation to accelerate and enhance IKEA’s overall growth.

Infobip, a global leader in omnichannel communication, was struggling with manual data collection processes. The growth marketing team was spending valuable time gathering information for lead acquisition and conversion reporting from Google Analytics and various ad platforms such as Facebook, LinkedIn, and Google. As a global company, Infobip’s marketing analytics required two advertising accounts with Facebook in different currencies, making it difficult to gain a holistic view of their advertising spend. The lack of a data platform that could automatically pull the data and provide reports led the team to rely on outdated spreadsheets to merge the aggregated data. This process required the support of Infobip’s business intelligence (BI) data engineers, who invested 10 to 15 hours a month just to consolidate and turn the information into usable datasets. The company needed a data integration solution that would eliminate such manual efforts, that could collect data from website analytics and ad platforms and push it to the company-wide BI tool Qlik Sense.

Mediahub, a leading global media planning and buying agency, was grappling with the stress of creating data reports and analyzing performance for its global clients. The agency's growing data was scattered across various advertising platforms, making it difficult to manually keep up with API changes that required constant monitoring and updating. These API connectors often broke, causing delays and requiring data engineers to spend time and effort fixing them. Despite having a full-time engineer to develop an in-house solution, Mediahub needed to automate the data acquisition and management process to alleviate the frustration and inefficiencies.

ODLO, a global retailer specializing in sports clothing, was facing a significant challenge in tracking and analyzing the performance of their marketing campaigns across various online channels and international retail stores. The team was manually collecting data from disparate marketing tools, a process that was not only time-consuming but also prone to errors. The lack of a consolidated data solution made it difficult to clean, prepare, and report the data, thereby weakening the team's ability to accurately predict return on investment (ROI). The absence of a unified platform for data management was hindering their operational efficiency and decision-making capabilities.

Seven.One Entertainment Group, a German-based innovator in the ad tech industry, was managing over 100 marketing campaigns involving siloed sources of data, including TV, Google and Bing search ads, print, and social channels. The team was manually gathering and breaking down the information using spreadsheets and PDF files, a process that was not only time-consuming but also made it difficult to examine results quickly. Reports were only issued once a week rather than daily, and the company lacked an accurate, overall view across online and offline campaign strategies, leading to uncertainty in decision-making.

Superbet, a leading sports betting and gaming operator, was facing challenges in measuring the effectiveness of their marketing efforts due to the lack of a dedicated marketing data team. They were using various platforms for their operations, but tracking and updating across these platforms was proving to be time-consuming and at times, impossible due to limited resources. The company operates across multiple geographies, with localized campaigns in place across various channels. Therefore, being able to track, analyze, and improve their marketing programs was crucial for their continued growth. The challenge was to find a solution that could streamline their process, improve the speed and accuracy of their marketing data and analysis, and save time.

UPC Switzerland, a dominant player in the telecommunications sector, was struggling with the collection and understanding of large amounts of data from various channels and platforms. The team lacked an automated platform to manage the information, resulting in a tedious process of copying and pasting sales and marketing performance data into individual spreadsheets. The company wanted to issue accurate, updated reports to understand campaign performance rather than spend time and resources on manual data processes. The challenge was to find a solution that could automate and streamline the data management process, enabling the team to focus on analyzing the data and making informed decisions.

Apollo, a sales intelligence and engagement platform, was seeking ways to enhance their conversion rates. They identified that incorporating user behavior data into their strategies could significantly improve their results. However, the challenge was to make this data more accessible and usable for their go-to-market and operations teams. The company needed a solution that would allow them to experiment and iterate with different product data, precisely time their outreach based on in-app user behavior, and identify product qualified leads that reflect both Apollo’s business needs and the customer’s segment and funnel stage.

Boll & Branch, a luxury home goods retailer, was seeking to enhance its direct mail campaigns by incorporating the level of customer segmentation typically seen in email marketing. The company, which sells its artisanally crafted bed linens through both ecommerce and retail locations, was looking for a way to get data from its warehouse to PebblePost, a platform that enables the creation of highly targeted direct mail campaigns. The challenge was to find a solution that could streamline this process, enrich user profiles for both direct mail and email marketing, and save time for the data team.

Clockwise, a SaaS productivity tool, was facing a significant challenge in getting product usage and engagement data to its go-to-market teams. The process of setting up data for segmentation growth experiments was time-consuming, often taking weeks to complete. This delay was primarily due to the long data engineering queue. The lack of real-time data syncing was hindering the company's ability to conduct growth experiments promptly and efficiently. Furthermore, the absence of granular user segmentation was limiting the company's capacity to personalize onboarding communications, which is crucial for enhancing user experience and engagement.

Screencastify, a company founded in 2013, is committed to providing the simplest possible user experiences for its primary user base, which includes educators and students. The company helps over 15 million users to record, edit, and share asynchronous video. However, the team at Screencastify was facing a significant challenge. They were spending hours of engineering effort on building and maintaining custom API integrations. This not only consumed valuable time and resources but also delayed the access to critical data necessary for a product-led company. The challenge was to find a solution that could automate this process, save engineering hours, and provide quicker access to the essential data.

Smartify, a consumer app company that connects customers with art through virtual tours, on-demand content, and online booking, was in search of a customer data platform (CDP) to support marketing personalization. The company's primary goal was to enhance its marketing strategies by personalizing product usage emails and other marketing materials. However, they soon realized that the implementation of a CDP would consume a significant amount of development time, potentially wasting up to six months. This posed a significant challenge as it would not only delay their marketing efforts but also increase their operational costs.

Spreedly, a global payments orchestration platform, was facing a challenge in personalizing their customer outreach. The company wanted to base their communication on actual customer actions and needs, rather than relying on default timelines. This approach required a responsive workflow that could drive personalized communication effectively. The challenge was to develop a system that could sync models from Looker to Salesforce, operationalize product usage data to Salesforce, and increase conversion on trial emails using personalized behavioral data synced to Pardot.

Wistia, a video hosting platform that aids businesses in creating, managing, and measuring videos, was facing a significant challenge in transferring data from its main application into Salesforce through a custom integration. This process was proving to be a major drag for the company, causing friction and delaying the delivery of crucial data to the business team. The challenge was not only in the transfer of data but also in the accessibility of product usage information. Salespeople had to navigate through multiple systems and learn SQL, a programming language for managing data, to access this information. This situation was not only time-consuming but also required a certain level of technical expertise.

Zip, a global 'Buy Now, Pay Later' company, was facing challenges in unifying their audience segmentation. They were struggling to deliver consistent customer experiences across all channels, including their app and Braze, a customer engagement platform. The company was also unable to build granular segments and target specific user subsets due to limited access to their Customer 360 data. This was a significant issue as Zip integrates with thousands of merchant partners including Amazon, Best Buy, eBay, and Uber, and serves millions of consumers. The lack of a user-friendly interface for segmentation and syncs was another challenge, which increased manual work for analytics engineers and made it difficult for non-technical users to build and sync trusted customer lists.

Jaguar Freight Services, an international transportation and logistics company, was facing a significant challenge in customer integrations. Despite having a talented in-house development team, the process of integrating customers was taking longer than expected, diverting the team's focus from other crucial development projects. This delay was causing frustration among customers who were not only waiting for integrations but also for other functionalities that were put on hold due to the complex integration projects. The company's President and CEO, Simon Kaye, recognized this issue and sought a solution that would speed up customer integrations without compromising other development tasks.

Janel Group, a mid-size customs brokerage and freight forwarding company, was facing challenges with its outsourced integrations. The company had always relied on external partners for integrations, but these partners were not able to respond quickly or guarantee smooth projects. This was affecting Janel Group's ability to respond to its customers in a timely and efficient manner. The company did not have any internal developers and needed a reliable partner to manage its integrations and improve its customer response time.

John S. Connor, a global logistics company, was facing significant challenges due to its reliance on a legacy transportation management system (TMS). The outdated system was causing difficulties in integrating with customers who were using more modern systems. This lack of integration was impacting the company's ability to provide timely visibility to its customers. The situation was further complicated by the varying levels of technological sophistication among their customers. Some customers had their own internal development teams, others relied on external supply chain integration partners, while some had no technological support at all. John S. Connor had previously attempted to work with another integration partner, but progress was slow and customer service was being adversely affected.

Ligentia Global, a technology-focused Freight Forwarding Firm based in Leeds, UK, was facing a significant challenge in managing the data flow from their Transportation Management System (TMS) to their Warehouse Management System (WMS). The company, which provides a range of services including air, road, rail, and sea freight management, as well as warehousing, was struggling with disparities in the quality and file type of data ingested from various customers. This required custom development for nearly every customer and every job, leading to inefficiencies and delays in their shipping and receiving processes. The challenge was to streamline these processes without any risk of missed requests, while also providing their customers with complete visibility 24/7 and relaying complex data in simple and easy-to-understand formats.

Magnate Worldwide, a global freight forwarder and customs brokerage based in Portland, OR, was grappling with two significant systems-related issues. Firstly, the executive and operational teams were finding it increasingly challenging to manage their business due to the need to access multiple different systems for an overview. This fragmentation was negatively impacting their efficiency and decision-making capabilities. Secondly, their customers, who were dealing with disparate data sources and platforms, were seeking a unified view of their data. The lack of a single, comprehensive system was causing frustration and inefficiencies, both internally and for their customers.

OIA Global, a supply chain management company offering global logistics and packaging optimization services, faced a significant challenge in providing a top-tier visibility experience to its customers. The company wanted its customers to have real-time information about the exact location of their shipments and their estimated arrival times. However, the task of gathering data from multiple sources, which often changed over the course of a shipment, and centralizing it into a single, user-friendly platform proved to be a daunting task. Additionally, the company had to deal with constant updates from technology partners, which were difficult to track and accommodate.

ABSA Group Limited (ABGL), a leading financial services group based in South Africa, was facing challenges with its data infrastructure. The infrastructure, which consisted of two data warehouses and a complex series of extract, transform, and load (ETL) processes, was not only costly to operate but also time-consuming in delivering data to business analysts. Recognizing the need for improvement, ABSA decided to modernize its data ecosystem and embrace a big data strategy. However, during the modernization process, ABSA encountered difficulties in ensuring the continuity of business operations. The company needed a data abstraction layer between the legacy systems and the new strategic platform to continue building out the new platforms without disrupting business processes.