Clayco, a top design-build construction firm in North America, was relying on manual processes for its operations. The construction industry is often underserved when it comes to data and analytics, and Clayco was no exception. The company had a wealth of data but it was not being leveraged effectively. Reports would take months to compile, if ever, and there was a lot of frustration built up due to past experiences. The company needed a solution to improve how it leveraged its data and to up level its analytics maturity.

Torpedo7, a successful online retailer in New Zealand, was facing challenges with its data management. The company lacked reliable, up-to-date information, which was crucial for decision-making. The decision-makers within the company were unable to effectively communicate their data due to the lack of a suitable platform. Furthermore, they were constantly waiting on 'the data guys' to generate reports, which was a time-consuming process. The company was in need of a solution that could provide real-time updates and a collaborative platform for sharing data.

Federated Media Publishing, one of the largest owned and operated real-time ad exchanges in the world, was facing several challenges. The data they were dealing with was complex and inconsistent across different office locations. This led to an overloaded data management team that was struggling to keep up with the volume and complexity of the data. Additionally, the company needed custom Key Performance Indicators (KPIs) that could provide better insights for executives. The lack of a unified platform for sharing data and automating mundane tasks further exacerbated these challenges.

H&R Block, a global tax services provider, was facing several challenges related to data management and reporting. The company had many disparate sources of information, which made it difficult to consolidate and analyze data effectively. This resulted in a significant amount of time being spent on building reports. Furthermore, the company's leadership lacked critical data insights due to the fragmented nature of the data sources. The need for a solution that could provide a unified view of the disparate data sources and offer greater transparency across teams was evident.

Check Into Cash, a national leader in affordable short-term, small dollar credit solutions, was facing several challenges related to data management and reporting. The company was dealing with an overwhelming number of ad hoc reporting requests. The executives were not receiving reports in a format that was easy to understand and digest. Moreover, it was taking too long for the company to get updates on important metrics. These challenges were hindering the company's ability to make timely and informed decisions.

RelayRides, the world’s largest peer-to-peer car-sharing marketplace, was facing challenges in making sense of their vast amount of data. The manual reporting process was tedious and slow, which hindered the company's ability to make quick, data-driven decisions. The information wasn’t delivered in real time, which further complicated the decision-making process. The company needed a solution that could automate the reporting process and provide real-time insights.

Capco, a leading provider of global business and technology solutions for the financial services industry, was struggling with a lack of visibility into multiple data sources. This resulted in hours of manual reporting that hindered executives’ ability to make informed decisions. The limited view of people data also impacted manpower planning. Capco needed a consolidated view into data that allowed them to look at data as information instead of just raw data.

Rakuten Marketing, a global digital marketing technology and services company, was facing challenges in providing high-level data to its clients and executives. The reported information was often outdated, and the process of gathering and sharing data was too manual. This was a significant issue as Rakuten Marketing places high value on actionable information. The company needed a solution that could provide real-time, accurate data to its clients and executives.

Rapid7, a leading provider of security data and analytics solutions, was facing challenges with their data management. Despite being a data-driven company, they were spending a significant amount of time each month creating recurring reports. This was not only time-consuming but also hindered their ability to innovate and analyze the most relevant data. They needed a reliable data management platform that could integrate seamlessly with their existing systems and provide access to the same data across the organization.

The Positive Group, a financial services company, was facing challenges due to the lack of a centralized data platform. The company was generating data from more than 10 major sources, but had no way to collect, analyze, and access this data in a centralized manner. This lack of data transparency between their headquarters in Adelaide and their branch in Manila made it difficult for leaders to obtain the information they needed to track and streamline interaction between their platform and those of their partnering lenders and financiers.

Before implementing Domo, Walker Edison, a furniture company, was struggling with inventory management. Despite having a strong reputation for quality products, fast shipping, and excellent customer service, the company was frequently out of stock. This was a major concern for their retailer partners. The company attempted to address these issues using spreadsheets, but the task of manually aggregating data from all their disconnected sources quickly became too complex. The company needed a solution that could provide real-time insights into their inventory and supply chain performance.

San Diego Workforce Partnership, one of California’s leading workforce development boards, was struggling with disparate data systems that were difficult to use and integrate. They had to rely on time-consuming manual reporting to manage cases, apply for grants, and meet compliance requirements. This significantly reduced the time left to understand where they could focus their resources for maximum impact. They needed a solution that would allow them to dig deeper into the data and enable the organization’s success.

In 2018, Dr. Coopwood challenged his organization to transform the health system by digitizing the way they deliver health. By incorporating high-tech, innovative medical services and leveraging data in new ways throughout the organization, Regional One Health wanted to prepare the health system to serve the needs of Memphis for decades to come. However, with nearly 200 years of history and nine locations spread across Shelby County, it’s easy to imagine how many disjointed, siloed systems the hospital had in place.

Before implementing Domo, Martinelli’s was struggling with a decades-old legacy ERP system and a spreadsheet-driven planning process. The company had very little insight into its business beyond its financial statements. Over the past ten years, Martinelli’s has digitally transformed operations by implementing new systems such as SAP S/4HANA, Workday Adaptive Planning, and ADP. While these systems helped the company generate more and better data, business users still found it difficult to access that data for driving decisions.

Before implementing Domo, NorthShore Care Supply relied on a combination of internally built dashboards and basic analytics solutions to manage its analytics needs. However, having data stored in many locations and formats made it challenging for NorthShore to analyze its customer needs. The company's rapid business growth found it struggling to keep pace, requiring NorthShore to seek out a more capable BI solution. One of NorthShore’s key customer acquisition tools is its sampling program, which allows customers to try a product to find the right fit before placing an order. However, NorthShore was struggling to effectively track the sampling program and target its marketing communications towards interested prospects.

Velasca, a direct-to-consumer brand, faced several challenges. These included gathering the right data to know who buys which products and when, collecting omnichannel insights from both online and offline channels, managing inventory and adjusting production to meet changing demand, analyzing customer service to gauge customer needs, pain points, and solutions, and monitoring performance marketing to better build and optimize campaigns in real time. Despite having multiple data tools, they struggled with siloed data that couldn't be synced across teams and platforms, manual processes that wasted valuable time and resources, supply chain problems that threatened to interrupt the direct-to-consumer experience, and out-of-date analytics that were not readily available or usable.

Cozy Earth, a company that manufactures sleep products from bamboo, faced challenges in managing its supply chain and forecasting demand. The company's raw materials and final products are supplied from Asia, requiring precise forecasting up to nine months in advance. Over-ordering could tie up valuable cash in unsold products, while under-ordering could result in missed sales opportunities. Prior to implementing Domo, gathering data to inform forecasting was a complex, manual process that involved downloading reports from each separate channel, copying and pasting data into a spreadsheet, and spending hours working with the data before it was ready for use by decision-makers.

The NBA, a global media company, needs to accurately estimate the viewership for every single game to make key decisions, including which games are broadcast on which networks and which games receive advanced promotion. The NBA’s success requires the organization to accurately estimate the viewership for every single game, using that information to make key decisions, including which games are broadcast on which networks and which games receive advanced promotion. The NBA needed more data, and more speed and agility to put it together, so they could gain insights that would help the NBA succeed in an increasingly competitive media landscape.

WKS Restaurant Group, which operates five different restaurant brands across 400 locations, faced the challenge of managing data from disparate sources due to the different operational metrics of each brand. The company needed a solution that could integrate data from various legacy technologies and make it usable for business leaders to understand the commonalities and differences in the business. The company also needed to track its sales and revenue across each brand, regional district, and location. Additionally, WKS wanted to improve its visibility into its costs, such as repair and maintenance budgets, and track the speed and uptime of its internet at each of its locations.

In 2014, Sears Auto Center was facing declining sales and margins. The company had useful operations data, but it was inconsistent, difficult to analyze, and open to misinterpretation. The operations performance, particularly at the regional retail level, was difficult to analyze. Different management layers had different reports, and even shared data was open to misinterpretation. In a competitive business environment, static monthly reporting was not dynamic enough to enable Sears Auto Center to respond to in-market regional trends. When a location’s business was struggling, it was tough to fix things when you couldn’t agree on what the data tells you.

Before Domo, Tipico’s BI department found itself bogged down with roughly 100 ad hoc report requests a month. Each report would take 9-12 hours to create; this unplanned request would not only consume an analyst’s day and distract her from her other work but would also slow down other departments as they waited for their reports. And in an industry where the action moves by the minute, twelve hours is an eternity. Tipico also needed a way to access data on the go through smartphones and tablets. When an executive is attending a match or watching a game at home, she can easily go into Domo to see Tipico’s betting exposure for any game or bet.

Philz Coffee, a coffee chain known for its personalized coffee experience, was struggling with a spreadsheet-driven reporting process that it had outgrown. As the company expanded from a single location in San Francisco’s Mission District to stores throughout California, the Washington D.C. metro area, and Chicago, the need for a more efficient and scalable reporting system became apparent. The company was spending 16 hours a month gathering all sales data into a report, a process that was not only time-consuming but also delayed the availability of crucial data for decision-making. The company needed a solution that would make reporting faster, efficient, and capable of getting into the hands of store leaders.

Traeger Grills, a pioneer in wood pellet technology for barbecuing, was facing a challenge. Despite its innovative approach and global success, the company lacked real-time insights into its business operations. The CEO, Jeremy Andrus, was often waiting for a week or more to receive reports. The company had a wealth of data, but it was scattered across dozens of different sources, making it difficult to gain a comprehensive, up-to-date view of the business. This lack of real-time data was hindering the company's ability to make timely decisions and respond to emerging trends or issues.

Before Domo, Texas Tech Credit Union (TTCU) struggled to leverage its customer data in a way that would allow it to make agile business decisions required to keep pace with customer needs. The credit union had multiple data sources, which could introduce discrepancies. It was hard for people to trust data, and everything took longer. They could get a request for a field or a new piece of information and then have to work for eight hours to bring that piece of data into a visualization because most people don’t want to look at rows and columns. TTCU also had to compete against well-funded national banks, scrappy fintechs, and other local financial institutions, and it had to leverage data if it hoped to break through the noise of the market.

Telus, a Canadian national telecommunications company, was facing a significant challenge in making informed decisions due to a lack of accessible data. The data they needed was stored in disconnected systems, making it difficult to gather and analyze. The process of disseminating information was time-consuming, and building reports took longer than was efficient. The company was in need of a solution that could consolidate their data and provide real-time information to drive decision-making.

SABMiller, a multinational brewing and beverage company, faced challenges in monitoring its brands due to disconnected data sources. The company operates in 80 countries and has over 200 brands, making it difficult to maintain a standardized system for all data assets. The company wanted to create a global, standardized system into which all data assets could be plugged. They also wanted to drill deeper into data for insights into the business.

The Cliffs, a real-estate development and private club company, was struggling with visibility into multiple data sources to track performance relative to targets. The company operates multiple real estate offices and member amenities, including seven luxury private country clubs, seven championship golf courses, five wellness centers, seven restaurants, seven retail shops, and private event venues. The company wanted to reduce the number of manual spreadsheets and hours spent on reporting. They needed a centralized location to view key performance indicators for each department in real time.

Lendio, a company that aggregates lenders into a simple online platform, was facing challenges due to a lack of quality data. The company had limited visibility into multiple data sources, which led to outdated reporting. They needed the ability to look at all data sources in one place to get a real-time view of the business. Additionally, they wanted an option that allowed everyone in the office to create and view reports on their own.

Loveland Planet Aquarium was facing a challenge of scattered data across multiple sources and platforms, including Gateway Ticketing, Facebook, and Google Analytics. The visualizations were scarce and reports were difficult to consume and understand. The information wasn’t available in real time, which was affecting the efficiency and informed decision-making process. They needed a solution to centralize all of their business data in order to quickly provide executives, managers, and directors the information they needed to effectively run the business.

Apria Healthcare, a leading home healthcare organization serving over 1.2 million patients annually, was facing challenges with its sales organization. The company's data environment was siloed, which resulted in limited visibility into real-time sales data. This lack of access to crucial information was hindering the sales team's ability to make informed decisions. Furthermore, Apria needed a solution that was easy to use and could translate complex data into a format that an operational audience could understand and utilize effectively.