Before implementing Domo, Fuji Xerox faced significant challenges in visualizing data, which affected its speed and agility in problem-solving. The company was reliant on a Business Intelligence software that was slow and cumbersome, often taking months to solve even the simplest problem. The sales team lacked transparency, often making monthly sales projections without any data to back up their claims. The company also struggled with profitability transparency across its various business lines, including device sales, service click charges, and software.

Mark Brand, a chef, professor, and social impact entrepreneur, runs multiple businesses and advocacy programs aimed at helping marginalized populations reintegrate into society. His restaurant, Save On Meats, has a program where individuals in need can exchange a plastic token for a sandwich. The program has served over two million meals to the community since its launch in 2012. However, with so many programs pressing his time, Mark needed a way to more effectively and efficiently run his core business so he could focus more on expanding his vision. He needed a mobile-first solution to access the statistics and evidence he needs to substantiate his call for change. He also needed a real-time view of what was happening in his Save On Meats business, including metrics around the restaurant’s profitability, from revenue to operational costs, and how it all contributes to the bottom line.

La-Z-Boy, an international furniture manufacturer and retailer, had a challenge managing the data needs of the company due to its vast product variations. The company needed a solution that could raise the visibility of data throughout the organization while making it available for all. The company's CEO emphasized the importance of data-driven decision making, which further necessitated the need for a robust data management solution. The company needed a solution that could integrate data from various departments and provide real-time insights for effective decision making.

Spinach, a full-service agency, was facing a challenge of managing the increasing data input from its clients. The agency was looking for a tool that could help them collate and analyze information efficiently to find valuable insights. They wanted to ensure that their talented consultants weren’t being bogged down in tedious tasks. The agency was in need of better-quality data to predict advertising outcomes and real-time insight to increase productivity.

Modernizing Medicine, a data-savvy organization transforming healthcare information, was facing challenges with their own data. They were wasting resources on duplicated reports by different departments. Additionally, they had non-aggregated data living in separate systems. This was causing inefficiencies and hindering their ability to effectively utilize their data.

Save the Children, a global humanitarian organization, wanted to better leverage data to further advance its goal of driving progress for children globally. They needed a solution that could provide quicker insights into the populations they serve and enable them to be more efficient in how they allocate limited resources. The organization also wanted to communicate essential information and metrics globally in real-time.

Many of the world's wild fisheries are either fully or overexploited, putting stresses on the billions who rely on them for nutrition and livelihood. If nothing is done, this trend will continue, and most of the world's fisheries will be in serious trouble by 2030. EDF worked with Domo to help make this problem visible and build the global movement necessary to transform fisheries to sustainability. They're putting the processes in place to help end hunger and malnutrition and create reliable income while allowing people and nature to prosper together.

D2L, the maker of Brightspace, an EdTech platform, found that its previous BI tool had become an obstacle to generating the insights required to help users and their students achieve all they could. The user experience wasn’t ideal, and they wanted to improve that by picking a new partner that would let them level up the whole product. When evaluating its BI options, the Brightspace platform needed a tool with the flexibility to meet the needs of its wide variety of education and corporate clients around the world. Their criteria around localization, translations, security, access, integration, usability and breadth of features quickly culled their list from every BI tool on the market down to just one: Domo.

JAMF, the world’s largest Apple device deployment company, initially implemented DOMO to address challenges around fall-off within a critical customer journey. The company was looking for a tool that could help them make sense of their complex business and gain faster and more powerful insights to fuel their growth. The initial success of DOMO in resolving a critical customer journey issue sparked interest among the senior leadership, leading to the question, 'what else can we do with DOMO?' This marked the beginning of JAMF's journey with DOMO.

CitrusAd, a leader in the e-commerce retail advertising space, helps retailers incorporate an auction-based advertising platform into their e-commerce operations. This allows brands to more effectively advertise to customers as they browse and search, helping them gain the exposure they need to get added to the cart and helping retailers further monetize their e-commerce operations. However, the company faced challenges in terms of scalability and the ability to extract insights and value out of data. Without a solution like Domo, it would have taken nearly six to twelve months to stand up a comparable solution.

Asure Software, a provider of Human Capital Management (HCM) software for small businesses, wanted to enhance its data science capabilities to better understand its customer health, improve forecast accuracy, and identify and convert prospects more effectively. The company aimed to gain a holistic, 360° view of each customer to reduce churn. However, the company faced challenges in managing and integrating data from various sources, including its CRM Salesforce, DealHub for quote creation, its Deal Software Integration platform for integrating transactions into their ERP NetSuite, Concur for expenses, Rockettrip for gamification of travel expenses, and an Excel-based corporate performance management tool. The company also used external data from Dun & Bradstreet, customer usage data, macroeconomic data, and customer sentiment data from social networks and Zendesk.

Freddy’s Frozen Custard & Steakburgers® has grown from a single location in the heart of the Midwest to nearly 400 locations across the US. The company has a modern approach to data science. However, when Freddy’s first began its data science journey, it struggled with a lack of technology and perspective. After a failed pilot engagement, Freddy’s needed a different partner and a different approach to sell the initiative to its leadership team. The company had to deal with 18 different data sets spanning over 100 different columns of information created for each of the Freddy’s locations at multiple points in time. With so many individual columns of data to consider, store quality was difficult to understand and assess.

ESPN, a global leader in multimedia sports entertainment, was facing several challenges in delivering quality service to its fans. The company needed a way to quickly aggregate customer comments to spot emerging issues with access to ESPN and identify which services were affected before it caused subscriber churn. With a large and growing set of content distribution partners, ESPN wanted to partner more closely with them and use data to engage them on improving service quality levels. Additionally, ESPN wanted to increase convenience for fans by adding additional web, phone, text-based support channels. However, a lack of visibility into existing activity was holding back these new implementations.

Dr. Consulta, a healthcare clinic startup in Brazil, was founded to provide high-quality, low-cost healthcare to Brazilians who often lack access to timely, quality care from their public healthcare providers. However, the company faced challenges in improving the speed and quality of its care due to a spreadsheet-driven process that created a delay in collecting and sharing information. The process of downloading patient satisfaction information, building a spreadsheet, sending it to each medical center for analysis, and waiting for the analysis to come back for a final report would take about 30 days. This delay in data processing and analysis hindered the company's ability to act on critical information like patient satisfaction scores instantly.

Before Domo, TheraSkin often found remarkable differences in information between all its different data sources, with no way to easily identify which, if any, was the correct version. Not only was it time-consuming to collect and verify data, but analysts would then have to spend more hours manually building charts, dashboards, and reports. By the time the data got into the hands of business users, it was often too stale to use effectively.

Swagelok Albany found itself unable to efficiently leverage its business data. Information was spread across multiple systems, which could take hours to collect and process before it could be analyzed. This lack of insight began to impact the customer experience. Swagelok Albany struggled to know whether it had the inventory in place to process a sales order or if its marketing analytics indicated buyer intent based on the web pages a customer spent time on. Sales staff would have to wait for reports to arrive in their inbox before taking action.

Before the implementation of Domo, iPro Systems, the data and analytics arm of Alliance Retail Group, was primarily focused on billing and adjudication. The company desired to share business insights with retailers and vendors, but this proved to be a challenge due to the complexity of the data. This complexity consumed a significant amount of the analytics team’s time and only allowed for limited, intermittent spreadsheet-based reporting. The company needed a solution that could handle the complexity of the data and provide insights in a more efficient and accessible manner.

Before Domo, Torchy’s struggled with a data collection and reporting process that might make sense when running a single food truck, but not a taco empire. The finance team would have to manually collect data across disparate data sources, build reports one by one in Excel, and then send reports out to each store operator. With more than 100 stores to track, the finance team spent all its time on reporting, with limited time left over for analysis.

Sportsnet, Canada’s number one sports network, connects Canadian sports fans with their favorite teams and leagues across various sports by delivering thousands of hours of live games, news, and original content each year across regional and national TV networks, radio networks, digital audio, and online streaming. One of Sportsnet’s fastest-growing products is its direct-to-consumer streaming platform, SN NOW, which provides on-demand access to live events from NHL, NBA, MLB, WWE, Bundesliga, and more. The challenge was to understand what each fan wants so they don’t miss a moment of the action. The company needed a solution to bring all its data together in one powerful visualization solution so business users could access the information they need without effort.

KOKO Networks, a company that is scaling a proprietary technology platform to protect Africa’s forests from the destructive charcoal cooking fuel industry, was facing challenges with its data visualization software. The company was dealing with a large volume of data from three disparate databases, which led to issues with dashboard speed and performance. As the company was growing rapidly, it needed a solution that was easy to use and could be quickly adopted by new team members. Additionally, the solution needed to be affordable and manageable by the analytics department.

In the last five years, Consumers Credit Union (CCU) has grown from $650 million in assets to nearly $3 billion as it began to expand into new markets and offer new products. However, with this growth, it became too complicated and inefficient to use data the same way they did in the past. The organization was filled with mainframe reports, spreadsheets, and dual entry of data. Furthermore, the pandemic had the most significant impact by far to its operations. Executives needed to understand what types of banking services people still needed so it could adequately staff its drive-thru branches, ensure its online banking services were up to the task, and adequately staff its call center during its busiest hours.

Equicapita, a private equity firm with over $300 million in assets under its management, was facing challenges in tracking the success of its diverse portfolio of 13 companies. Each company measured success differently and delivered its reporting in significantly different formats. This resulted in each company spending about three days each month on a manual reporting process that involved collecting data, normalizing it, consolidating it, and then creating reports for the board. The firm was also looking for ways to use data to help the companies under its umbrella work smarter.

Vivint, a leading smart home company in North America, was facing challenges with its sales data management. The company's sales leaders were making decisions based on gut instinct rather than data-driven insights. The sales team was using Excel spreadsheets for data, which were difficult to parse and often ended up in the trash after meetings. Furthermore, there was a lack of trust in the numbers provided by the sales staff, as their individual claims of productivity did not add up to the company's overall growth. The company needed a single source of truth that could standardize data and accurately show the impact each sales staff member has on the bottom line.

World Rugby, the international federation responsible for overseeing the sport, has data coming in from around the world through dozens of systems. Everything from ticket sales to game statistics to TV ratings and social media engagement analytics is brought into Domo to help staff understand its fan base and identify new opportunities for growth. Faced with a growing need to better manage its data so it could improve reporting, World Rugby evaluated multiple business intelligence solutions. World Rugby brings in millions of dollars each year through corporate sponsorships. In turn, it redistributes nearly all that money to the wider rugby community to provide the income national unions need to grow the sport.

Metro-West, the largest independent appraisal firm in the nation, was facing several challenges that were affecting its efficiency and decision-making process. The company was heavily reliant on manual reporting, which was not only time-consuming but also a significant drain on resources. The lack of real-time data was another major issue, leading to slower decision-making. Furthermore, the company was having difficulty leveraging data from disparate sources, which further complicated the decision-making process.

Bohme, a retail boutique, was facing several challenges in its operations. The company lacked a centralized reporting solution, which made it difficult to assess the performance of individual stores. This lack of real-time data insights was also hindering their purchasing decisions. The fast-paced nature of their business, which involves designing, making, stocking, and selling merchandise within 30 days, necessitated a more efficient and streamlined approach to data management.

Scrum, Inc., a company that consults and coaches leading companies across the globe, was facing several challenges related to data management. The data was siloed in numerous systems, spreadsheets, and applications, which limited access to critical data. The existing Business Intelligence (BI) solutions were not able to provide the necessary insights that the company needed for its operations.

WhippleHill faced several challenges in their operations. They were unable to view data from multiple systems in one place, which made it difficult to turn raw data into actionable information. Additionally, the process of reporting was cumbersome and time-consuming. This lack of a unified data view and the difficulty in data interpretation hindered their decision-making process and overall efficiency.

Platinum IDS, a pioneer in outsourced litigation support services, was facing several challenges. The company was struggling to manage a variety of data sources, which was affecting its ability to track metrics in real time. This was a significant issue as real-time data is crucial for making informed decisions and driving business growth. Additionally, Platinum IDS was having difficulty disseminating information across the organization. This lack of effective communication was hindering the company's ability to operate efficiently and effectively.

Litigation Services, a law firm serving several large insurance companies, was facing significant challenges in managing its data. The firm's reporting was static, often resulting in outdated information. Furthermore, the data was not easily accessible to decision-makers, hindering the firm's ability to make informed, timely decisions. The firm needed a solution that would enable it to become truly data-driven, providing real-time insights and facilitating a more proactive, consultative approach with its clients.