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.

GE Healthcare, a leading healthcare company, was facing challenges with its existing BI tools. The company had several BI tools within finance, but no single solution supported a self-service model that allowed business users to easily create visualizations, share data, and support transactional level commentary. The existing system was causing internal frustration and required a high dependency on the technology team. Dashboards could take months to build, slowing down the decision-making process. The company needed a solution that could quickly share data and reports on a global scale for mass consumption.

EDP Comercial, a global leader in managing the transition to clean, renewable energy, was struggling with siloed data stuck in multiple departments across separate countries. The sheer volume of the data the company generated was overwhelming for business users when trying to use it to make decisions. The company needed a strategy that would allow it to treat data as the valuable corporate asset it is.

BacklotCars, an online marketplace platform for auto dealers, was looking for a way to collect and integrate data directly into their platform. The company wanted to provide users with easy and instant access to relevant insights to inform their deals, instead of having to request a manual report. The sales staff was using Domo to collect insights which they then shared with their specific auto dealer customers. However, this process still created an extra step of having to create and send out the report.

Life Time, a healthy lifestyle company, was facing challenges in managing its rapid growth across multiple categories while navigating the operational difficulties posed by the pandemic. The company had expanded its digital offerings to include on-demand and live-streaming fitness classes, health talks, virtual coaching, meditation, and in-person class registration on its app. However, it needed a way to analyze the data generated by the app to better understand its members and their goals. Additionally, Life Time was struggling with a complex spreadsheet-driven finance reporting process that was time-consuming and left little time for data analysis.

Grünenthal, a global leader in pain management, was struggling to understand its customers due to patient privacy regulations. The company lacked customer data, making it difficult to know what customers thought about its products and marketing strategies. This lack of data led to a culture where decisions were made based on gut feelings rather than concrete data. Grünenthal needed a solution that would allow it to overcome its data challenges and change its culture.

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.

Before Domo, Intermix had valuable customer data siloed across its marketing department, ecommerce operations, and retail locations. Because data was disconnected, a stylist making a recommendation about a pair of jeans had no visibility into the fact that her customer had been browsing dresses online the day before, which items were sitting in her online cart that she might want to try on, or the effectiveness of online promotions in spurring offline sales. The company struggled with store teams lacking real-time visibility into what items had been sold in a day on the website, often leading to the overselling of available stock and resulting in cancelled website orders.

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.

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.

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.

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.

Before the implementation of Domo, Boyne Resorts faced challenges in accurately tracking the state of the business due to data silos and outdated spreadsheets. The company's understanding of the business was largely based on gut feelings, and by the time reports made their way up to the owner, they were often several months out of date. This lack of real-time data made it difficult for the company to be proactive in its decision-making, often resulting in reactive measures that were not as effective.

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.

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.

Zillow, a widely-used real estate marketplace, was facing challenges with its media business's billing process. The process was manual and inefficient, involving multiple teams and taking approximately 30 hours a month to send out invoices. The company was looking for a solution to streamline this process and reduce the time spent on billing. Additionally, Zillow was interested in exploring other ways to improve its operations, such as analyzing ticketing data and process run times within IT.

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.

Dal-Tile, an international manufacturer responsible for selling one out of every three floor tiles in the U.S., was still run on Excel, with analysts downloading data through Microsoft Access from its data warehouse. After migrating to SAP from its legacy JD Edwards mainframe, the company had hoped to get a better solution in place. Instead, it discovered that it had extremely limited management reporting tools in place. The company was looking for a solution that could automate report creation and delivery that before took days for an analyst to complete. It also wanted to provide mobile access to data.

Edrington-Beam Suntory, a prestigious spirits producer, was struggling with data transparency and efficiency in its sales operations. The company's sales data and pipeline information were siloed, with data being managed through Excel documents and third-party systems like SalesForce and internal CRM tools. This led to sales reports taking up to three days to complete, and the data was often up to a month old. This outdated data caused issues in sales performance, with accounts being lost and sales teams working from late reports. The teams were even duplicating calls due to outdated data, leading to up to 200 more calls being made per year.

7-Eleven Vietnam was operating on multiple discrete retail-specific systems, which made it difficult to streamline operations for long-term growth. The company needed a singular, centralized data platform to gain greater visibility and more rigorous reporting in its data management. The company wanted to link different datasets within a single overarching window into all its data, visualize all data for more intuitive and prompt decision-making, and boost end-to-end efficiencies from logistics to points-of-sale.

ClearScore, a startup launched in 2015, aimed to provide free access to credit scores and reports for everyone. However, as the company expanded internationally, it faced challenges in understanding and interpreting its own data. Daily reporting had become complex and difficult to understand, and the company aspired to be data-driven but lacked a clear path to achieve this goal. The company wanted to make data accessible across the organization, enable self-serve reporting, free up time for data science, and provide a deeper understanding of the business.

Cisco Networking Academy, an education program and platform, had a goal to positively impact one billion lives by 2025 through education around digital technology and its benefits. To achieve this, they needed to constantly build their funnel of students for their online, entry-level courses, and ensure that these students progress into tertiary institutions which can equip them for true career readiness in a digital world. They enlisted the help of digital agency krunch.co to help optimise its marketing and advertising efforts. They aimed to maximise student “return” on marketing spend, improve overall enrolments as well as those in areas of need, and reduce the average cost of each enrolment.

Verivox, a leading independent comparison portal in Germany, needed a solution that could provide accurate, transparent, democratised and easily accessible data from its website and business units. One of Verivox’s main goals was to map the market as closely as possible - a huge challenge given the variety of sectors they cover. To achieve this, it needed constant, real-time access to data, where teams could monitor, report and make decisions that improve customer satisfaction, increase traffic and facilitate internal decision-making. Prior to Domo, Verivox needed to improve its democratised access to all data sourced from the website, third-party data sets and internal management systems. Employees would access different versions of the data sets, limiting transparency and accuracy.

OVO, an Australian telco and media broadcaster, faced a significant challenge in consolidating and interpreting metrics from its two distinct industries. The company lacked a centralized reporting platform that could present these metrics side-by-side and provide meaningful insights. Their previous solution was too basic for their requirements, failing to provide the comprehensive and integrated view they needed to drive business growth. The leadership at OVO recognized the need for a more advanced solution that could consolidate organizational metrics and align reporting in a clear, coherent, and accurate manner.