audibene, a rapidly growing hearing care company, was struggling with the volume of data generated by their online tools. They needed a way to effectively track, visualize, and act on their marketing and sales data. Despite using Tableau as their central business intelligence platform, data was still being used and stored in silos across the business via Excel sheets and third-party tools like Salesforce. These third-party solutions lacked the structure and functionality to easily analyze data, leading to low adoption rates across the business. The siloed data also led to longer and more complex decision-making processes. audibene wanted to bring data to the masses and provide greater transparency across departments, but they needed a platform that could help drive adoption rates and self-service usage.

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valuable time and resources, supply chain problems that threatened to interrupt the direct-to-consumer experience, and out-of-date analytics that were not readily available or usable.

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.

Weitz & Luxenberg, a legal services firm, was in need of a business intelligence solution that could deliver more than just data. They needed a solution that could easily fix and connect data, provide self-service for users, offer an easy-to-use interface, integrate data sources without limitations, and turn data into actionable insights. They were looking for a solution that could help them make data-driven decisions, identify bottlenecks, and determine the most effective means of customer acquisition. They also faced challenges with disparate systems and ineffective communication with partner law firms.

Driva, an Australian car financing platform, was struggling with managing and leveraging its data as the company expanded into new product lines and markets. They were collecting data through various sources such as consumer application info, their CRM system, Google Analytics, and their product-based analytics software. However, it became too difficult to reconcile data across different sources or create reports using multiple data sources. They needed a solution that could bring all its business data together into a single source of truth.

NLC Mutual, a member-owned insurance provider serving the reinsurance needs of 28 states, was facing challenges due to the lack of a central business intelligence system. This hindered its ability to leverage data when processing claims and underwriting coverage. Each state has its own systems for claims and underwriting management, making it difficult to collect data in a timely manner. The company was also struggling with collaboration issues with its members due to the lack of a unified data platform. The municipal reinsurance industry is highly competitive, with larger cities often looking for private options to see if they can find better rates compared to the coverage provided by their state. NLC Mutual needed a solution that could help them prove their value to customers and engage in proactive conversations.

North American Properties, a real estate company, was facing challenges in managing its expansive portfolio and planning future projects due to the lack of a unified data system. The company was using its data primarily for reporting purposes, which only provided insights into past performance and did not allow for future projections. The company's properties were using disconnected ERP systems and other siloed data sources, making it difficult to consolidate and analyze data. To address this, North American Properties created a new business intelligence team tasked with leveraging the company’s data across projects and making it actionable.

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.

Penola Catholic College, a co-educational secondary school in Melbourne, Australia, serves a diverse student population of approximately 1,500 students. The school's educators struggled to leverage all the student data at their disposal due to the data being scattered across multiple locations. This made it difficult and time-consuming for educators to collect and synthesize the data in a way that could produce meaningful insights. Without the ability to visualize data and put it in context, educators couldn’t quickly determine which step to take next, which meant at-risk students would fall further behind before they got the help they needed.

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.

Before Domo, the national support centre team at Forty Winks struggled to collect data from its franchisee stores. Some stores used one of two point of sale systems, while others would send in performance data via Excel spreadsheets. Some of their stores are still on manual systems, which required them to fax in data. The eCommerce platform had no reporting capabilities, which meant someone would have to manually total the sales from the order screen. Every week, the operations team would have to collect sales data from 100+ stores and manually input it into a series of spreadsheets. While unwieldy, the byzantine system worked, however, Panagiotou was faced with a choice - keep struggling to do things the old way, or modernize the process.

NRL Mortgage, a company with 80 branches licensed in 48 states, was previously using a BI tool designed specifically for the mortgage industry. While this tool was effective for Loan Origination System (LOS) use cases, it was not capable of leveraging data from other systems such as the general ledger, payroll, or CRM. This limitation prevented NRL Mortgage from making fully informed business decisions. Additionally, the company struggled to accurately track which lead sources generated a positive ROI, making it difficult to know where to invest its marketing time and budget. The company also faced challenges in tracking loan officer performance and managing its headcount effectively.

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.