WorkRamp powers employee and customer learning for high-growth companies like Airtable, Notion, and Sprout Social. Surfacing data to their customers on course comprehension, completion, and performance had always been crucial to the product, but they relied on a homegrown solution until recently. While their custom-built application gave them complete control over the experience, it was taxing on engineering resources — especially as their customer base scaled.
“Customers expect SaaS platforms to provide in-app reporting, and we’ve offered it from the beginning. However, we always strive to provide our customers with the best, and we never want to compromise on the experience. That’s why we built it ourselves in the first place. But I always hoped to eventually find a vendor who would give us the control we wanted, while taking the burden of analytics development and maintenance off of our team,” explains Arsh Mand, CTO & Co-founder, WorkRamp.
After years of searching for the right partner to help scale their analytics without compromising the experience, WorkRamp rebuilt their customer-facing data product with Omni’s embedded analytics.
Results #
Fast deployment: Relaunched customer-facing data product in less than three months — with zero customer downtime
Improved customer experience: Received positive customer feedback on enhanced flexibility, customization, and AI
Time savings: 10% gain in engineering time previously spent on analytics features, and fewer time-intensive data requests sent to the customer success team
WorkRamp's Data Stack #
The Challenge #
Over the years, WorkRamp invested heavily in building its own customer-facing analytics experience, which included a custom report builder, scheduled deliveries of data, and a foldering system. But as their customer base and expectations grew, so did the strain on the team.
“Every quarter, we received requests for new reporting features. Sometimes we’d take them on, but each feature meant pulling engineers away from our core product.”Arsh Mand, CTO & Co-founder, WorkRamp
Customers continued to ask for more control, including the ability to build their own dashboards. Adding that level of customization would have required a major engineering investment — on top of the time the team was already spending maintaining the existing infrastructure. Additionally, as they supported an increasing number of customers, the customer success team was spending more time on ad-hoc analytics requests, which took time away from more strategic and relationship-focused parts of their role.
To meet these increasing demands, Arsh and the team knew they needed to give customers more flexibility and power, but they were hesitant about giving up the clean, intuitive experience they spent years perfecting.
The Evaluation Process #
The tipping point came when an engineer prototyped new embedded analytics using a third-party tool during a company hackathon. Seeing what was possible inspired the team to revisit the vendor landscape.
“A lot of vendors either took a pure BI-first approach and just tacked on embed features, or they were purpose-built for embedding but lacked depth. We needed a solution with both the robustness of a BI platform and the interactivity of a customer-facing application.”Arsh Mand, CTO & Co-founder, WorkRamp
To evaluate potential solutions, Arsh put together a list of criteria crafted with their customers in mind:
Time to value: Prioritizing a fast launch with no customer downtime
Feature development: Providing customers with the additional customization they wanted, rich features they already knew and loved, and a commitment to continued development — including AI experiences
Governance: A platform with strong governance to allow for secure metrics across customers and easy management across thousands of users
Software development lifecycle controls (SDLC): With thousands of users, it was also important to find an embedded analytics vendor with SDLC workflows, so they could test changes before deploying to customers
Product vision: Beyond current features, Arsh looked for long-term product momentum — evaluating roadmaps, integrations, and APIs to find a platform that would continue to innovate for their customers
Partnership & value: Since this offering would be deployed to thousands of customers, the commercials and vendor team needed to align with their growing business
After looking at several tools, including Looker and Sigma, Arsh and the team decided Omni was the right partner to trust with their customer experience.
“In addition to the vendor’s feature set, I also really cared about the development features they offered. As CTO, it’s crucial to me that we can test changes before deploying to our customers. Omni was the first tool we saw that truly struck the right balance of giving our customers more flexibility, while keeping our team in control.”Arsh Mand, CTO & Co-founder, WorkRamp
The Migration #
WorkRamp’s implementation took just three months, which included building out a comprehensive semantic model to set their customers up for success with data exploration and AI, and to speed up future development.
Arsh and his team set up Omni’s semantic layer to enable a curated, trusted experience for customers to explore. During the implementation, they invested in the details: from how Topics (curated datasets) were grouped to how metrics were calculated, joined, and documented. They allocated the time to design a solid foundation that would facilitate long-term customer clarity and trust.
“We spent about two months deeply focused on the semantic layer. That was deliberate. We wanted every measure, Topic, and column to make sense to our customers. Omni’s semantic layer helps make the end user experience feel clean and intuitive, and it makes AI better too.”Arsh Mand, CTO & Co-founder, WorkRamp
To support the rollout, WorkRamp partnered with Astrodata, a data consultancy specializing in embedded analytics, to advise on early modeling decisions as well as offer guidance throughout the development process.
“Astrodata was a great partner. They helped us think through the right way to structure our data in Omni. Their support helped us accelerate our launch and set us up for long-term success.”Arsh Mand, CTO & Co-founder, WorkRamp
Within three months, WorkRamp was ready to relaunch analytics to its customers — starting with a small group of trusted users and expanding to 100% adoption within a month. Customers experienced no downtime or disruptions, and they were delighted by the updates once they were live.
The Impact #
Exceeding customer expectations #
Once they launched the updated analytics experience, WorkRamp surveyed customers to gather their feedback. The feedback was overwhelmingly positive, including:
“This is great, thank you! I like the visual, you can really customize it.”
“I wish I had this when I signed on, it’s like having a reporting assistant.”
“My statistical brain is firing on all cylinders.”
WorkRamp’s customers, which include admins across learning & development, sales enablement, and customer enablement teams, now get more flexibility to track comprehension, completion, and performance — without needing to file a ticket for customer success or request a new feature.
“We opened up Omni’s full product suite to our customers. Now, they can create and save reports, build dashboards, schedule deliveries of data, and even use AI to ask questions in natural language. We’re able to give them a whole new level of self-service without needing to compromise on the control we had with our homegrown solution.”Arsh Mand, CTO & Co-founder, WorkRamp
Enabling trustworthy data exploration with AI #
For Arsh, one of the most valuable aspects of Omni is what powers the customer experience behind the scenes: the semantic layer. With metric definitions thoughtfully defined and governed in Omni, customers can explore the data however they want, without fear of inaccurate results or introducing risk.
The semantic layer also provides valuable business context to AI, tuning it to the needs and language of their customers. WorkRamp customers are now using Omni’s AI assistant to ask questions and generate reports, and the team plans to further enhance the model with even more context as they learn how their customers are using AI.
“Omni gives our customers power without overwhelming them. And with AI, analyzing and understanding data within our platform is even more accessible to our diverse user base.”Arsh Mand, CTO & Co-founder, WorkRamp
Refocusing internal resources on strategic priorities #
Since launching, WorkRamp has seen a measurable reduction in support volume and engineering time spent on analytics features — saving the equivalent of two engineers per quarter.
“It’s saving us about 10% of engineering time. That means we can focus on our core product and deliver more value to our customers, faster.”Arsh Mand, CTO & Co-founder, WorkRamp
By migrating from a homegrown solution to Omni, WorkRamp unlocked a path to faster innovation — without compromising on design, governance, or user experience.
“Omni gave us everything we needed: a modern UI, a powerful semantic layer, embedded AI, and a thoughtful approach to our customer experience. It finally felt like a vendor we could trust to help us deliver an even better product.”Arsh Mand, CTO & Co-founder, WorkRamp