a demo
01 - Why switch
The tool isn't the problem. The gap is
Most teams do not switch data tools because the old one failed. They switch because getting from question to answer keeps taking more tools, more tickets, and more time than the business can afford.
At most companies, a business user who needs a number has to file a ticket, wait for priortization, hope the analyst interprets the question the way they meant it, and review a result that often arrives too late to matter. The data team isn't the problem, but they become the bottleneck.
Three patterns show up consistently in the companies that use Supper:
The ticket queue
Someone in sales needs a number by end of day. They file a request. The data team — already stretched across three priorities — gets to it by Thursday. The decision already got made, with a gut feeling instead of a number.
Dashboards for last quarter's questions
Your dashboard library is impressive. It also answers questions from six months ago. Every new question either waits for a rebuild or gets answered with a screenshot from someone's personal Looker tab.
Three reports, three answers
Sales says MRR is up. Finance says it's flat. The data team is pretty sure both are wrong. Nobody agrees on the definition, so nobody trusts the numbers. Decisions get made on instinct and defended with whichever number looks best.
What changes when you switch
Not just "it's faster." Here's specifically what changes, for whom, and why it sticks.
The answer in the time it takes to ask the question.
The answer in the time it takes to ask the question. Anyone on your team can ask Supper a question in plain language and get an answer in seconds — without opening a ticket, without knowing SQL, without waiting for a dashboard rebuild. The question-to-answer gap closes from days to under a minute.
Your team stops being a bottleneck.
When business users can answer their own questions, your data team stops spending 60% of their time on ad hoc requests. They spend it on the work that actually requires their expertise — building the semantic model, improving data quality, driving the analytics roadmap.
Your team stops being a bottleneck
When business users can answer their own questions, your data team stops spending 60% of their time on ad hoc requests. They spend it on the work that actually requires their expertise — building the semantic model, improving data quality, driving the analytics roadmap.
The ROI shows up fast
Supper replaces or consolidates multiple tools in your existing data stack. Setup in days, not months. Value measurable from week one: time saved, tickets eliminated, decisions made faster. Most customers see $100K+ in annual savings on legacy data stack costs."
My ops team used to file two or three tickets a week for numbers I needed before a meeting. Last quarter, they filed zero. They just ask Supper. The data team is shipping projects again instead of answering questions about CAC.
Maya Kothari · VP Revenue Operations
Ramp
The real questions teams ask before they switch
We've heard them all. Here are honest answers.
02 - Run a pilot
A Supper pilot runs for four weeks. By the end, you'll have a working semantic model, a group of live users who've asked real questions, and a clear picture of what full rollout would look like. No sandbox. No synthetic data. The real thing.
We define what success looks like at the start — together. At week four, we review the results honestly. If it worked, we talk about full rollout. If it didn't, we tell you why and what would need to change.
What happens during the four weeks
Connect and configure
We connect Supper to your data sources — warehouses, SaaS tools, databases. Our team handles the technical setup. Your team provides credentials and a point of contact. Most connections are live within a day.
Build the semantic model
Our team works with yours to encode your business logic — metric definitions, key entities, edge cases. You review and approve everything before it goes live. Typical time commitment from your team: 3–5 hours across two weeks.
Pilot users go live
A selected group of business users — typically 5–15 people across 2–3 teams — start asking real questions. We monitor for gaps in the semantic model, tune as needed, and track usage.
Review against success criteria
Defined upfront with your team. We review the results honestly — if it worked, we talk full rollout; if it didn't, we tell you exactly why.
We do the heavy lifting. You make the calls
The asymmetry is intentional. Six things on our list, four on yours.
Supper handles
Technical setup and data source connections
Initial semantic model configuration
Business logic encoding and documentation
User onboarding and training materials
Monitoring and tuning during the pilot
Reporting on usage and outcomes at week four
Your team does
Provides credentials and data access
Reviews and approves the semantic model
Nominates pilot users
Gives feedback on answer quality
Ready to see it on your data? Most pilots start within a week of the first conversation
Start a pilot03 - Migrate
Full rollout follows the same pattern as the pilot — we lead, you approve. Your existing data infrastructure doesn't change. What changes is who has access to it and how they ask questions.
We work in phases so your team isn't asked to validate everything at once. Nothing gets turned off until you've confirmed the new setup is working correctly alongside it.
Migration phases
Data connection + credentials
Every data source connected, schemas documented, access configured. Supper's team owns this end to end.
Semantic model + business logic review
The pilot model gets extended to cover your full data surface. Your data team reviews in stages, not all at once.
Dashboard recreation + user training
Existing dashboards that matter get rebuilt in Supper. Ones that don't get retired. Users onboarded in small cohorts — not a company-wide training day.
Parallel run + validation
Supper runs alongside your existing tools. Answers get compared. Discrepancies get investigated and resolved. Nobody is asked to trust a new tool before they've verified it.
Cutover + decommission old tools
Old tools get turned off on a timeline your team controls. There's no hard deadline forced by us.
What you keep.
Your data warehouse
Supper queries your existing warehouse. Nothing moves, nothing gets copied into a new environment. Your warehouse is still your warehouse.
Your permissions and governance
Every permission and access control you've already set up is inherited by Supper. If someone can't see a table today, they can't query it through Supper tomorrow.
Your existing team workflows
Supper adds a layer on top of your stack — it doesn't reroute it. Existing pipelines, existing processes, existing tools that aren't being replaced: untouched.
We do the heavy lifting. You make the calls
I used to wait days (or sometimes weeks!) for answers from the data team. It's a life changer to be able to get the data I need in minutes now.
Kate · CSM
Fintech · Switched from manual spreadsheets
01 - Why switch
The tool isn't the problem. The gap is
Most teams do not switch data tools because the old one failed. They switch because getting from question to answer keeps taking more tools, more tickets, and more time than the business can afford.
At most companies, a business user who needs a number has to file a ticket, wait for priortization, hope the analyst interprets the question the way they meant it, and review a result that often arrives too late to matter. The data team isn't the problem, but they become the bottleneck.
Three patterns show up consistently in the companies that use Supper:
The ticket queue
Someone in sales needs a number by end of day. They file a request. The data team — already stretched across three priorities — gets to it by Thursday. The decision already got made, with a gut feeling instead of a number.
Dashboards for last quarter's questions
Your dashboard library is impressive. It also answers questions from six months ago. Every new question either waits for a rebuild or gets answered with a screenshot from someone's personal Looker tab.
Three reports, three answers
Sales says MRR is up. Finance says it's flat. The data team is pretty sure both are wrong. Nobody agrees on the definition, so nobody trusts the numbers. Decisions get made on instinct and defended with whichever number looks best.
What changes when you switch
Not just "it's faster." Here's specifically what changes, for whom, and why it sticks.
The answer in the time it takes to ask the question.
The answer in the time it takes to ask the question. Anyone on your team can ask Supper a question in plain language and get an answer in seconds — without opening a ticket, without knowing SQL, without waiting for a dashboard rebuild. The question-to-answer gap closes from days to under a minute.
Your team stops being a bottleneck.
When business users can answer their own questions, your data team stops spending 60% of their time on ad hoc requests. They spend it on the work that actually requires their expertise — building the semantic model, improving data quality, driving the analytics roadmap.
Your team stops being a bottleneck
When business users can answer their own questions, your data team stops spending 60% of their time on ad hoc requests. They spend it on the work that actually requires their expertise — building the semantic model, improving data quality, driving the analytics roadmap.
The ROI shows up fast
Supper replaces or consolidates multiple tools in your existing data stack. Setup in days, not months. Value measurable from week one: time saved, tickets eliminated, decisions made faster. Most customers see $100K+ in annual savings on legacy data stack costs."
My ops team used to file two or three tickets a week for numbers I needed before a meeting. Last quarter, they filed zero. They just ask Supper. The data team is shipping projects again instead of answering questions about CAC.
Maya Kothari · VP Revenue Operations
Ramp
The real questions teams ask before they switch
We've heard them all. Here are honest answers.
02 - Run a pilot
A Supper pilot runs for four weeks. By the end, you'll have a working semantic model, a group of live users who've asked real questions, and a clear picture of what full rollout would look like. No sandbox. No synthetic data. The real thing.
We define what success looks like at the start — together. At week four, we review the results honestly. If it worked, we talk about full rollout. If it didn't, we tell you why and what would need to change.
What happens during the four weeks
Connect and configure
We connect Supper to your data sources — warehouses, SaaS tools, databases. Our team handles the technical setup. Your team provides credentials and a point of contact. Most connections are live within a day.
Build the semantic model
Our team works with yours to encode your business logic — metric definitions, key entities, edge cases. You review and approve everything before it goes live. Typical time commitment from your team: 3–5 hours across two weeks.
Pilot users go live
A selected group of business users — typically 5–15 people across 2–3 teams — start asking real questions. We monitor for gaps in the semantic model, tune as needed, and track usage.
Review against success criteria
Defined upfront with your team. We review the results honestly — if it worked, we talk full rollout; if it didn't, we tell you exactly why.
We do the heavy lifting. You make the calls
The asymmetry is intentional. Six things on our list, four on yours.
Supper handles
Technical setup and data source connections
Initial semantic model configuration
Business logic encoding and documentation
User onboarding and training materials
Monitoring and tuning during the pilot
Reporting on usage and outcomes at week four
Your team does
Provides credentials and data access
Reviews and approves the semantic model
Nominates pilot users
Gives feedback on answer quality
Ready to see it on your data? Most companies start asking questions within 24 hours.
Start a pilot03 - Migrate
Full rollout follows the same pattern as the pilot — we lead, you approve. Your existing data infrastructure doesn't change. What changes is who has access to it and how they ask questions.
We work in phases so your team isn't asked to validate everything at once. Nothing gets turned off until you've confirmed the new setup is working correctly alongside it.
Migration phases
Data connection + credentials
Every data source connected, schemas documented, access configured. Supper's team owns this end to end.
Semantic model + business logic review
The pilot model gets extended to cover your full data surface. Your data team reviews in stages, not all at once.
Dashboard recreation + user training
Existing dashboards that matter get rebuilt in Supper. Ones that don't get retired. Users onboarded in small cohorts — not a company-wide training day.
Parallel run + validation
Supper runs alongside your existing tools. Answers get compared. Discrepancies get investigated and resolved. Nobody is asked to trust a new tool before they've verified it.
Cutover + decommission old tools
Old tools get turned off on a timeline your team controls. There's no hard deadline forced by us.
What you keep.
Your data warehouse
Supper queries your existing warehouse. Nothing moves, nothing gets copied into a new environment. Your warehouse is still your warehouse.
Your permissions and governance
Every permission and access control you've already set up is inherited by Supper. If someone can't see a table today, they can't query it through Supper tomorrow.
Your existing team workflows
Supper adds a layer on top of your stack — it doesn't reroute it. Existing pipelines, existing processes, existing tools that aren't being replaced: untouched.
We do the heavy lifting. You make the calls
We switched from [Tool X] after three years on it. I expected six months of pain. The pilot was live in two weeks, the rebuild took six, and we cut the old tool off on schedule. The biggest surprise was how much of the work Supper's team did before our data team had to weigh in.
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Daniel Rojas · Head of Data
Mercury · Switched from Looker