Ask the question directly
No SQL. No ticket. Ask the business question you need answered.
For revenue, marketing, and growth leaders
Ask your data a question. Get an answer you can defend.
Anna turns your existing data into answers you can trace, check, and explain.
Book a CallDoes this sound familiar?
- You need the number before the meeting.
- You’re about to present a number you don’t fully trust.
- The person who can verify it is already working through a backlog.
From question to answer
See how the answer was derived
Review the logic, definitions, and data behind the result.
Present with confidence
Every answer is traceable, so you can verify it before you present or act on it.
Transparent by design
What’s behind the answer
Anna shows the definitions, data sources, and exclusions behind every answer.
Why did pipeline drop in EMEA last month?
EMEA pipeline was $1.24M in August, down 18% from $1.51M in July. Most of the decline came from inbound, which fell from $610K to $390K. Outbound was flat.
Definitions used
- “EMEA” uses the region field on the account, not the owner’s territory.
- Pipeline means open opportunities created during the month, excluding renewals.
Data used
- salesforce.opportunity
- salesforce.account
- dbt model fct_pipeline_daily
Excluded from the answer
41 opportunities with no region set.
Proof in practice
Case Study
From ambiguous questions to qualified answers in minutes
Mitch, a sales and operations leader at a weight-loss telehealth e-commerce business with approximately $100M in ARR, had a problem: Facebook ads performed well at modest budgets, but ROAS dropped sharply as spending increased. He needed to understand why and where to invest next.
Previously, getting answers meant submitting a request to the data team, clarifying the question through back-and-forth conversations, and waiting for custom analysis. A simple exploratory question could also turn into something much bigger, like a dashboard project. After 2–3 weeks of iteration and development, Mitch had a dashboard but still needed an answer to his original question.
His ad agency also struggled with Meta's limited native reporting, making it harder to see what might be driving the decline.
Now, questions that once took hours, days, or even weeks can be answered in minutes.
Domain Methods had already built a BigQuery data warehouse combining historical data from Meta Ads, Google Analytics, Shopify, and the company's CRM. We cleaned and joined the data, added attribution rules, and included cost of goods sold and contribution margin.
Claude was then connected to that data. With some coaching from Domain Methods, Mitch could ask questions on his own and keep digging without involving the data team.
The analysis identified ad types and formats that became less efficient as budgets increased, along with ads stuck in Meta's learning phase. The business reallocated spending across channels, shifted budget to higher-performing ads, and reorganized its campaigns and testing. Mitch also took specific findings and recommendations back to the agency.
“Instead of fretting about if my business questions are worthy of diverting company efforts to address them, now I just ask Anna. She asks me follow-up questions to clarify my intent and then goes to work. And a minute or two later, she has something for me. If that then inspires more exploration, I just ask for it.”
Mitch can now investigate questions as they come up, follow the data where it leads, and make decisions without waiting on a separate analysis project.
This engagement demonstrates the opportunity to build on and customize Anna Lytics, Domain Methods’ analytics agent for Slack. It gives business users a way to ask questions directly of trusted company data and keep exploring as new questions come up.
Questions we often hear
What do we need to have already?
You need usable business data. A warehouse helps, but it is not required. If you need to bring the data together or prepare it first, that can be part of the work.
Which cloud and warehouse does Anna support?
Anna is designed to work with your existing environment. We confirm the data sources, warehouse, authentication, and deployment approach during setup rather than requiring a specific vendor.
Where does Anna run?
Anna is deployed in your environment. Your team decides where it runs and how it accesses the systems it needs.
What happens when our data is sent to an LLM?
You control what data can reach the model and what is anonymized or removed first. Deployment, model connection, and data-handling rules are configured to your requirements.
How long does setup take?
A typical setup takes a few days once access and deployment decisions are in place. We confirm the scope before work begins.