Deep Insights
Agent
Ask your Ometria data anything. Deep Insights Agent gives retail marketing teams instant access to analytics, insights and strategic intelligence from their complete customer universe – inside the AI tools they already use.
Your data, your questions, your answers.
Deep Insights Agent connects your Ometria data to Claude and Copilot, so your team can query campaigns, customers, and revenue in plain language — and get back answers, charts, and dashboards that reflect how your business actually works.
Your Ometria data, live inside Claude and Copilot. Ask in plain language, get answers where you already work. No exports, no waiting.
Cleaned, normalised, and enriched with your business logic before any question reaches the model. Answers you can act on, not second-guess.
Follow a thread, ask follow-ups as they occur. Get charts, tables, or plain summaries, whichever fits the question.
Prepared data in. Reliable answers out.
Most MCP-style tools pass raw API data straight to the LLM. Deep Insights Agent prepares your data first: cleaned, contextualized, and enriched with your business logic, so every answer is grounded in reality.
Five layers of data preparation, so your answers hold up.
Normalizes source data
Duplicate products, spelling variants, and incomplete attributes are caught and corrected automatically.
No more confidently wrong answers.
Semantically enriches product data
Attributes and order properties are restructured so AI can understand your catalogue.
The AI reads your catalog the way your team does.
Bakes in retail KPI definitions
Retail metrics like AOV, repurchase rate, and lapsed status come pre-configured, alongside your own definitions.
No conflicting numbers across teams or tools.
Loads in business context
The agent is loaded with your business context: priorities, target market, trading patterns, and reporting preferences.
The AI knows how your business runs before you ask.
Strips PII
Names, emails, and phone numbers are stripped before any query runs. The model reads, never writes.
Customer identities never reach the AI.
Use Cases
Everyday reporting
Replace the weekly reporting grind with a single conversation. Pull campaign stats, revenue overviews, product performance, and health checks in one place — in seconds, not hours.
‣ "Show me campaign performance last week vs. the week before"
‣ "Top 10 products by revenue, last 30 days"
‣ "Weekly health check: automation sends and revenue"
Customer intelligence
Understand how your customer base is evolving: lifecycle stages, repeat purchase behavior, high-value profiles, and segment performance.
‣ "How many customers did we acquire, lapse, and win back this year?"
‣ "Profile our top 10% — acquisition channel, first purchase category"
‣ "How did the Superfan segment perform on email in Q1?"
Strategy and optimization
Go beyond describing what happened and start answering what to do next. Model the revenue impact of a discount strategy, identify suppression opportunities, or audit your automation flows – all from a single conversation.
‣ "If we discount after first purchase, what could this push in repeat rate?"
‣ "Which customers should I be suppressing to improve conversion?"
‣ "What does the post-purchase flow look like at node level?"
"I love being able to dig into data I never would have had access to before, and the visuals look even better than the reports we produce ourselves. The time saving is significant too: no more manually pulling data from multiple sources."
