Treasure Data Platform Help
Step 1 — Gather context
If references/learnings.md exists, read it first for accumulated platform knowledge.
What do you need help with?
- A. Initial setup — implementation, onboarding, connecting first data sources
- B. Profile unification — identity resolution, merging customer records, parent/child tables
- C. Audience segmentation — building segments, no-code Audience Studio, SQL-based segments
- D. Connectors & integrations — configuring import/export connectors, Integration Hub, 400+ sources
- E. Journey orchestration — customer journeys, triggered campaigns, activation workflows
- F. AI Marketing Cloud — AI Suites (Engagement, Personalization, Creative, Paid Media, Service)
- G. Agent Hub & Treasure Code — AI agents, Marketing Super Agent, agent development
- H. API & SDK — TD API, Audience API, Postback API, LLM API, client SDKs
- I. SQL & queries — Presto/Trino queries, job management, query optimization
- J. Workflow scheduling — Treasure Workflows, DAGs, scheduling jobs, CI/CD
- K. Pricing & plans — Intelligent CDP vs AI Marketing Cloud, "No Compute" pricing, Trade-Up Program
- L. Choosing vs competitors — Treasure Data vs Segment, Tealium, Amperity, Hightouch, RudderStack
- M. Other
Skip-ahead rule: if the user's prompt already contains enough context, skip to Step 2.
Step 2 — Route or answer directly
| If the question is about... | Route to... |
|---|---|
| CRM data deduplication or quality outside TD | /sales-data-hygiene [question] |
| Retargeting/remarketing strategy | /sales-retargeting [question] |
| Connecting TD to other tools (general integration strategy) | /sales-integration [question] |
| Contact/company enrichment | /sales-enrich [question] |
| Lead scoring models | /sales-lead-score [question] |
| Buying intent signals | /sales-intent [question] |
| Email campaign strategy | /sales-email-marketing [question] |
When routing to another skill, provide the exact command: "This is a {problem domain} question — run: /sales-{skill} {user's original question}"
Step 3 — Treasure Data platform reference
Read references/platform-guide.md for the full platform reference — modules, pricing, integrations, data model, workflows, regional endpoints.
If the question involves the API, also read references/treasuredata-api-reference.md.
Answer the user's question using only the relevant section. Don't dump the full reference.
Step 4 — Actionable guidance
You no longer need the platform guide — focus on the user's specific situation.
- Start with the simplest approach — use Audience Studio UI before writing SQL, use pre-built connectors before custom scripts
- Check regional endpoints — TD has separate API base URLs for US, EU, Japan, and Korea
- Test in QA sandbox first — production changes to parent tables or identity rules affect all downstream segments
- Monitor job queue — Presto/Trino jobs share compute; large queries can block others
- Use Treasure Workflows for orchestration — don't schedule individual jobs when a DAG handles dependencies
If you discover a gotcha, workaround, or tip not covered in references/learnings.md, append it there.
Gotchas
> Best-effort from research — review these, especially items about plan-gated features and integration gotchas that may be outdated.
- SQL required for many workflows — Audience Studio handles basic segments, but complex transformations, custom enrichment, and advanced queries need Presto/Trino SQL. Non-technical marketers will need analyst support.
- Postback API is case-sensitive — column names in payload must match table schema exactly (case-sensitive). Mismatched casing silently drops data.
- Legacy compute engine contention — Presto/Hive jobs share resources. Large queries can queue behind others. Schedule heavy jobs during off-peak hours.
- Profile API refresh lag — unified profiles don't update instantly. Allow time for identity resolution jobs to complete before querying the Profiles API.
- Implementation timeline — typical deployment takes 8-12 weeks with implementation partner. Budget $30K-$100K+ for implementation costs on top of licensing.
- "No Compute" pricing — charges are based on unified profiles and events, not queries. But profile count can grow unexpectedly if identity resolution rules are too loose.
- Regional endpoint mismatch — using the wrong region's API URL returns auth errors, not a helpful redirect. Double-check your site (US/EU/JP/KR) in console settings.
- Add-on costs — AI Marketing Cloud suites (Engagement, Personalization, Creative, Paid Media, Service) are separate fixed-annual + consumption-based licenses on top of the CDP.
Related skills
/sales-cdp— CDP comparison and selection strategy across Tealium, Segment, BlueConic, mParticle, Treasure Data/sales-tealium— Tealium CDP — Real-Time CDP, identity resolution, 1300+ connectors/sales-blueconic— BlueConic CDP — profile unification, segmentation, audience activation (mid-market alternative)/sales-data-hygiene— CRM data quality, deduplication, normalization/sales-retargeting— Retargeting and remarketing strategy across ad platforms/sales-integration— Connecting sales tools with webhooks, APIs, Zapier, Make/sales-enrich— Contact and company enrichment across providers/sales-intent— Buying intent signals and prioritization/sales-lead-score— Lead scoring models across platforms/sales-do— Not sure which skill to use? The router matches any sales objective to the right skill. Install:npx skills add sales-skills/sales --skill sales-do
Examples
User prompt: "Our customer profiles are fragmented — website visitors tracked separately from email subscribers and in-store purchases. How do I unify them in Treasure Data?"
Response covers: parent table setup, identity resolution rules (deterministic matching on email/phone, probabilistic on device IDs), data source priority configuration, testing unification in QA sandbox before production.
User prompt: "I need to build an audience of high-value customers who haven't purchased in 90 days and push them to Facebook Custom Audiences"
Response covers: SQL segment definition using purchase history and recency, Audience Studio segment creation, Facebook Custom Audiences connector configuration, sync frequency and match rate expectations.
User prompt: "Our Treasure Data implementation is $200K/year and leadership wants to know if we're getting value. What should I measure?"
Response covers: profile unification rate, audience activation volume, campaign lift from CDP-powered segments vs non-CDP, time-to-insight reduction, connector utilization across the 400+ available, "No Compute" pricing optimization.
Troubleshooting
Profiles not merging correctly
- Check identity resolution rules in parent table configuration — are you matching on the right identifiers (email, phone, customer ID)?
- Verify data source priority order — conflicting values resolve based on source ranking
- Run a test unification on a small dataset in QA sandbox before applying to production
Connector sync failing or data not appearing
- Verify connector credentials haven't expired (especially OAuth tokens for Salesforce, Google)
- Check the job log in TD Console for specific error messages
- Confirm the regional API endpoint matches your TD site (US vs EU vs JP vs KR)
- For Postback API: verify column name casing matches the target table schema exactly
Queries running slowly or timing out
- Check the job queue — other Presto/Trino jobs may be consuming shared compute
- Optimize SQL: avoid SELECT *, use WHERE clauses to reduce scan scope, partition large tables by time
- Schedule heavy analytical queries during off-peak hours
- Consider Treasure Workflows to chain dependent queries instead of running sequentially
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