| name | sales-cdp |
| description | CDP comparison, selection, and implementation strategy — Customer Data Platform evaluation across Tealium, BlueConic, Segment, Treasure Data, mParticle, RudderStack, Hightouch, Amperity. Use when choosing between CDPs, evaluating whether you need a CDP, customer data is scattered across dozens of tools, profiles aren't unifying across channels, you need real-time audience activation, comparing composable vs bundled CDP approaches, or planning a CDP implementation. Do NOT use for platform-specific CDP setup (use /sales-tealium, /sales-blueconic, /sales-treasuredata, /sales-rudderstack, or /sales-mparticle) or CRM data cleanup without a CDP (use /sales-data-hygiene). |
| argument-hint | [describe your CDP question or selection criteria] |
| license | MIT |
| version | 1.0.0 |
| tags | ["sales","cdp","data-platform","strategy"] |
CDP Comparison & Selection Strategy
Step 1 — Gather context
If references/learnings.md exists, read it first for accumulated knowledge.
-
What's your primary goal?
- A) Choosing between CDPs (evaluation/comparison)
- B) Deciding if I even need a CDP
- C) Planning a CDP implementation
- D) Unifying customer data across channels
- E) Activating audiences to ad platforms, email, CRM
- F) Setting up real-time personalization
- G) Warehouse-first / composable CDP approach
- H) Other — describe it
-
What's your technical maturity?
- A) No data infrastructure — starting from scratch
- B) Basic analytics (GA, Mixpanel) but no unified profiles
- C) Data warehouse exists (Snowflake, BigQuery) but not activated
- D) Current CDP that we want to replace
- E) Homegrown system we've outgrown
-
Who will own the CDP?
- A) Marketing team (need no-code/low-code)
- B) Engineering team (API-first, developer tools)
- C) Data team (SQL, warehouse, dbt)
- D) Cross-functional (marketing + engineering + data)
-
What's your scale?
- A) Under 100K monthly active users
- B) 100K-1M MAU
- C) 1M-10M MAU
- D) 10M+ MAU
Skip-ahead rule: if the user's prompt already contains enough context, skip to Step 2.
Step 2 — Route or answer directly
| Problem domain | Route to |
|---|
| Tealium-specific setup or config | /sales-tealium {user's question} |
| BlueConic-specific setup or config | /sales-blueconic {user's question} |
| Treasure Data-specific setup or config | /sales-treasuredata {user's question} |
| RudderStack-specific setup or config | /sales-rudderstack {user's question} |
| mParticle-specific setup or config | /sales-mparticle {user's question} |
| CRM data dedup without a CDP | /sales-data-hygiene {user's question} |
| Email marketing strategy | /sales-email-marketing {user's question} |
| Retargeting ad strategy | /sales-retargeting {user's question} |
| Contact enrichment | /sales-enrich {user's question} |
When routing, provide the exact command.
Step 3 — CDP comparison reference
Read references/platform-guide.md for the full CDP comparison — positioning, feature matrices, pricing guidance, decision frameworks, implementation timelines.
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 comparison reference — focus on the user's specific situation.
Decision framework (quick version):
- Marketer-first, no-code segmentation, mid-market: BlueConic
- Enterprise, 1000+ integrations, tag management heritage: Tealium
- Enterprise, AI/ML-native, 400+ connectors, heavy SQL: Treasure Data
- Developer-first, quick implementation, warehouse-centric: Segment
- Mobile-first, SDK-focused, gaming/media apps: mParticle
- Open-source, self-hosted, full control: RudderStack
- Warehouse-native activation (reverse ETL): Hightouch
- Identity-focused, retail/hospitality: Amperity
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 pricing that may be outdated.
-
CDPs don't fix bad data — if your source systems have duplicates, missing fields, or inconsistent formats, the CDP will unify garbage. Clean data at the source first (use /sales-data-hygiene).
-
Identity resolution quality varies wildly — duplication rates of 10-30% are common across CDPs. Test identity resolution with your actual data in a POC, not just vendor demos.
-
"Real-time" means different things — event ingestion may be fast but profile updates or downstream activation may lag by minutes or hours. Test end-to-end latency, not just ingestion speed.
-
Implementation takes 2-6 months for enterprise CDPs — Tealium and Treasure Data require careful planning and often professional services. Segment and RudderStack can POC in days.
-
Event-based pricing catches enterprises off guard — high-volume sites can see costs spike unpredictably. Negotiate volume commitments and overage caps upfront.
Before recommending a specific platform skill
This skill covers a strategy domain across many platforms. Before pointing the user to any specific platform skill (any /sales-{platform} listed in ## Related skills, e.g., /sales-mailshake, /sales-klaviyo, /sales-apollo), read that platform skill's actual SKILL.md first. The 1-line description in ## Related skills is enough to identify a candidate — it's not enough to commit to it or to write a prompt that invokes it well.
How to read it:
- If
~/.claude/skills/{skill-name}/SKILL.md exists locally, Read it.
- For
sales-* skills, WebFetch directly from this repo: https://raw.githubusercontent.com/sales-skills/sales/main/skills/{skill-name}/SKILL.md — e.g., for sales-mailshake: https://raw.githubusercontent.com/sales-skills/sales/main/skills/sales-mailshake/SKILL.md.
- For non-
sales-* skills (third-party), look up {org}/{repo} in ~/.claude/skills/sales-do/references/skill-sources.md if installed and fetch the same skills/{skill-name}/SKILL.md path under that repo.
After reading, ground your recommendation in something concrete from the SKILL.md (its scope, a sub-flow, its argument-hint shape, or a "Do NOT use for..." negative trigger). Align any generated invocation with the platform skill's argument-hint. If the platform skill turns out not to fit the user's situation, swap to another or handle the question here directly rather than recommending a poor fit.
Related skills
/sales-tealium — Tealium platform help — Real-Time CDP, iQ Tag Management, EventStream, 1300+ connectors/sales-blueconic — BlueConic CDP — profile unification, segmentation, audience activation, Jebbit Experiences/sales-treasuredata — Treasure Data enterprise CDP — AI Marketing Cloud, 400+ connectors, SQL-based/sales-rudderstack — RudderStack platform help — warehouse-native CDP, Event Streams, Reverse ETL, open-source/sales-mparticle — mParticle platform help — hybrid CDP, real-time event streaming, identity resolution, 300+ integrations/sales-data-hygiene — CRM data quality — clean your data before feeding it to a CDP/sales-retargeting — Retargeting strategy — activate CDP audiences to ad platforms/sales-integration — Tool integration — connecting CDP to CRM, email, ad platforms/sales-enrich — Contact enrichment — augment CDP profiles with third-party data/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
Example 1: CDP selection
User says: "We have 500K monthly users across web and mobile. Our marketing team needs to build audiences without engineering help. Budget is $50K-$100K/year."
Skill does: Compares BlueConic (marketer-first, mid-market pricing) vs Tealium (enterprise, more integrations but steeper learning curve) vs Segment (developer-first, may not suit a non-technical marketing team). Recommends BlueConic for the marketer-first UI, or Tealium if the 1,300+ integration catalog is critical.
Result: User has a shortlist of 2 CDPs to evaluate with clear pros/cons for their situation.
Example 2: Do I need a CDP?
User says: "We use HubSpot for CRM, Mailchimp for email, and Google Ads. Our data feels messy. Do we need a CDP?"
Skill does: Asks about pain points — are profiles fragmented? Do you need real-time activation? How many data sources? For a 3-tool stack, suggests starting with native integrations and /sales-data-hygiene before investing in a CDP. A CDP makes sense when you have 10+ data sources or need real-time audience activation across channels.
Result: User understands the CDP readiness threshold and knows what to try first.
Example 3: Composable vs bundled CDP
User says: "We already have all our data in Snowflake. Should we get a traditional CDP or use a composable approach?"
Skill does: Explains the composable CDP approach (Hightouch, Census) vs warehouse-native features from traditional CDPs (Tealium Composable CDP, Segment Linked Audiences). Compares cost, implementation time, and activation capabilities.
Result: User understands the trade-offs and can choose the right architecture for their warehouse-centric stack.
Troubleshooting
Profiles not unifying across channels
Symptom: Same customer has multiple profiles — one from web, one from email, one from mobile
Cause: No shared identifier connecting profiles across channels. CDPs merge on matched identifiers (email, customer ID, phone).
Solution: Implement progressive identification — capture email/login on every channel. Use identity resolution rules that prioritize deterministic matches (email) over probabilistic (device fingerprinting). Test merge rules in a sandbox.
CDP implementation taking too long
Symptom: 6+ months in, still haven't activated first audience
Cause: Trying to boil the ocean — connecting all data sources, building all segments, and activating all channels at once
Solution: Start with one use case (e.g., abandoned cart audience → Facebook retargeting). Get that working end-to-end in 4-6 weeks. Then expand iteratively. The biggest CDP implementation risk is scope creep, not technical complexity.
Data quality issues after CDP deployment
Symptom: CDP profiles have incorrect data, duplicate merges, or stale attributes
Cause: Source data quality issues — the CDP unified garbage from garbage sources
Solution: Run /sales-data-hygiene on source systems first. Audit identity resolution rules for false merges. Set up data quality monitoring in the CDP dashboard.
