How to choose a CDP for product-led growth?

Summarize this article with LLMs

I’ve lost count of how many teams said they were “buying a CDP to unlock PLG”. Twelve months later, many of them had:

A very expensive event warehouse, a few half-finished dashboards, and no clearer picture of who was actually activating or expanding.

Sales still ran on gut feel and spreadsheets. Product had no trustworthy way to see which behaviors predicted revenue. Marketing was stuck with generic campaigns because the “PLG events” never quite made it into their tools.

The problem usually wasn’t that they chose the “wrong” vendor on a feature matrix.

It was that they never defined what product-led growth meant in data, so the CDP turned into a catch-all project instead of a sharp tool.

When I say product-led growth (PLG), I mean a go-to-market model where new revenue and expansion are mostly predicted by what users do in the product, not by how many sales calls or campaigns you run.

When I say customer data platform (CDP), I mean a system that collects events and traits from your product and other tools, unifies them around users and accounts, and sends them to the places where your team takes action (like CRM, marketing, and internal analytics).

This post is a practical guide to choosing a CDP specifically for product-led growth. The goal is to help you avoid a beautiful architecture diagram that has no impact on activation, expansion, or retention.

If you’re evaluating Skene, you can keep this post open next to the main site and compare the patterns here to how you’re thinking about product signals and onboarding today. For a broader PLG playbook, see How to achieve product-led growth?.

Who this is for

This is mainly for:

Early-stage SaaS founders who feel pressure to “get serious about data” and are being pitched CDPs as a silver bullet for PLG.
Product and growth leaders who know they need better product usage signals to drive self-serve, not just more dashboards.
RevOps / data / analytics people who are tired of being the bottleneck every time someone wants to know “who actually activated”.

If you’re already running a mature CDP implementation, this will still help you sanity-check whether it’s actually aligned with your PLG motion.

Key takeaways

You don’t start CDP selection with a feature matrix; you start with your “aha” and “habit” moments and work backward.
The biggest risk is not picking the “wrong” tool; it’s owning a system your current team can’t realistically implement and maintain.
For PLG, the most important CDP capabilities are reliable product events, identity resolution, and actionable audiences, not every possible integration.
A good CDP choice makes sales, CS, and growth more product-led, not more dependent on analysts to answer basic questions.

TL;DR – what actually matters when choosing a CDP for PLG

Define your PLG data model first. Write down your “aha” and “habit” events and the minimum schema you need to support those.
Prioritize the boring fundamentals. You need trustworthy tracking, identity resolution, and audience syncs more than advanced AI scoring.
Score vendors on implementation reality. Can your current team wire this up in weeks and maintain it, or does it assume a data org you don’t have?
Make use cases explicit. Choose 2–3 concrete PLG use cases (activation alerts, upgrade triggers, lifecycle messaging) and evaluate tools against those.
Run a small, honest pilot. Instrument a thin slice of your product and see if the CDP actually makes it easier to run product-led experiments.

Step 1: Define your PLG data model before your CDP

Most CDP evaluations start with a spreadsheet of:

“Must-have” integrations.
Nice-to-have features.
Security and compliance boxes to tick.

Those are important, but they’re not what makes a CDP work for product-led growth.

For PLG, a more useful starting point is:

“What behaviors in our product reliably predict revenue, and what events do we need to track to see those behaviors?”

Sit down with your team and answer three questions:

What is our “aha” moment?
- The first action that strongly correlates with higher activation or conversion.
- Examples:
  - An analytics product: “Created first dashboard with real data sources.”
  - A messaging product: “Sent first campaign to at least 50 real recipients.”
  - A dev tool: “Deployed first change to production using our pipeline.”
What is our “habit” moment?
- The recurring usage pattern that separates casual users from retained accounts.
- Examples:
  - “Runs at least one key workflow every week for 4 weeks.”
  - “Invites at least 3 teammates who also perform a key action.”
  - “Defines and tracks at least 3 core objects (projects, campaigns, reports).”
Which tools need to know about these moments?
- Sales (CRM): to prioritize outreach and expansion.
- CS / success tools: to see who’s stuck vs. thriving.
- Marketing: to run in-product and email journeys based on real product activity.
- Internal analytics: to measure and improve your PLG funnel.

Now sketch the minimal event schema you need:

Which events do you need to send? (e.g. workspace_created, project_created, campaign_sent)
Which properties are non-negotiable? (e.g. plan type, region, integration type, number of recipients)
How will you represent users vs. accounts (and guests, admins, workspaces, etc.)?

If you can’t answer these on a whiteboard, your CDP is at risk of becoming a generic logging tool instead of a PLG engine.

Step 2: Non‑negotiable CDP capabilities for product‑led growth

Once you’re clear on your PLG data model, you can evaluate CDPs against what actually matters.

For most early-stage PLG teams, the non-negotiables look like this:

1. Reliable event collection

SDKs and server-side APIs that your team is comfortable using.
Clear handling of retries, batching, and failures.
Support for your main platforms (web, backend, mobile) without heroic effort.

If your engineers don’t trust the SDKs or find them painful, adoption will stall and events will drift.

2. Solid identity resolution

In PLG, you care about:

Individual users (who did what).
Accounts / workspaces (where revenue lives).

Your CDP should help you:

Tie anonymous activity to identified users when they sign up.
Merge identities sanely when emails or account structures change.
Keep a coherent picture of “account health” even when there are many users.

If this is weak, you end up with:

Multiple records for the same customer.
Confusing, contradictory dashboards.
Sales and CS not trusting the data, reverting to manual notes.

3. First‑class traits and audiences

For PLG, you want to be able to:

Attach traits (e.g. “is_trialing”, “plan_tier”, “has_key_integration”) to users and accounts.
Build audiences like:
- “New workspaces that haven’t hit ‘aha’ within 7 days.”
- “Power users who invited at least 3 teammates.”
- “Accounts with heavy usage but still on a low tier.”
Sync those audiences into:
- CRM (for sales and CS).
- Marketing tools (for campaigns and journeys).
- In-app messaging (for nudges and guides).

If building these audiences is painful, you’ll end up asking analysts for exports instead of running real PLG plays.

4. Reasonable governance, not bureaucracy

You don’t need a full data governance committee at seed or Series A.

You do need:

A way to keep schemas from exploding into hundreds of slightly different events.
Basic controls around PII and deletion.
Clear ownership of “who can create new events and traits”.

The right CDP should make it easy to stay tidy without paralyzing you.

Step 3: Evaluate implementation and maintenance cost honestly

The most common failure pattern I saw was:

The demo looked amazing.
The architecture diagram was clean.
The implementation plan quietly assumed a data team you don’t have yet.

Before you fall in love with a vendor, ask:

Who will actually implement this?
- Do you have engineers and analytics people with bandwidth?
- Is there a realistic owner for schemas and tracking quality?
How many systems need to be wired up to support your first PLG use cases?
- Product (web/app).
- Backend events.
- Billing.
- CRM, marketing, and maybe support tools.
What does “good enough” look like in the first 4–8 weeks?
- One or two solid “aha” events fully wired.
- A small set of audiences visible to sales and CS.
- A basic activation dashboard you all trust.

If the vendor’s plan jumps straight to “full tracking of everything” or months-long implementation, be careful. Early-stage PLG teams win by shipping a thin slice end-to-end and iterating.

Ask each vendor to walk you through:

A realistic phased rollout for a company at your stage.
What they’ve seen similar-sized teams achieve in the first 90 days.
Which parts you can self-serve vs. which require their services or heavy consulting.

You want a CDP that matches your current level of maturity and can grow with you. You do not want one that only makes sense when you’re 10x bigger.

Step 4: Governance, security, and stakeholder reality check

Even at early stage, you can’t ignore governance and security. But you also can’t afford to let them freeze your PLG motion.

Walk through these questions with your stakeholders (engineering, security, legal, data):

What data must not leave certain regions or systems?
- Do you have data residency requirements?
- Are there regulated data types (health, finance) in the mix?
What are your minimum access controls?
- Who can see raw events?
- Who can build audiences and connect destinations?
How will you handle deletion and consent?
- Can the CDP help you propagate deletions and consent changes?
- Does it make audits easier or harder?

Good CDP choices for PLG:

Make it easier to stay on top of privacy and access.
Don’t require months of policy work before you can track your first “aha” event.
Give you clear logs and controls so security can sign off without blocking experiments forever.

If a tool can’t give your security and legal stakeholders a straightforward story, it will slow every PLG initiative that depends on product data.

Step 5: How to run a focused CDP evaluation for PLG

Instead of a generic RFP, run a PLG-focused evaluation:

Pick 2–3 concrete use cases.
- Example:
  - “Alert sales when an account hits ‘aha’ but hasn’t talked to us.”
  - “Trigger in-app guides for new workspaces that stall before first value.”
  - “Identify power users who could be champions for case studies or referrals.”
Define simple success metrics.
- Examples:
  - “Within 60 days, we can reliably see which accounts hit ‘aha’ and when.”
  - “We reduce manual CSV exports by 80% for activation reporting.”
  - “Sales and CS log into a product usage view at least weekly and trust it.”
Ask vendors to show you these flows end-to-end.
- How do we:
  - Track the events?
  - Build the traits and audiences?
  - Sync them into our existing tools?
  - Visualize and monitor them over time?
Time-box a pilot.
- 4–8 weeks is usually enough to see whether:
  - Engineers are happy instrumenting events.
  - Data feels clean and trustworthy.
  - GTM teams actually use the signals.

At the end of the pilot, debrief ruthlessly:

What did we actually ship?
Which team members are excited to keep using this?
Did it get us closer to product-led activation and expansion, or just add another dashboard?

Checklist before you sign with a CDP vendor

Use this as a quick filter before you commit to a CDP contract:

We have written down our “aha” and “habit” moments, and we know which product events represent them.
We have a minimal event schema on paper, including how we represent users, accounts, and key objects.
We have identified 2–3 concrete PLG use cases for the first 90 days, and we can describe how the CDP will support each one.
We know who will own implementation and tracking quality, and those people agree they have the time and skills.
We understand how events, traits, and audiences will flow into our existing tools, including CRM, marketing, and success tooling.
We have seen the vendor walk through our specific flows end to end, not just a generic demo.
We have a realistic phased rollout plan, with a clear “good enough” state for the first 4–8 weeks.

If you can say “yes” to most of these, you are in a much better position to choose a CDP that actually moves your product-led growth forward.