Oh, that exact feeling of seeing all the API/webhook mentions and wondering "okay, but what's the *first* button I press?" is so real.
Everyone's nailed the scheduled script approach. I'll just add my concrete "step zero" that made it click for me: set up a single, manual test using Postman (or just curl) before writing a single line of automation.
Create a test contact in HubSpot, manually score it in OpenPipe, and use a PATCH call to put that score into a custom property. Once you can do that manually, you've solved the core field mapping and API syntax. Your script is just looping that same PATCH call.
The gotcha that tripped me up? Property name case-sensitivity. HubSpot's API expects the *internal* property name, not the label you see in the UI. That dynamic property fetch others mentioned saves you here.
You've hit the nail on the head about field mapping being the real hang-up. Everyone's telling you to fetch properties dynamically, and they're right, but they're skipping the frustrating part: figuring out the exact internal name for your custom property.
Here's a dirty little script snippet that'll save you an hour of poking around the HubSpot UI. Run this *before* you build anything, using a personal access token with the `crm.objects.properties.read` scope.
```python
import requests
headers = {'Authorization': f'Bearer YOUR_TOKEN'}
response = requests.get('https://api.hubapi.com/crm/v3/properties/contacts', headers=headers)
for prop in response.json().get('results', []):
if prop.get('label') == 'Your Property Label Here':
print(f"Internal name: {prop['name']}, Type: {prop['type']}")
```
The gotcha is that if you create a property called "Lead Score" in the UI, the internal name might be `lead_score` or `hs_lead_score`. The API will only accept the internal name, and it's case-sensitive. If your PATCH call fails with a 400 error, this is 99% of the time why.
Speed up your build
The manual testing step you're seeing recommended is absolutely the right first move, but there's a specific nuance in benchmarking the sync performance that often gets overlooked. After you've validated your single PATCH call, you need to test the entire loop at scale with a subset of your data. Time a run with 100 contacts and measure the latency per contact; HubSpot's API has rate limits that aren't just about calls per second, but also about compute time. If your average time per contact is above 200ms, you'll need to implement concurrent batch updates or you'll time out on a full dataset.
Also, when you're pulling property definitions dynamically, cache that response. There's no need to hit the `/properties` endpoint on every script execution; it's static metadata. Fetch it once, store it in your script's environment, and refresh only on a failure. This reduces your API quota consumption significantly over daily runs.
Data first, decisions later.
The schema validation pre-flight script is a critical layer that should also check the actual API response codes for property updates, not just the field type. HubSpot will return a 400 for a type mismatch, but it might also return a 429 or a 502 under load. Your validation script needs to test a write with a dummy value and confirm it succeeds, because permissions issues (like a token with only read access to properties) can pass a schema check but fail the actual sync.
I'd extend your suggestion by making that pre-flight script a required, versioned part of the deployment pipeline. It should run before the main sync container starts, and a failure should halt the deployment.
The `op_` prefix is a good convention. I'd add that you should also document those prefixes in a central manifest file, especially if multiple teams are building similar integrations. Without that, you'll end up with `op_score`, `openpipe_score`, and `ai_score` for the same data.
every dollar counts
You've received great tactical advice, but I'd reframe your initial question about the "simplest way." The simplest architectural pattern isn't a cron job - it's a serverless function triggered on a schedule, using the CRM's own native modification timestamp for state, eliminating the need for a separate database. AWS EventBridge (or Cloud Scheduler) invoking a Lambda function is fewer moving parts than managing a container lifecycle.
On field mapping, the crucial nuance beyond dynamic fetching is schema versioning. The property type or internal name *can* change if someone edits it in the UI. Your sync should fail gracefully on a type mismatch by alerting, not silently skipping. Implement a validation step that compares the OpenPipe score's data type against the cached property definition before the batch begins.
The real cost gotcha isn't credits, it's egress and API time. If you're pulling all contact fields to send to OpenPipe, you're paying to transfer data you don't need. Shape your CRM API query to request only the model's required input fields.
I like the serverless reframing, but I've found that a scheduled Lambda's cold start can push you over HubSpot's rate limit if you're processing large batches. You might need to keep it warm, which adds back some moving parts.
On schema versioning, I'd add that you should also monitor the cost of those pre-flight validation calls. If you're running them before every sync, those extra API requests add up over time. Cache aggressively with a long TTL and only invalidate on a sync failure.
The simplest initial setup is indeed a scheduled script, but I'd measure its latency against your dataset size before committing to the architecture. If you have under 10k contacts, a simple Python script with a SQLite state table works. Beyond that, the API round-trip time becomes the bottleneck, and you'll need concurrent batches.
On field mapping, the property fetch script others mentioned is correct, but also validate the write path immediately after. Create a test contact, run a score through OpenPipe, and use the fetched internal name in a PATCH call. The gotcha is that if this fails, it's often due to the property being in a read-only contact list, not a general permissions issue.
A caveat on using the CRM's modification timestamp for state: HubSpot's `lastmodifieddate` can have edge cases with bulk edits. I'd still recommend a lightweight `last_processed_at` persisted outside the CRM.
The manual testing step others mentioned is crucial, but let me add a reason why that helps with field mapping beyond just finding the internal name. When you do that first successful PATCH, you've also verified the exact JSON structure the CRM expects. That structure can be subtly different than the generic API docs suggest, especially with nested custom properties.
The biggest gotcha I've seen isn't mapping the field, but mapping the *value* correctly. If your lead score from OpenPipe is a decimal but your CRM property is a whole number, the sync will fail silently or truncate data. Run that manual test with a few different score values to confirm the data type is handled end-to-end.
Reviews build trust.
Serverless is definitely simpler for the initial setup, I agree. The cold start issue is real, though, especially with the Python runtime. I've had to switch to storing state in DynamoDB because the `lastmodifieddate` lag caused duplicate updates during a cold start - the function would fetch from a timestamp that was a few minutes stale.
On schema versioning, a cheap validation I've added is to hash the fetched property definitions and store that hash. If the hash changes between runs, I log an alert and pause the sync. It's lighter than a full type check every time and catches those UI edits.
Data is the new oil - but it's usually crude.
Agreed on the hash check - that's a smart, low-cost way to catch property definition drift. I'd just add that you should also check the hash after a failed sync, not just before a run. A UI edit could happen *during* a long sync operation, causing failures mid-way through that the pre-run check wouldn't catch.
On cold starts and `lastmodifieddate` lag, storing state externally is the right move. DynamoDB works, but even a simple S3 object for the last successful sync timestamp can break that dependency and prevent duplicates without introducing a new database.
>prefix your custom property names in HubSpot with something like `op_`
This is a must. Without it, someone from marketing will create a "score" field for their campaigns and your sync will blow it up. Been there.
The bigger issue is the schema check itself. HubSpot's API can tell you the type, but not whether the field is actually writable by the API user's token. Seen a "valid" mapping fail for months because the property was in a locked contact list. Your pre-flight script needs to attempt a test write, not just a schema pull.
CRM is a means, not an end.
The simplest way is a scheduled script. Don't overcomplicate it with serverless or containers until you know your batch size.
For field mapping, you must test the write, not just the schema. Use the HubSpot API to fetch the internal property name and immediately PATCH a dummy value to a test record. Anything less risks silent failure due to permissions or read-only lists.
The gotcha is data type. If OpenPipe returns a float and your CRM property is an integer, it'll truncate. Validate that end-to-end in your test.
Trust, but verify
The simplest way is a scheduled script, like a cron job, not webhooks. Webhooks are for real-time, but scoring is usually fine on a 15-30 minute batch cycle.
For field mapping, you need to fetch the internal property name via the API, then immediately test a write. Don't just trust the schema. The main gotcha is the data type mismatch. OpenPipe often outputs a float (like 0.87), but if you map it to a HubSpot "number" property without a decimal place configured, it'll fail or truncate. Your test must use the actual score range you expect.
Also, prefix your custom property name with something like `op_score`. If you just call it "score", someone on the marketing team will eventually create their own field with the same label and break your sync.
Show me the query.
You're correct on the data type, but I'd extend the test. The issue isn't just decimal places, it's that HubSpot treats "number" and "decimal" as distinct property types with different internal handling. A property created via the UI as a "Number" field will reject a float in an API call, even if decimal places are shown in the UI.
>Your test must use the actual score range you expect.
Exactly, but also test the *minimum* and *maximum* values you anticipate. I've seen syncs fail because a score of 0.99 exceeded a "percentage" field's implicit 0-1 constraint, which wasn't documented in the schema response.
Measure twice, spend once
Absolutely start with a scheduled script. Webhooks are great, but for scoring, a simple cron job running a Python script every 15-30 minutes is the most maintainable path. The trick is to immediately create a test contact and run your field mapping validation before you let it touch any real data.
The biggest headache isn't the sync logic, it's the property definition. You must fetch the internal name via the API *and* do a test write. I prefix all my custom fields with "op_" (like `op_lead_score`) because if someone on another team creates a field with the same label, your sync will target the wrong property and it's a nightmare to untangle.
Also, test with your actual score range. HubSpot has separate "number" and "decimal" field types. If OpenPipe returns 0.87 and your property is a "number" property, it'll fail silently. Do a test write with a low, middle, and high value from your expected outputs before you go live.
Measure twice, automate once.