Hey folks, hoping to tap into the collective wisdom here. I'm deep in the evaluation phase for cloud security platforms, and Lacework is a strong contender for our needs, especially with its data ingestion model.
But as someone who's negotiated plenty of marketing automation contracts (HubSpot, Marketo), I know list price is rarely the final price. The pricing seems complex with the whole Polygraph Data Unit model.
Has anyone here successfully negotiated their Lacework contract? I'm particularly curious about:
* What kind of discount percentage were you able to secure off the list price?
* Were there specific levers that helped (commitment term, paying upfront, threat of a competitor)?
* Any flexibility on the PDU commitments or overage fees?
Just trying to understand the real-world pricing landscape before we get into talks. Any data points on deal structure would be incredibly helpful!
Pick the right stack.
MartechMatch
Based on my experience with their PDU model, the most significant discounts came from structuring the annual commitment around projected data volume growth, not just a flat percentage off list price. We secured tiered pricing where the PDU cost decreased as we consumed more, which provided a hedge against overages. The initial discount off the standard rate card was around 30%, but the real savings were in the overage structure, which they were willing to cap.
Competitive pressure was a substantial lever, but only when we had a detailed, side-by-side analysis of feature parity and could demonstrate the competitor's pricing model was more predictable. Paying upfront yielded a minor additional concession, maybe 5%, but the term length was a bigger factor. A three-year commitment with specific growth projections gave them more to work with.
Be prepared to negotiate the PDU definition itself, not just the price per unit. We pushed for clarification on which data sources were counted at full weight versus half weight, which had a material impact on our consumption forecasts. The flexibility on overage fees was there, but it was tied to agreeing to a higher commitment in the next contract term.
Data doesn't lie, but folks sometimes do.
You're right to focus on the PDU model - that's where the real negotiation happens, not on a simple percentage off a list price that's almost fictional.
I agree with user667's point about tiered pricing being key. In my last negotiation, we pushed hard on the overage structure and got them to agree to a blended PDU rate for any overages, not the punitive standard overage rate. This effectively gave us a 40% discount on overages, which was more valuable than the 25% discount on the base commitment. The threat of a competitor was only effective when we had a signed quote from them that we were willing to present, not just a verbal "we're looking at others."
One caveat: their flexibility on PDU commitments seems tied to your projected growth curve. If you're forecasting flat consumption, they'll hold you to a hard commit. If you're projecting 30% year-over-year growth, they become much more willing to structure a flexible commitment with true-up quarters. Be prepared to share your cloud growth projections from your FinOps team.
This is super helpful, thanks both user667 and user777. That makes sense that the discount on overage rates would be the real win. I'm still wrapping my head around PDUs, honestly.
When you mention a signed quote from a competitor, which ones were most effective for you? Was it Wiz or something else?
The other responses are correct, the PDU structure is the primary negotiation surface. However, from a benchmarking perspective, I'd add that you must ground your "projected data volume growth" in actual telemetry from your CSP, not just financial forecasts. I've seen negotiations stall because the vendor's PDU estimate was 3x the customer's actual CloudTrail/Flow log volume.
When we prepared our negotiation, we ran a 30-day collection using open-source tools to establish a baseline data ingest rate per account. This gave us an irrefutable metric to push back on their initial PDU allocation and to argue for a more favorable overage threshold. The discount on the rate card became secondary; the main win was aligning the committed PDU to our empirically observed 95th percentile usage, plus a 20% buffer for growth.
Regarding competitors, a detailed feature gap analysis was more effective than just a quote. We created a weighted scorecard for capabilities like query latency, agent footprint, and detection coverage, which demonstrated where Lacework had measurable advantages and where the competitor was functionally equivalent. This allowed us to negotiate on specific module pricing rather than just an overall discount.
numbers don't lie