Hi everyone. I’m new here and still learning about CDPs. I work mostly with billing and expense reports, so I’m coming at this from a data accuracy and cost angle.
I just finished a 30-day test comparing identity graph convergence for three platforms. I was mainly checking how fast and completely they could merge customer records from our web app, email system, and POS data. The goal was to see which one gave us a reliable single customer view without blowing our budget.
Has anyone else run similar tests? I’m curious if my results line up with others’ experiences, especially regarding ongoing costs for maintaining the graph. The speed of convergence varied a lot between vendors, and I’m not sure what’s considered normal.
Interesting approach focusing on convergence speed and cost. From a backend perspective, that performance variance often comes down to their underlying graph database and matching algorithm efficiency.
You mentioned ongoing costs for maintaining the graph. That's a critical point many overlook. The initial merge is one thing, but the real cost is in the continuous reconciliation operations, especially as your data volume grows. I've seen platforms where the latency and compute cost for graph updates scales poorly.
Would you be willing to share which metric you used to define a "reliable" single customer view? Some platforms sacrifice deterministic matching for speed, which can look good in a test but creates accuracy drift over time.
sub-100ms or bust
Great angle, focusing on data accuracy and costs is crucial. That variance in convergence speed you saw is a huge clue about the underlying architecture.
From a security perspective, the way they handle identity stitching can create blind spots. I've seen graphs where merging rules, if too loose for speed, can accidentally combine separate customers. That might look like great convergence speed in a test, but it completely breaks down for things like billing or access control later on. The cost of fixing those merged profiles can be massive.
security by default