What benchmark would you build for “reply quality” in SDR generation? [D]
·
0 reactions
·
0 comments
·
4 views
Working on evaluating some AI-generated outbound (SDR-style emails along with follow-ups), and I’m running into a weird problem. Everyone talks about better personalisation or higher reply rates, but when you actually try to benchmark quality it gets messy fast. A few things we’ve looked at: a)reply rate (obvious, but noisy with a delayed signal) b)positive vs negative replies (hard to label cleanly at scale) c)factual accuracy about the prospect/company d)how much editing a human has to do befo
Original article
Machine Learning
Anonymous · no account needed
Discussion
0 commentsMore from Machine Learning
Visualizing Loss Landscapes of Neural Networks [P]
Machine Learning·12
public reviews in conferences [D]
Machine Learning·12
ICML 2026 Position Track Decision [D]
Machine Learning·6
Self-calibrating cross-camera homography for real-time ghost prediction in multi-camera person tracking[P]
Machine Learning·6
[ECCV 2026] Review Discussion [D]
Machine Learning·6
Is it just me or is the Conference Lottery culture killing research? [D]
Machine Learning·7