I have 2 questions: Let's say a company have 1.000 leads in stage 2, and they won 18%, then there's 7% pipeline inflation (by following the definition of qlf pipeline as 25% win rate) 1) If 100% of the company's leads come inbound through the website by booking a demo call, how would the pipeline inflation analysis be done, in order to find out which leads are causing inflation? Especially if the self reported attribution is more or less the same. My background thought for this is that even declared intent leads are created differently. A "we've seen your content on linkedin" SRA, can both mean someone read your linkedin posts 5 times or 100 times, so the ones who read content 100 times would have higher win rates. 2) I think the 25% win rate defintion is genius, but is it the right number for all B2B SaaS companies?
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I have 2 questions:
Let's say a company have 1.000 leads in stage 2, and they won 18%, then there's 7% pipeline inflation (by following the definition of qlf pipeline as 25% win rate)
1) If 100% of the company's leads come inbound through the website by booking a demo call, how would the pipeline inflation analysis be done, in order to find out which leads are causing inflation? Especially if the self reported attribution is more or less the same.
My background thought for this is that even declared intent leads are created differently. A "we've seen your content on linkedin" SRA, can both mean someone read your linkedin posts 5 times or 100 times, so the ones who read content 100 times would have higher win rates.
2) I think the 25% win rate defintion is genius, but is it the right number for all B2B SaaS companies?
Way to REFINE the definition of pipeline. #qualityoverquantity
Quality definition 👌🏾
🤜💥🤛
OMG. Yes! 👏🏻
The more you know 🤜💥🤛