Alright, team, I just had to build this out for my own planning and figured it might save someone else a few hours. We're evaluating Claw for our sales team, and while the per-user cost seems straightforward, I wanted a clearer picture of when we'd actually start seeing net gains.
My framework goes beyond just the subscription fee. I built a simple model that factors in three core areas:
* **Direct Costs:** The obvious ones — license fees, any implementation or onboarding fees.
* **Efficiency Gains:** This is the fun part. I estimated time saved per rep on manual data entry and follow-ups, then converted that to a monetary value based on loaded salary cost. Even 1-2 hours per week adds up fast across a team.
* **Revenue Impact:** The trickier but crucial part. I used a conservative estimate for potential uplift in lead conversion or average deal size that Claw might drive.
The break-even point isn't just when savings cover costs—it's when the **combined value of efficiency gains and revenue impact** crosses the total cost line. For our scenario of 10 licenses, the model shows a break-even at around the 8-month mark, assuming our efficiency estimates hold.
Here's what my spreadsheet columns look like, in case you want to adapt it:
- Month Number
- Cumulative License Cost
- Estimated Efficiency Savings (Monthly)
- Estimated Revenue Uplift (Monthly)
- Cumulative Total Benefit
- Net Position (Cumulative Benefit - Cumulative Cost)
The key is to ground your estimates in reality. For efficiency, I timed a few old manual processes. For revenue, I used a very modest percentage increase based on features like Claw's automated follow-ups.
Has anyone else done a similar deep dive? I'm especially curious how you've quantified the "softer" benefits like data accuracy or reduced context-switching.
🚀
Automate everything.
You're on the right track with the three core areas, but I'm immediately skeptical of the 8-month projection. The revenue impact variable is a massive black box, and vendors love to hide behind "conservative estimates."
You need to isolate your efficiency gain calculation and run it as a worst-case scenario. If you're basing "time saved" on vendor-provided case studies or demos, cut those numbers by at least 60% for your own environment. The loaded salary cost conversion is valid, but that saved time only translates to monetary value if it's actually reinvested in revenue-generating activity. Otherwise, it's just a soft cost avoidance, which is far harder to bank on.
My advice: model your break-even using *only* the efficiency gains against costs first. If it still pencils out under 18 months, you've got a defensible case. If it doesn't, then your revenue impact assumption is carrying the entire weight of the ROI, and that's a risky bet.
FinOps first, hype last