Results that already happened
Numbers from systems already running.
3–5 hrs
back to the team, per day
The average time saved by admin and sales teams once the system runs — from manual follow-ups, daily reports, and coordination that no longer needs to happen.
+28–42%
leads turn into booked calls
The average increase in leads turning into booked calls within the first 2–3 months. Leads no longer disappear in WhatsApp or spreadsheets no one opens.
+15–25%
calls turn into deals
The average increase in calls turning into deals. Every call is logged, has a next step, and nothing gets left hanging without follow-up.
*Numbers are averages from several projects. Your results depend on your business, offer, and team execution.
What actually goes up
Not some vague idea of "business growth" — these are 5 real, specific things that change, from conservative to best-case.
Four points per number: No Service (business runs normally with no service at all), Conservative (even an average response still turns a profit), Documented (the number most often quoted in research), Best Case (the best case study we found). These come from different studies — not a guarantee for your business, and not statistical percentiles from one dataset.
Featured Metric
Response Speed to Prospects
chance of closing
Dot position = tier level, not a number scale (units differ between points)
No Service (>42 hours): today's average industry response time — the impact is close to zero, called an "infrastructure failure" in research
Sales speed-to-lead data
Conservative (7x): more likely to close if you respond within about 1 hour (vs. waiting 2 hours)
Speed-to-lead research
Documented (21x): more likely to qualify a lead if you respond within about 5 minutes — the "industry gold standard"
Consistent across 3 sources (same citation chain, not 3 independent studies)
Best Case (+391%): increase in conversion if you respond in under 1 minute (the "Platinum Minute")
Sales speed-to-lead data
Operating Cost Efficiency
per customer service interaction
Dot position = tier level, not a number scale (units differ between points)
No Service ($5.00): cost per interaction with a fully manual process, no AI triage at all
AI Triage vs. Manual study
Conservative (75%): cost efficiency per interaction ($5.00 → $1.20) with AI triage
AI Triage vs. Manual study
Documented (~82%): cost efficiency per interaction, the midpoint of the same study range
AI Triage vs. Manual study
Best Case (90%): cost efficiency per interaction ($5.00 → $0.50) at full scale
AI Triage vs. Manual study — same single source for all 3 tiers
Team Productivity / Output
output multiplier
Dot position = tier level, not a number scale (units differ between points)
No Service (1x): baseline with no automation — manual work as usual, no speed-up
Defined zero point, not a research claim
Conservative (4.3 hours): saved per person, per week, from CRM automation (−67% manual update time)
Sales-CRM operations data
Documented (2x): productivity increase reported by executives after adopting agentic AI
Executive survey, cited by Google Cloud
Best Case (5x): output with no added staff — a single company case study, not representative of the wider population
Single case study (TinySuperheroes)
Checkout Conversion Increase
conversion rate
Dot position = tier level, not a number scale (units differ between points)
No Service (0%): no checkout UX improvements made — conversion rate stays at the starting point
Defined zero point, not a research claim
Conservative (+22.3%): conversion gain from one specific fix (adding Apple Pay at checkout)
Baymard Institute
Documented (+35.26%): conversion gain from general checkout usability fixes — the most credible number in this whole research set
Baymard Institute, 327 sites, 14 years of research
Best Case (~+57%): combined checkout fixes + Apple Pay (35.26% + 22.3%), still from the same Baymard study
Baymard Institute — combining 2 findings
Direct Revenue Increase
revenue growth
Dot position = tier level, not a number scale (units differ between points)
No Service (+5–8%): yearly revenue growth for a typical business, with no AI/SEO/etc. adoption — matching the baseline used in the source research
US Census Nonemployer Statistics 2025 / OECD 2025
Conservative (+10%): year-over-year — the minimum bar for an "AI high performer" in international research
International study, 2023
Documented (+77%): revenue per sales rep, from a sample of 7.1 million opportunities across 3,600+ companies
Sales AI industry research
Best Case (3.2x): revenue growth from the combined, compounding effect of AI and SEO
⚠️ Illustrative estimate, not yet verified against the original source report
*All numbers come from independent third-party research, not Ranvil's internal project data. Each point (No Service/Conservative/Documented/Best Case) comes from a different study or source — not statistical percentiles from one dataset, and not a guarantee for your own results. The "No Service" point in 2 metrics (Productivity, Checkout Conversion) is a defined zero point (no change), not a research claim — clearly marked at its source. Unverified vendor claims (like "23x GEO conversion") were deliberately left out, except for the one number marked above.
How to read these numbers
What we mean when we say "proof"
The stats on this page come from two different places, and we keep them separate on purpose. The headline numbers above are averages from systems we've built. The comparison table below is third-party research — industry studies on response speed, automation cost, and conversion — not our own client data.
We'd rather show a range with sources than one impressive number with none. Where a stat came from a single case study instead of a broad dataset, we say so directly instead of presenting it as typical.
None of this is a guarantee. Your results depend on your offer, your team's follow-through, and how disciplined the rollout is. What we can guarantee is that the system gets built to actually track these numbers — so you're not guessing whether it's working.