ROI Calculation Methodology & Data Sources

We make specific claims about automation ROI. You deserve to see exactly where those numbers come from—every data source, every assumption, every limitation.

• Conservative assumptions clearly stated and justified
• Alternative interpretations acknowledged
• Limitations and edge cases explained honestly
• Regular updates as new research becomes available
• Every statistic cited with its original source

If you spot an error or disagree with an assumption, we want to know. Contact us.

1. Primary Data Sources
2. Extrapolation Methodology
3. Time Savings Calculations
4. Cost Assumptions
5. Scenario Breakdown
6. Alternative Calculation Scenarios
7. Limitations & Caveats
8. Frequently Asked Questions (FAQ)

Additional Studies Supporting Speed-to-Lead:

• Harvard Business Review: Companies that contact potential customers within 1 hour are 7× more likely to qualify the lead compared to those who wait longer.
• InsideSales.com: 50% of buyers choose the vendor who responds first, regardless of other factors. Speed becomes a tie-breaker when multiple options are available.
• LeadSimple: Responding within 5 minutes makes you 9× more likely to convert the lead compared to responding after 30 minutes.

Consistency Across Research:

Every major study in this space reaches the same conclusion: faster response = dramatically higher conversion. The exact percentage varies by industry and methodology, but the pattern is universal and robust across different research teams, time periods, and markets.

1. Under-promise, over-deliver
   If actual results exceed projections, clients are delighted. If we overstate and disappoint, trust is damaged. Conservative projections protect client relationships.
2. ROI is overwhelming even at conservative rates
   Even assuming 60% conversion (same as 30 minutes), the ROI ranges from 1,158% to 18,670%. We don't need to claim higher rates to prove value.
3. Transparency builds credibility
   By admitting we're extrapolating conservatively and not claiming the full benefits research suggests, we avoid accusations of overstating our case.

What This Means for Projections

If MIT and Velocify are correct (and we believe they are based on the consistency of findings), actual results should exceed our projections. Our 60% assumption for <5 minute response is almost certainly understated. But we'd rather be pleasantly surprised than disappointingly wrong.

Time Components of Manual Quoting
 

Base Quote Preparation: 45-120 minutes

• Calculate pricing manually (spreadsheets, rate cards): 15-30 min
• Check availability across multiple systems: 10-15 min
• Check for conflicts/overlaps with other bookings: 5-10 min
• Create quote document (Word/PDF formatting): 15-30 min
• Review and proofread for errors: 10-15 min
• Format and send via email: 3-5 min
• High-customization venues: Additional 45-75 min for unique elements

Follow-up Activities (30% of quotes): 9-18 minutes average

• Client follow-up emails when no response: 5-10 min
• Answer clarifying questions: 4-8 min

Revision Requests (30% of quotes): 9-18 minutes average

• Recalculate pricing with changes: 5-10 min
• Update documents and resend: 4-8 min

Total Times by Scenario (manual quoting)

Time Components of Automated Quoting (optimized process)

System-Automated Components (0 minutes staff time):

• Availability check: Instant (real-time system query)
• Pricing calculation: Instant (automated based on rules)
• Conflict detection: Instant (database check)
• Document generation: Instant (template auto-fill)

Staff Review Time: 3-30 minutes

• Standard scenarios: 3 minutes (quick review, approve, send)
• High-customization: 30 minutes (staff focuses only on truly unique elements)

Follow-up Activities (30% of quotes, but 80% time reduction): 1.2-3.6 minutes

• Automated tracking reduces need for manual follow-up
• Automated reminders and templates streamline when needed
• System flags quotes needing attention

Revision Requests (10% of quotes - reduced from 30% due to accuracy):

• Reduced frequency: Accurate automated calculations mean fewer revision requests
• Reduced time when needed: Instant recalculation, automatic document update 1.5-2.7 minutes instead of 9-18 minutes

Total Times by Scenario (automated quoting)

Conservative Assumption:
We assume full adoption and optimization by Month 12. Early months (1-3) achieve 30-50% of full benefit during learning curve, ramping to 70-85% by Month 6, and 100% by Month 12.

Staff Cost: €50/Hour (Fully-Loaded)

Components

• Base salary: ~€35/hour (median for event sales roles in DACH region)
• Benefits: ~€9/hour (health insurance, pension, vacation—typically 35% of base)
• Overhead: ~€6/hour (office space, equipment, utilities—typically 15% of loaded cost)
• Total: €50/hour fully-loaded

Note: This hourly rate is calculated based on 1,408 productive hours per year (2,080 total hours minus vacation, public holidays, sick leave, training, and administrative tasks).

Source: DACH region hospitality industry salary surveys, adjusted for event sales roles specifically, 2025 labor market conditions.

Conservative or Aggressive? Mid-range estimate. Some properties pay significantly more (€65-75/hour for senior sales directors), some pay less (€40-45/hour for junior staff). €50/hour is a reasonable average.

Technology Cost (Overview)

Technology Cost For Specific Scenarios

Scenario 1: Smaller Hotel

Annual quote volume: €90,000 (average €7,500 per month)
Eventmachine Plan: Flex (annual)
Base fee: €1,140/year
Platform fees: €225/year (€7,500 × 0.25% × 12 months)
Technology costs (base fee + platform fees): €1,365/year

Scenario 2: Mid-Size Hotel

Annual quote volume: €540,000 (average €45,000 per month)
Eventmachine Plan: Flex (annual)
Base fee: €1,140/year
Platform fees: €1,350/year (€45,000 × 0.25% × 12 months)
Technology costs (base fee + platform fees): €2,490/year

Scenario 3: Larger Hotel

Annual quote volume: €3,600,000 (average €300,000 per month)
Eventmachine Plan: Reserved (annual) – more cost-effective at this volume
Base fee: €4,500/year
Platform fees: €38/year
Technology costs (base fee + platform fees): €4,538/year
(Explanation: The Reserved Plan includes 0% fees on the first €375,000 quote volume per month. At an average of €300,000/month, most months fall below this threshold. The €38 comes from occasional peak months exceeding €375,000.)

Scenario 4: Special Event Venue

Annual quote volume: €3,600,000 (average €300,000 per month)
Eventmachine Plan: Reserved (annual) – more cost-effective at this volume
Base fee: €4,500/year
Platform fees: €38/year
Technology costs (base fee + platform fees): €4,538/year
(Explanation: The Reserved Plan includes 0% fees on the first €375,000 quote volume per month. At an average of €300,000/month, most months fall below this threshold. The €38 comes from occasional peak months exceeding €375,000.)

Note on Platform Fees:
Platform fees are calculated on quoted volume, not booked volume. This might seem counterintuitive, but it's actually favorable: automation makes quoting so efficient that the cost per quote becomes trivial even for non-converting inquiries. Properties generate many quotes, but the per-quote cost with automation is far below manual labor cost.

Scenario 1: Smaller Hotel

Benefit per year: €15,810  | ROI: 1,158% | Payback: <2 months

Profile: 60 quotes/year, average quote €1,500

Scenario 2: Mid-Size Hotel

Benefit per year: €92,235 | ROI: 3,704% | Payback: <1 month

Profile: 180 quotes/year, average quote €3,000

Scenario 3: Larger Hotel

Benefit per year: €679,642 | ROI: 14,977% | Payback: <1 month

Profile: 720 quotes/year, average quote €5,000

Note: 1) At larger hotels, manual conversion is typically only 40% due to high volumes and response times of 48+ hours. This calculation uses 44% (higher), which understates the calculated benefit. 2) Conversion with automation is 62% (instead of 60%) because - at higher average quote volumes - enterprise-level response speed and consistent quote quality create a clear competitive advantage.

Scenario 4: Special Event Venue

Benefit per year: €763,462 | ROI: 16,824% | Payback: <1 month

Profile: 120 quotes/year, average quote €30,000

Note: 1) At premium venues, manual conversion is typically only 42% due to highly complex quotes and response times of 48-72 hours. This calculation uses 44% (higher), which understates the calculated benefit. 2) Conversion with automation is 65% (instead of 60%) for more complex quotes with high quote values because you differentiate from competitors who are either fast or high-quality – but cannot offer both simultaneously.

[Benefit = (Staff Cost Savings – Technology Cost) + Additional Revenue from Higher Conversion]
[ROI % = (Benefit ÷ Technology Cost) × 100%]
[Payback Months = Technology Cost ÷ (Benefit ÷ 12)]

Sensitivity Test #1: Lower Conversion Rate Improvement

Original Assumption: 60% automated vs. 44% manual (16 percentage point improvement)
Alternative: 55% automated vs. 44% manual (11 percentage point improvement – 30% less benefit)

Mid-Size Hotel Example:

• Original additional revenue: €86,400/year
• Reduced additional revenue: €59,400/year
• Still strong ROI: (€59,400 + €8,325 - €2,490) ÷ €2,490 = 2,620% ROI
• Payback: still <1 month

Conclusion: Even with 30% lower conversion improvement, ROI remains overwhelming.

Sensitivity Test #2: Lower Staff Costs

Original Assumption: €50/hour
Alternative: €35/hour (30% less – conservative scenario)

Mid-Size Hotel Example:

• Original staff cost savings: €8,325/year
• Reduced staff cost savings: €5,828/year
• Combined with revenue gains: €86,400 + €5,828 - €2,490 = €89,738
• ROI: €89,738 ÷ €2,490 = 3,603% ROI

Conclusion: Even with lower staff costs, ROI remains very strong due to revenue gains.

Sensitivity Test #3: Faster Manual Process

Original Assumption: 63 minutes per quote (manual)
Alternative: 45 minutes per quote (20% faster manual process)

Mid-Size Hotel Example:

• Original manual staff costs: €9,450/year
• Reduced manual staff costs: €6,750/year
• Savings reduced, but revenue gains unchanged
• ROI: (€86,400 + €5,625 - €2,490) ÷ €2,490 = 3,595% ROI

Conclusion: Time savings are valuable, but revenue gains drive the ROI. Even with faster manual processes, ROI remains very strong.

Extreme Test #4: No Conversion Rate Improvement

What if automation provides ZERO conversion improvement
Assumption: 44% automated vs 44% manual (same conversion)

Mid-Size Hotel Example:

• Additional revenue: €0 (no improvement assumed)
• Staff cost savings only: €8,325/year
• Less technology costs: €2,490
• Benefit: €5,835/year
• ROI: 234%
• Payback: 5 months

Conclusion: Even in the extreme case where automation provides no conversion improvement whatsoever (contradicting all research), ROI is still positive from time savings alone. This demonstrates the robustness of the business case.

Limitation 1: Data Quality Dependencies

Risk: Garbage in, garbage out. Automation magnifies data quality—both good and bad. If your current pricing is inconsistent, your availability data is unreliable, or your package definitions are unclear, automation will expose (and potentially amplify) these issues.

Risk Mitigation:

• Use implementation as opportunity to audit/clean data
• Standardize pricing structures during setup
• Validate availability rules before go-live
• Test with sample quotes before full launch

Silver Lining: Discovering data issues during implementation is actually valuable. It forces properties to formalize knowledge that previously existed only in staff members' heads, reducing dependency on individual employees.

Limitation 2: Organizational Adoption

Risk: Staff resistance reduces benefit. If event sales team refuses to use the system, uses it reluctantly, or actively sabotages implementation, benefits won't materialize.

Risk Mitigation:

• Involve staff in setup process (creates ownership)
• Emphasize time savings benefits (less tedious work)
• Provide comprehensive training (builds confidence)
• Show quick wins early (builds momentum)

Reality: Most staff love automation once they see time savings. Initial resistance usually fades within 4-8 weeks as benefits become tangible. Common objection "I prefer doing it manually" shifts to "I can't believe we did this manually before."

Limitation 3: Implementation Quality

Risk: Poor setup = poor results. If property data is inaccurate (wrong pricing, incorrect availability rules), the system will generate poor quotes.

Risk Mitigation:

• Dedicated onboarding support
• Data validation workflows
• Regular optimization reviews
• Unlimited Plan includes full setup by Eventmachine team

Impact on ROI: Can delay payback by 1-3 months during optimization, but doesn't change long-term ROI.

Limitation 4: Extreme Customization

Risk: Some events are too unique for automation. Think of one-time corporate anniversaries, uniquely designed by a creative event design agency.

Reality Check: Even in Scenario 4 (high customization), we see 77% time savings. Automation handles standard elements; staff focuses on unique elements. The vast majority of events (especially in hotels) can easily be standardized (and automated) without problems.

Limitation 5: Market-Specific Factors

Risk: Your market may differ from benchmarks. VenueSuite data is European MICE. Your specific region might behave differently.

Conservative Approach: We use the most conservative figures from multiple sources. Regional variations shouldn't dramatically change results.

Example: If your market converts 50% with 24-hour response (not 44%), your baseline is higher—but you'll still see improvement from faster response. The magnitude might differ, but the direction is consistent.

The only way to truly know if automation works for your property is to try it. Start with a free trial month—no credit card required.