revial
Configuration
Number of users10
150100500
Contract type
Annual pipeline (estimate)€2M
0.1M10M20M100M
Salesperson monthly cost to employer
€5,000
2k5k10k15k
ROI estimate based on Revial customer results: +3% win rate (conservative sales assumption; market research customer average +45%) and time savings from each salesperson's daily cost (15% of work time). All prices VAT 0%.
Summary
6 MO
€680
6 months · VAT 0%
€68 / user / month
Users10
Price / user / month€68
Contract period6 mo
Total price€2,040
Time savings €/yr (15% of salesperson daily cost)
€40,950/yr
ROI estimate for the team
€140,000
Additional sales
+3% win rate
+3% win rate
€40,950
Time savings €/yr
(15% of daily cost)
(15% of daily cost)
~14 d
Payback
period Calculated on an annual cost basis regardless of the selected contract length.
period Calculated on an annual cost basis regardless of the selected contract length.
80×
ROI multiplier
(estimate)
(estimate)
Organization parameters
Number of salespeople10
150100500
Tech team (developers)3
151015
Developer monthly salary€7,000
2k5k10k15k
Organization size
AI infrastructure / mo€500
1001k3k5k
Calculates the realistic cost of building an equivalent system in-house: development, infrastructure, maintenance, integrations and staff. Does not include failure risk or opportunity cost.
Cost estimate
DIY BUILD
€298,000
Build cost (year 1)
+€9,500 / mo maintenance
Development time (estimate)12–18 mo
Development team cost€252,000/yr
AI infrastructure / yr€6,000/yr
Integrations (HubSpot, M365…)€20,000–€60,000
Maintenance and security / yr€40,000–€80,000
Total cost over 3 yr€850,000+
Comparison: Revial vs. DIY build
€2,040
Revial
selected period
selected period
€298,000
DIY build
year 1 cost
year 1 cost
146×
More expensive
to build in-house
to build in-house
14 d
Revial deployment
vs. 12–18 mo
vs. 12–18 mo
Project risk profile
Project budget (1–3 yr)€200,000
50k250k500k1M+
Project team size5 ppl
281525
Spec experience (product / data)
Solution criticality to the business
Risk scenarios
DIY RISK
€350,000
Potential waste and delays
52% of your budget
Budget wasted€120,000
Probability of over-engineering / spec changes68%
Budget overrun+189%
Additional time to market+6–10 mo
Opportunity cost (lost market growth)6–12 mo
Comparison: DIY risks vs. Revial
€350,000
DIY risk scenario
wasted value
wasted value
€2,040
Revial
selected period
selected period
120×
More expensive
to carry the risk
to carry the risk
Research evidence
45%
Over budget on average
Large IT projects: +45% budget, +7% schedule, −56% value. 17% threaten company existence.
McKINSEY & OXFORD · 5,400 projects ↗
McKinsey & University of Oxford (2012)
5,400 IT projects: avg 45% over budget, 7% over schedule, 56% less value delivered. 17% of projects threaten company existence. Cost overrun grows 15% per additional year.
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+97%
Success with clear requirements
Projects with clear requirements before development were 97% more likely to succeed.
ENGPRAX / J.L. PARTNERS · 600 engineers 2024 ↗
Engprax — Impact Engineering Study (2024)
600 software engineers surveyed. Clear requirements = 97% more likely to succeed. Documented requirements = 50% more likely to succeed. 65% of Agile projects fail on time/budget/quality.
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31%
Of projects fully cancelled
52.7% exceed budget by 189%. 75% of IT executives believe their projects will fail.
STANDISH GROUP CHAOS 2023 ↗
Standish Group CHAOS Report (2023)
31.1% of software projects cancelled before completion. 52.7% exceed budgets by 189%. 75% of IT executives believe their projects are doomed to fail from the start.
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70%
Of IT projects fail
They don't deliver agreed scope on time or on budget. $1M wasted every 10 seconds globally.
PMI PULSE OF THE PROFESSION 2024 ↗
PMI Pulse of the Profession (2024)
70% of projects fail globally. $1M wasted every 10 seconds due to poor strategy execution — approx. $2 trillion/year. Only 58% of organizations understand the value of project management.
Open study →
85%
Of AI projects fail
Gartner: most AI initiatives fail to meet their goals. 87% of R&D projects never reach production.
GARTNER 2023 ↗
Gartner — AI & Software Project Failure (2023)
85% of AI projects fail to meet expectations or fail outright. 87% of R&D projects never reach production. HBR places digital transformation failure rate as high as 80%.
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39%
Of failures caused by specs
Poor requirements gathering is the single biggest cause. Communication breakdowns cause 57% of failures.
BETABREAKERS / ZIPDO 2023 ↗
BetaBreakers — Software Failure Statistics (2023)
Poor requirements gathering = leading cause in 39% of failures. Communication breakdowns = 57%. Scope creep and unclear objectives = 32%. 29% due to inadequate testing.
Open study →
Development pace and execution model are decisive: leveraging an existing product reduces failure risk and shortens time-to-value. See sources below.