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Enterprise SaaS Case Study
39% → 82%

Completion Rate Transformation (+110%)

InputCoach — Adaptive Form Intelligence Platform

Vertex Enterprise Solutions

Transforming a 180+ field enterprise onboarding form from 39% completion to 82% with AI-powered contextual guidance, intelligent validation, and adaptive questioning.

Before and after comparison: traditional static form with 180+ fields vs InputCoach-enhanced form with intelligent AI coaching sidebar
Quick Facts
Industry Enterprise SaaS — Supply Chain
Duration 12 weeks (2 discovery, 6 MVP, 4 optimization)
Team Size 4-person core team
Technologies Claude 3.5 Sonnet, JavaScript SDK, TypeScript, React, WebSocket, PostgreSQL, Redis

-67%

Completion Time

$1.2M

Revenue Recovered

90%

Less Manual Work

+28

NPS Increase

Vertex Enterprise Solutions

Vertex provides supply chain optimization software for Fortune 1000 manufacturers across automotive, aerospace, and industrial sectors. Their platform manages operations across 40+ countries with 1,000+ supplier relationships, requiring comprehensive onboarding with detailed configuration data.

180+ Fortune 1000 Manufacturers
$240K Avg. Annual Contract
$18B+ Procurement Processed
Top 5 Automotive Manufacturers
The Stakes

61% of customers stalled during onboarding, causing delayed implementation timelines, overwhelmed sales engineering resources, and millions in deferred revenue.

Why This Case Matters

Vertex represents a common enterprise challenge: necessary complexity creates friction. Their data requirements were legitimate — they needed intelligent guidance, not simplification.

The Onboarding Bottleneck

61% of Vertex customers abandoned the configuration process during onboarding — a 180+ field form spanning 12 sections that required deep industry knowledge to complete.

61%

Abandonment Rate

Customers who never completed the onboarding configuration

180+

Form Fields

Complex technical questions across 12 sections requiring specialized knowledge

$45K

Per Abandoned Form

Delayed revenue plus 20+ hours of sales engineering time wasted

Overwhelming Cognitive Load

  • SNOMED codes, ERP specs, compliance frameworks
  • Non-linear field dependencies (field 12 → fields 45–52)
  • Industry-specific context required for each response
  • Unclear integration specifications

Insufficient Existing Support

  • Static help text ignored by 78% of users
  • 8–12 hour help desk response times
  • Video tutorials insufficient for complex fields
  • 20+ manual hours per customer for sales engineering

High-Stakes Data Requirements

  • Network topology → dashboard layouts
  • Compliance selections → feature sets
  • Integration specs → pricing and timelines
  • Incorrect data → costly manual cleanup

Business Impact

  • $45K delayed revenue per abandoned form
  • 20+ hours sales engineering per customer
  • Growing customer frustration and churn risk
  • Delayed time-to-value undermining retention

What They Had Already Tried

01
Simplify the Form

Eliminated necessary data collection, causing downstream configuration problems

02
Progressive Disclosure

Reduced visual overwhelm but did not solve comprehension of complex fields

03
Enhanced Help Text

Ignored by 78% of users — too generic and disconnected from context

04
Onboarding Calls

Effective but expensive and unscalable at $200+/hr for sales engineering time

05
Pre-filled Templates

Only worked 28% of the time — too much variation across industries

Core Tension

Users needed intelligent guidance through complex questions, not simpler requirements

From Static Forms to Intelligent Guidance

Our 2-week discovery phase revealed why traditional form improvements failed — and pointed to a fundamentally different approach.

01

Sales Engineering Shadowing

12 sessions observed

The valuable part was not the answers themselves — it was the contextual explanations and industry-specific guidance that sales engineers provided alongside each field.

02

User Interview Analysis

18 customers interviewed

  • 94% found questions reasonable
  • 76% needed context for WHY
  • 68% wanted industry examples
  • 89% confused about critical vs. optional
03

Form Analytics Deep Dive

400+ submissions analyzed

  • 3.7 avg sessions to complete
  • Fields 45–62 highest abandonment
  • 83% errors were formatting
  • 40% time on external docs
Breakthrough Insight

Sales engineers provided adaptive, conversational guidance — explaining purpose, providing industry examples, validating responses, skipping irrelevant questions, and reassuring about progress. We needed to replicate this intelligence, not replace it.

Why We Chose This Approach

Three key decisions shaped the InputCoach architecture and determined its success.

Why Not a Traditional Chatbot?

Chatbots require users to articulate questions they don't know how to ask. InputCoach observes behavior and proactively provides guidance at the moment of need.

  • Users don't know what they don't know
  • Chat UI competes for screen space
  • Reactive model misses hesitation signals

Why Not Simplified Forms?

Every field existed for a reason. Vertex had already tried simplification — it eliminated necessary data and caused downstream configuration failures.

  • 180+ fields each serve a purpose
  • Simplification caused data quality issues
  • Complexity is inherent to the domain

The InputCoach Approach

Embed intelligence into the form itself — observe user behavior, provide contextual guidance proactively, and validate inputs conversationally.

  • Proactive, not reactive assistance
  • Preserves full data collection
  • Replicates sales engineer expertise

InputCoach: Intelligence Embedded in the Experience

An embeddable JavaScript SDK that transforms complex forms into guided conversational experiences — operating simultaneously as an Observer, Guide, and Validator.

01

Contextual Field Explanations

Field focus triggers purpose explanation, industry context, impact clarification, and confidence building — delivered in under 200ms.

02

Intelligent Validation Engine

Conversational feedback with examples instead of generic error messages. 240+ custom validation rules with LLM semantic validation.

03

Adaptive Questioning

Shows only relevant fields based on previous answers, reducing perceived form length by 40% on average with industry-specific paths.

04

Progress Intelligence

Intelligent time estimation, section breakdown, milestone celebrations, and persistent session state across devices.

05

Session State Management

Auto-saves every field change with Redis hot storage, cross-device sync via WebSocket, and 30-day recovery window.

06

Smart Examples Library

Industry-specific examples from successful onboardings — automotive, aerospace, industrial — continuously updated and anonymized.

Comparison of generic form validation error vs InputCoach contextual conversational feedback with examples

Measurable Business Impact

InputCoach deployment transformed Vertex’s onboarding bottleneck into a competitive advantage

+110%
Completion Rate Increase

39% → 82% in 90 days. Improvement visible within 2 weeks, stabilized by week 8. 2.1x improvement delivering 43% more completions.

-67%
Time Efficiency

4.2 → 1.4 hours average. Single-session completions jumped from 18% to 64%. Average sessions dropped from 3.7 to 1.6.

$1.2M
Revenue Recovered

43% more completions × $45K average value over 6 months. 3.7 week timeline shortening plus 34% higher expansion revenue.

-90%
Sales Engineering Load

20+ hours → 2 hours per customer. Team refocused on pre-sales demos, driving 17% deal velocity increase and $180K annual savings.

+43%
Data Quality

76% validation error reduction. Completeness: 91% → 98%. Integration accuracy: 89% → 97%. 43% less manual cleanup required.

+28
NPS Increase

42 → 70 during onboarding. Customer effort score: 4.2 → 1.8. 52% support ticket reduction and 85% positive sentiment.

“Transformed what was a dreaded two-day process into a one-afternoon completion. It’s like having an implementation consultant sitting beside you.”

— Director of Procurement, Fortune 500 Automotive Manufacturer

Return on Investment (6 Months)

Revenue Recovered
$1.2M
Engineering Savings
$180K
Total Investment
$104K
Total ROI
1,650%

Technical Architecture & Innovation

Claude 3.5 Sonnet (Anthropic)

AI Engine

Superior reasoning for contextual “why” explanations, multi-turn conversation tracking, 200K token context window. Custom system prompts with industry knowledge injection and 70% cache hit rate.

JavaScript SDK

Client Integration

Framework-agnostic (React/Vue/Angular), 45KB gzipped with zero dependencies. Progressive enhancement with <200ms WebSocket delivery, HTTP polling fallback, and multi-tab sync via BroadcastChannel.

Redis + PostgreSQL

Data Layer

Redis for hot sessions with 7-day TTL, PostgreSQL for long-term storage and audit trail. Real-time sync with conflict resolution and TLS 1.3 encryption throughout.

AWS Infrastructure

Platform

Lambda auto-scaling supporting 10K+ concurrent sessions. VPC isolation with CloudWatch monitoring. Measured: <200ms guidance delivery, 99.97% uptime, 70% cache hit rate.

InputCoach system architecture showing JavaScript SDK, WebSocket communication, guidance engine with Claude integration, caching layer, and database architecture

Similar Challenges, Proven Results

See how we have solved similar challenges in UX optimization and intelligent communication across industries.

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