Skip to Content
Enterprise SaaS Case Study

InputCoach: Smart Form Optimization

AI-powered contextual guidance that transformed a 180+ field enterprise onboarding form from 39% completion to 82% — recovering $1.2M in deferred revenue.

+110% Completion Rate
-67% Completion Time
$1.2M Revenue Recovered
Before and after comparison: traditional static form vs InputCoach-enhanced form with intelligent AI coaching sidebar
The Challenge

The Onboarding Bottleneck

Vertex Enterprise Solutions — a supply chain optimization platform for Fortune 1000 manufacturers — faced a critical onboarding problem. 61% of customers abandoned a 180+ field configuration form, costing $45K per abandoned form in delayed revenue and 20+ hours of sales engineering time.

61%

Abandonment rate — customers who never completed onboarding configuration

180+

Form fields spanning 12 sections requiring specialized industry knowledge

$45K

Delayed revenue per abandoned form plus 20+ hours of wasted engineering time

Overwhelming Cognitive Load

SNOMED codes, ERP specs, compliance frameworks — non-linear field dependencies where field 12 impacted fields 45–52. Static help text was ignored by 78% of users, and 8–12 hour help desk response times left customers stranded.

Failed Prior Attempts

Vertex had tried simplifying the form (caused downstream data issues), progressive disclosure (didn’t solve comprehension), enhanced help text (ignored by 78%), onboarding calls ($200+/hr, unscalable), and pre-filled templates (only 28% match rate).

The Solution

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. Rather than simplifying the form, we made the complexity manageable.

01 — Contextual Guidance

Field Explanations

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

02 — Validation Engine

Conversational Feedback

240+ custom validation rules with LLM semantic validation. Provides examples instead of generic error messages, reducing validation errors by 76%.

03 — Adaptive Questioning

Smart Field Paths

Shows only relevant fields based on previous answers, reducing perceived form length by 40% on average with industry-specific paths for automotive, aerospace, and industrial sectors.

04 — Progress Intelligence

Smart Estimation

Intelligent time estimation, section breakdown, milestone celebrations, and persistent session state across devices with 30-day recovery window.

05 — Session Management

Cross-Device Sync

Auto-saves every field change with Redis hot storage, cross-device sync via WebSocket, and conflict resolution with TLS 1.3 encryption throughout.

06 — Examples Library

Industry-Specific

Examples from successful onboardings across automotive, aerospace, and industrial sectors — continuously updated and anonymized from real submissions.

Under the Hood

Technical Architecture

JavaScript SDK communicates via WebSocket to the guidance engine powered by Claude 3.5 Sonnet, with Redis hot caching and PostgreSQL long-term storage on AWS Lambda infrastructure.

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

Measurable Business Impact

InputCoach transformed Vertex’s onboarding bottleneck into a competitive advantage within 90 days of deployment.

+110%

Completion Rate

39% to 82% in 90 days. 2.1x improvement visible within 2 weeks, stabilized by week 8.

-67%

Time to Complete

4.2 to 1.4 hours average. Single-session completions jumped from 18% to 64%.

$1.2M

Revenue Recovered

43% more completions at $45K average value over 6 months, with 34% higher expansion revenue.

-90%

Engineering Load

20+ hours down to 2 hours per customer. Team refocused on pre-sales, driving 17% deal velocity increase.

+28

NPS Increase

42 to 70 during onboarding. Customer effort score improved from 4.2 to 1.8.

1,650%

Total ROI

$1.38M total return on $104K investment over 6 months including engineering savings.

Implementation

Discovery to Production in 12 Weeks

A phased approach: 2 weeks discovery, 6 weeks MVP build, 4 weeks optimization and scaling.

01

Discovery

Weeks 1–2

Shadowed 12 sales engineering sessions, interviewed 18 customers, analyzed 400+ form submissions. Identified that users needed guidance, not simplification.

02

MVP Build

Weeks 3–8

Built JavaScript SDK (45KB gzipped, zero dependencies), integrated Claude 3.5 Sonnet for contextual guidance, and deployed WebSocket real-time delivery under 200ms.

03

Optimization

Weeks 9–12

240+ custom validation rules, adaptive questioning paths for automotive/aerospace/industrial, Redis caching achieving 70% hit rate, and session state management.

04

Results

Day 90

Completion rate 39% to 82%, completion time down 67%, $1.2M revenue recovered, and 90% reduction in sales engineering support load.

Technology

Tech Stack Used

Anthropic Claude

Claude 3.5

React

React

TypeScript

TypeScript

Python

Python

AWS

AWS

Docker

Docker

Client Feedback

“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

Have a Similar Challenge?

Let’s discuss how AI-powered form intelligence can transform your onboarding, reduce abandonment, and recover revenue.

Start a Conversation Back to Home