Product Case Study

Executive Companion Pulse

A 0→1 executive mobile companion that turned platform telemetry into a fast, trusted operating view.

Secure mobile access, glanceable health metrics, and configurable dashboards gave executives product and platform visibility between meetings — built and shipped to production.

Product

0→1 mobile app

Stack

React Native + TypeScript

Auth

Okta

Rollout

LaunchDarkly

Observability

DataDog

Shipped

Apple App Store approved

Approach

AI-assisted development

Executive Overview

82

Executive Snapshot

+3%

Revenue Health

+12%

Audience Health

+6%

Deliverability Health

+4%

Engagement Quality

+1%

Product Momentum

-9%

Pipeline Reliability

+2%

Active Risks

Product momentum trending down 9% this week

Product82% confidence

3 audience segments showing reduced engagement this week

Audience74% confidence

Opportunities

Revenue trending toward a new high this month

Revenue88% confidence

Engagement quality up across top segments

Engagement79% confidence

Deliverability holding steady near an all-time high

Deliverability91% confidence

Representative Product DemonstrationThis page recreates the product experience using original HTML/CSS components and synthetic data. It illustrates the product concepts, UX, and technical implementation while avoiding reproduction of proprietary interfaces.

Case Study

The story behind the product

The Insight

Executives had data — just not fast access to it

Executives had access to platform and product data, but it was fragmented across desktop dashboards, static reports, Slack and email updates, and status meetings. The gap wasn't more dashboards — it was faster confidence between meetings.

The Product Thesis

Compress the operating view, not replicate the desktop

Mobile shouldn't recreate a desktop analytics workspace. The right experience is glanceable, secure, and configurable — trusted enough that executives could check in confidently between meetings.

The Outcome

From side project to executive-sponsored initiative

After an internal demo, executive interest helped rally a team around the concept and move it from an unofficial effort into a funded, production-grade mobile initiative that shipped to the App Store.

My Role

Sole product owner, concept to shipped app

Product Leadership

  • Market research and competitive analysis
  • Persona definition and use-case mapping
  • Requirements and acceptance criteria
  • MVP scope and phased rollout strategy
  • Roadmap and investment case

Technical Direction

  • React Native and TypeScript
  • GraphQL API integration
  • Okta authentication integration
  • LaunchDarkly feature flags and phased rollout
  • DataDog RUM and production observability
  • Automated test coverage

~75

Days

261

Commits

63

Test Files

748

Test Cases

~75,000

Lines of Code

Customer & Account Activity

Account activity, without digging through reports

  • Rather than asking executives to dig through account reports or wait for team summaries, the mobile view surfaced account activity and status indicators in a compact format for quick review.
  • High-level activity and adoption indicators helped highlight where executive attention might be needed — not churn prediction or account intelligence modeling.
  • Kept scoped to accounts and engagement — product-level signals get their own dedicated view, described next.
Customer & Account Activity

1,284

Active Accounts

+5%

76

Avg. Engagement Score

+2%

231

New Customers

+14%

What To Do

  • Review the 3 accounts flagged for reduced activity this week.
  • Prioritize outreach to accounts trending from Growing to Stable.
  • Scale successful engagement patterns while momentum is positive.

Account Activity Overview

InterestEngagement

Account Status Mix

  • New18%
  • Growing34%
  • Stable31%
  • Needs Attention17%

Web Behavioral Signals

Where visitors come from, and what they do next

  • Real customer-facing behavioral telemetry — page views, product views, cart adds, search, and abandonment — read at an executive level, not an analyst workspace.
  • A traffic-source-to-signal flow showed where activity originated (direct, search, social, email) and what it turned into, alongside a straightforward view→product→cart→order funnel.
  • Trend indicators and freshness timestamps kept the view grounded in current data, not static reports.
Web Behavioral Signals

Signal Health

79

+3%

Updated 6m ago

Signal Types

Page Viewed
92+6%
Product Viewed
84+9%
Added to Cart
61-2%
Order Placed
58+11%
Site Search
46-4%
Cart Abandoned
39+7%
Session Started
35+3%
Profile Updated
18+1%

Traffic Source → Signal

Signal Funnel

Page → Product
52%
Product → Cart
34%
Cart → Order
41%

Signal Timing Pattern

Product Intelligence

Catalog signals, without leaving the app

  • Built on the same product catalog capability from a separate 0→1 initiative — surfaced here as an executive-level view of what's moving.
  • Top-performing categories and the product funnel (views, cart adds, purchases, abandonment) gave a fast read on where interest was and wasn't converting.
  • A drill-in, not a full commerce dashboard — enough for an executive to spot a trend, not run a merchandising review.
Product Intelligence

Top Categories

Electronics
88+6%
Apparel
74+3%
Home & Garden
61-2%
Beauty
52+9%
Grocery
45+1%

Product Signals

The product funnel behind the top-line numbers — views, cart adds, purchases, and abandonment.

Product Views18,204+6%
Added to Cart4,932+3%
Purchased1,614-4%
Cart Abandoned3,318+9%
Browse Abandoned9,847+2%

Interest vs. Conversion

InterestConversion

Internal Telemetry

A separate lens, for a separate audience

  • Reached from a menu, not the main tab bar — an internal-only diagnostic view for the team building the product, kept fully apart from customer-facing signals.
  • Mobile screen views (via production RUM/observability) and web platform feature-area usage, broken out into their own tabs.
  • When you're in this view, none of the other tabs apply — it's effectively its own small, separate app.
Telemetry Overview

Internal Telemetry

Diagnostic-only view of how the tool itself is used — kept fully separate from customer-facing data.

Active Internal Users

34

+8%

Sessions (7d)

612

+5%

Crashes / Errors

3

-40%

Executive Brief

Deterministic by default. AI-enhanced on your terms.

Every day, the app assembled an executive brief — What Changed, What To Watch, What's Working, and Recommended Actions — calculated directly from platform and product telemetry using fixed rules and thresholds. Add your own Anthropic, OpenAI, or Gemini API key in Settings, and that same trusted foundation gets described in AI-generated language instead — the same facts, put more naturally. Try the toggle below. The next step is a fully proactive agent that surfaces this on its own, not just on request.

Executive Brief

Today's Executive Brief

Every brief ships with a deterministic baseline. Bring your own API key in Settings and the same facts are described with AI-generated language instead.

What Changed

Product momentum dipped this week

Calculated automatically from usage telemetry — a rules-based comparison against the prior period.

What To Watch

A handful of accounts show reduced engagement

Flagged deterministically once an account crosses a defined engagement-decline threshold.

What's Working

A usage trend is accelerating ahead of plan

Surfaced by a fixed rule comparing current trend velocity against target.

Recommended Actions

Review accounts with declining engagement

A standing recommendation tied directly to the watch-list rule above.

Outcome

What happened

  • Gave executives and product leaders faster mobile access to trusted platform, product, and operational signals.
  • Created a production-ready mobile foundation for executive visibility.
  • Reduced dependence on manual status gathering and desktop-only dashboards.
  • Demonstrated how AI-assisted development could accelerate a production-grade internal product from concept to App Store approval.
  • Established reusable patterns for secure authentication, telemetry display, configurable cards, feature-flagged rollout, and production observability.

What I'd Build Next

  • A proactive AI agent (via Model Context Protocol) that surfaces insight automatically, not just on request
  • Explainable anomaly and risk detection
  • Recommended follow-up workflows
  • Delegation and ownership tracking
  • Drill-down to source data

Why This Matters

Executives don't need more dashboards — they need a fast, trusted signal they can check from anywhere. Pulse is what that looks like when product thinking, UX, and hands-on engineering come from the same person.