Our Story
Alpine Apparel
Alpine Apparel sells premium outdoor performance gear across a growing eCommerce business and 50 physical retail stores. Your omnichannel customers spend significantly more, buy more frequently, and stay longer than customers who shop only one channel. Your goal is to build more of these omnichannel customers, but the execution path doesn't exist.
Current State: Your current emails have no idea which customers are omnichannel, which customers have never visited a store, or which post-purchase moments are the right ones to close that gap. Much of that data lives in your OMS Fluent Commerce (which is common for many large brands), and today, Fluent Commerce and your marketing platform don't speak the same language.
The Result: every customer gets the same post-purchase emails.
Omnichannel customers are your most valuable. You just can't create more of them.
The data is clear. Omnichannel shoppers, customers who engage with both the digital and physical brand, outperform single-channel customers on every retention metric.
One signal isn't enough. Two customers, two missed opportunities.
When an order ships, your ESP receives one signal from Fluent Commerce: "Fulfilled." Here's what that means for two specific customers today:
Today
With Klaviyo
in_store_candidate: true. On-time delivery + online-only + store nearby = omnichannel conversion opportunity. Flow routes to in-store invitation email with store address and hours.
purchase_channel: in_store routes him to in_store_recovery. Recovery email references his physical brand relationship. Different message, different outcome, same platform.
An omnichannel customer building pipeline.
The pipeline uses Airtable for event storage, Pipedream for orchestration, Claude for AI enrichment, and Klaviyo's Events API as the destination. In production, Airtable becomes Fluent Commerce's native webhook. The pipeline doesn't care what OMS is behind it — that's the point.
OMS Event — Fluent Commerce fires
An order lifecycle event — DELIVERED, DELIVERY_FAILED, or RETURNED — fires from Fluent Commerce with full context: carrier, tracking, customer LTV, purchase channel, delivery promise date, return history. In this proof of concept, Airtable simulates the webhook. Same data shape, same pipeline.
Store Location Lookup — Pipedream fetches at runtime
Pipedream reads the customer's ship-to city and matches it against Alpine Apparel's store location database. In production this is a call to their store locator API or ERP. has_nearby_store, nearest_store_name, nearest_store_address, and nearest_store_hours are all resolved before Claude sees the event.
Claude Enrichment — AI reasoning over full context
Claude evaluates the complete order context and returns structured JSON: event type, fraud signal, customer tier, delivered_on_time, purchase channel, in_store_candidate, recommended action, action urgency, and a one-sentence ai_reasoning that explains the recommendation in plain English — stored directly on the Klaviyo event and auditable by anyone on the team.
Klaviyo Event — enriched intelligence lands on the profile
Pipedream posts the enriched event to Klaviyo via the Events API. Every enriched property — including store details, channel context, and Claude's reasoning — is now available to Klaviyo's segments, flows, and profile views. The marketing team never needs to open Pipedream or Airtable.
Klaviyo Acts — automatically, on every order
Segments evaluate the enriched properties in real time. Flows fire the right communication for the right customer situation. The in_store_candidate segment populates with digital-native customers who had a positive delivery experience near a store — a segment that didn't exist in Klaviyo before this pipeline.
One intelligence layer. Four automated responses.
Every OMS event is evaluated by Claude and routed to the correct Klaviyo flow automatically. The same pipeline that enables omnichannel conversion also handles VIP recovery, late delivery apology, and fraud suppression.
delivered_on_time: true
purchase_channel: online
purchase_channel: in_store
recommended_action: in_store_recovery
fraud_signal: false
recommended_action: proactive_notify
action_urgency: high
recommended_action: fraud_review
This pipeline is running right now.
Live since April 7, 2026. These numbers are pulled directly from the Klaviyo account powering this store.
Converting online customers into omnichannel customers is the highest-leverage move in retail.
Omnichannel customers spend 2–3x more annually and retain at 89% higher rates. Alpine Apparel's pipeline is designed first and foremost to close that gap — surfacing the right post-purchase moment to move an online-only buyer into their first in-store visit. Everything else the pipeline does compounds on top of that primary conversion.
In the first 72 hours of running, 210 in-store acquisition candidates were identified from the live order stream. Annualized, that's roughly 25,000 high-intent moments per year to make that ask at exactly the right time.
| Flow | What it does | Live segment | Conservative annual value |
|---|---|---|---|
| In-Store Invitation | Converts online-only customers post-delivery into their first store visit | 210 profiles | $400K–$700K incremental revenue from omnichannel conversion |
| VIP Exception Recovery | Prevents churn on highest-LTV customers after a carrier exception or late delivery | 747 profiles | $17K–$22K retained VIP revenue |
| Late Delivery Apology | Drives repeat purchase after a service failure with a unique recovery coupon | All late deliveries | $200K+ recovered at-risk revenue |
| Fraud Suppression | Blocks promotional spend and recovery flows before they reach flagged accounts | 55 profiles | $150K+ in protected coupon exposure |
Assumptions: 500K annual orders, $145 online AOV, $210 in-store AOV, 8–10% email-to-visit conversion on in-store invitation. VIP recovery based on 5K VIP customers, 15% exception rate, 35% retention lift from proactive outreach. All figures conservative.
Your omnichannel strategy is already decided. Klaviyo can execute it.
You've done the analysis. Omnichannel customers spend more, retain longer, and cost less to keep. The board has seen the slide. The priority is set. What you haven't had is a path from that strategy to a Klaviyo flow — because the intelligence that would power it has been sitting in Fluent Commerce, untranslated, while every customer gets the same post-purchase email regardless of how they shop, where they live, or what went wrong with their order.
What you saw running in this room isn't a prototype or a proof of concept that needs six months of engineering before it's real. It's live. Jude Brooks's in-store invitation went out automatically. Cruz Cox's recovery email acknowledged his physical brand relationship without anyone configuring a rule. No one touched a workflow. The system decided.
What you're being asked to approve is a solution that is working, documented, extensible, and built specifically around the problem you came in with. The omnichannel execution path your strategy has been waiting for exists. It's running on your data. The only thing left is the decision.
A repeatable pattern for Klaviyo's enterprise motion — in the room and in production.
Alpine Apparel is a fictional brand but the problem is real. Any enterprise brand running a non-native OMS — Fluent Commerce, SAP, Manhattan, a custom build — with a physical retail presence faces this exact gap. This pipeline is the pattern that closes it.
Omnichannel conversion at scale
The in_store_candidate segment automatically identifies digital-native customers with positive delivery experiences near a store — a net new Klaviyo capability that didn't exist before this pipeline. This is the execution path for Alpine Apparel's omnichannel strategy.
Channel-aware communication
purchase_channel from the OMS gives Klaviyo context it has never had before — whether a customer's relationship with the brand is digital, physical, or both. Every flow, every segment, every email can now respond to who the customer actually is.
AI reasoning that's auditable
Every event carries ai_reasoning — a plain-English explanation of why Claude made the recommendation it made. Visible in Klaviyo's profile view. Your CS team, marketing team, and fraud team can all see exactly why a customer got the communication they got.
Repeatable as a demo engineering pattern
This pipeline was built end-to-end as a working proof of concept — Pipedream workflow, enrichment schema, Klaviyo flows, segments, and email templates — in days, not weeks. The same approach applies to any enterprise prospect with an OMS gap: swap the brand, update the store locations table, and the pipeline is live. It's a Solution Recipe that an SE team can deploy, not just present.
Six components, all working together.
Airtable → Fluent Commerce
Simulates Fluent Commerce OMS webhooks including a dedicated Store Locations table. In production: Fluent's native event stream + store locator API.
Pipedream
Orchestration layer. Polls for OMS events, fetches store location data at runtime, calls Claude for enrichment, pushes to Klaviyo Events API. Suggested directly in the brief.
Claude (Anthropic)
AI enrichment layer. Evaluates full order context and returns structured intelligence including fraud signals, delivery timing, channel context, in_store_candidate, and auditable reasoning.
Klaviyo Events API
Receives enriched events, creates and updates profiles, populates custom properties, and triggers segments and flows in real time.
Shopify
Storefront layer completing the end-to-end picture — product catalog, Our Story page, Store Locator, and Get Help page all consistent with the demo environment.
Klaviyo MCP
Layer 3 of the demo — Claude.ai with Klaviyo's native MCP connector queries the live account, surfaces insights, and takes action through Klaviyo's own APIs in real time.
10 years of enterprise SaaS. One proof of concept.
Every decision in this pipeline — the architecture, the enrichment schema, the flow logic, the omnichannel positioning — draws on real patterns I've seen and solved across enterprise retail accounts.
Feb 2026
Manager, Solutions Engineering
Led a global team of 6 SEs across US and EMEA supporting Enterprise and Mid-Market segments. Built SE frameworks where minimal process existed — competency scorecards, demo standards, Fast-Track vs. Expert-Track qualification. Led AI copilot adoption for GTM: designed baseline surveys, mapped use cases, and built the business case that beat out competing tools.
Jan 2025
Senior Solutions Engineer — Strategic & Enterprise
Designed a multi-tier customer notification preference system for a healthcare company processing 30M annual orders. Implemented a multi-persona messaging strategy for gift transactions using conditional content rendering based on customer profile. Explained AI-powered products to both technical and business audiences.
Sep 2024
Solutions Engineer — Strategic & Enterprise
Led technical strategy in 6-7 figure enterprise deals with C-Suite stakeholders. Developed exception-based triggered messaging for an automotive retailer: when shipment ETA diverged from a customer's installation appointment, the system automatically alerted them via email/SMS. Operated without a manager for 6+ months reporting directly to the CRO.
Mar 2022
Technical Account Manager — Unified Commerce Platform
High-touch technical support for the two largest enterprise clients on the platform (OMS, iPaaS, POS). Built executive relationships, ran QBRs, and diagnosed complex issues across distributed systems working directly with Engineering to implement permanent fixes.
Apr 2020
Solutions Architect — Unified Commerce Platform
Led technical sales for retailers with $100M–$8B in revenue. Designed end-to-end solution architectures integrating eCommerce, OMS, WMS, and TMS. Built custom demo environments showcasing real-time event orchestration.
Dec 2018
Business Development Representative
Built pipeline from $100K to $9.4M in qualified opportunities in 2018 alone, targeting retailers with $100M–$8B in annual revenue. Developed go-to-market messaging for the Dropship solution increasing qualified meetings 15x year-over-year.
Mar 2016
Founder & Partner
Co-founded a software startup digitizing change due after cash payments. Wrote the business plan, led fundraising, hired developers, and secured U.S. Provisional Patent No. 62/127,058.
The skills that made this proof of concept possible.
Development & Integration
Customer Messaging
Enterprise Pre-Sales
Thank you.
I appreciate the Klaviyo team hosting me in Boston and the time everyone invested in the day. The exercise helped me get a much better understanding of the platform and team and where the company is headed. Please let me know if I can answer any additional questions.
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