In Part 1 of this series, we looked at why centralized ecommerce data beats plugin-heavy stacks. In Part 2, we showed how UltraCart’s native AI agents use that centralized data to deliver AI that actually knows your store.
In this article, we’re zooming in on one of the biggest practical wins of centralized data: Flows in UltraCart’s StoreFront Communications.
Flows are UltraCart’s built-in automation engine for behavior-based communication and personalization. Because they run on the same centralized ecommerce data as your checkout and orders, you can trigger and tailor messaging based on real customer behavior, not just static lists.
We’ll cover:
- What Flows are and how they differ from campaigns
- How centralized data makes triggers and conditions much smarter
- How Steps let you build nuanced, data-driven journeys
- Real examples like abandoned cart and post-purchase review flows
- How analytics and AI help you keep improving over time
Upsells deserve their own spotlight, so we’ll cover UltraCart’s Upsell Engine and centralized data in the next article.
What Flows Are (and Why They’re Native Matters)
UltraCart’s StoreFront Communications is a marketing platform built directly into UltraCart and seamlessly integrated with StoreFronts. It includes modern segmentation, automated flows, broadcast campaigns, postcards, and detailed tracking—all in the same system as your ecommerce checkout.
Within that system:
- Flows are event-triggered, per-customer journeys—think abandoned cart recovery, review requests, win-back sequences, etc.
- Campaigns are scheduled broadcasts sent to lists and segments at a specific time.
Flows are communication sequences that usually start from an event and can be further filtered by properties of the customer, their order, or their cart.
Because Flows live inside UltraCart, they have direct access to:
- Orders, carts, items, and shipping status
- Customer profiles, properties, and segments
- StoreFront communications data (opens, clicks, flow history)
No external marketing platform, no stitching together webhooks—just one data brain powering your flows.
Centralized Data = Smarter Triggers
Most external email tools can trigger off simple events: “joined list,” “clicked link,” “opened email.” UltraCart Flows go far beyond that, because they can trigger off true ecommerce events tied to your centralized data.
- Automate abandoned cart recovery
- Trigger post-purchase review requests
- Run re-engagement campaigns
- Deliver postcard promotions and email sequences
- Dynamically segment customers based on system events and purchase history
- Trigger a flow when an event occurs (abandoned cart, order placed, shipment, etc.)
- Further narrow entry using filters like “Someone’s Cart” or “Someone’s Order”—for example, only customers whose order contains a certain item or exceeds a certain value.
Because UltraCart is both your storefront and your marketing engine, Flows can answer questions like:
- “Start a replenishment flow 30 days after someone buys Product X.”
- “Start a VIP nurture series when a customer’s LTV goes over $300.”
- “Start a win-back flow if a customer hasn’t ordered in 90 days and hasn’t opened the last three campaigns.”
You’re not guessing based on crude tags—you’re triggering targeted marketing and sales automations off live ecommerce data.
Building Journeys with Steps (No Extra Tools Required)
Every Flow in UltraCart is built from Steps, which are reusable building blocks for automation. The Steps documentation lays out a rich set of step types. Some of the most important for personalization:
- Wait / Delay steps
Control timing: e.g., “wait 3 hours after cart abandonment” or “wait 21 days after shipment.” - Condition steps
Branch based on data (order value, items, number of orders, profile flags, etc.). - Split steps
Randomly split traffic (e.g., 50/50) for A/B testing messaging or incentives right inside the flow. - Update Profile
Add or update custom properties on the customer profile (text, number, date, boolean). These profile fields later fuel more precise segments and flows. - Send Email / Resend Email
Core communication, including resends when the first message isn’t opened. - Send Postcard
Add physical mail into the same automated journey. - Send Webhook
Notify external systems or CRMs when milestones are hit in the flow.
Because these steps operate on UltraCart’s centralized data, you can do things like:
- Mark a customer as “engaged” or “at risk” using Update Profile as they move through flows.
- Use Condition or Split steps to test whether free shipping, a percentage discount, or a bonus gift works best for a specific segment.
- Fire a webhook from a step to notify another system when a high-value customer hits a certain point in a flow.
The net effect: you’re not just sending emails, you’re orchestrating behavior-based journeys across channels using one data model.
Real-World Examples: Flows in Action
Centralized data and flexible steps are nice in theory—but what does it look like in practice? UltraCart’s public articles give a couple of great examples you can use as patterns.
Abandoned Cart Recovery
The article Boost Your Sales with UltraCart’s Abandoned Cart Flow explains how to:
- Capture emails as soon as they’re entered in checkout using proactive collection.
- Enable the pre-built “Example: Abandon Cart” flow from the Flow Library.
- Customize branding, timing (via a Wait step), and content.
Because UltraCart knows the cart contents and customer email and handles the storefront and checkout, the flow can send a branded email with a live summary of the cart and a link that drops the customer straight back into checkout, with no external cart recovery service, apis or integrations needed.
Post-Purchase Review Requests
The article Encouraging Post-Purchase Reviews With Flows describes how to:
- Add the “Encourage Item Review” flow from the Flow Library.
- Wait ~3 weeks after shipment before sending the initial review request.
- Automatically resend if the initial email isn’t opened.
Flows use order data and shipment timing from UltraCart to hit the sweet spot: long enough that customers have used the product but not so long they have forgotten, and because the review engine is also native, the email can show order details, deep link customers to leave a verified review, and feed collected reviews back into your product pages and future flows, with centralized data doing the heavy lifting.
Segmentation & Statistics: Personalization with Feedback Loops
Flows get even more powerful when you combine them with lists, segments, and statistics in StoreFront Communications.
- Lists let you group contacts (imports, forms, etc.).
- Segments let you dynamically filter customers based on behavior—email engagement, cart activity, purchase history, Facebook audience sync, and more.
Flows get even more powerful when you combine them with lists, segments, and statistics in StoreFront Communications, since lists let you group contacts from imports, forms, and other sources, while segments let you dynamically filter customers based on behavior like email engagement, cart activity, purchase history, or synced audiences; together, they make it easy to control who enters a flow, precisely target campaigns, and build high-value audiences for future marketing.
On the analytics side, the Statistics page for StoreFront Communications shows:
- Plan usage and high-level health metrics
- Flow and campaign performance over a chosen date range
- Step-level stats including how many customers go down each branch of a Condition or Split step
If you make a big change to a flow, you can even reset statistics to get a clean read on performance.
Because stats are tied directly to orders and customers, optimization isn’t about opens alone—you can see which flows and steps are actually driving revenue and retention.
Where AI Fits In
In Part 2, we covered how UltraCart’s AI Report Builder, Viewer, and Dashboards sit on top of your centralized ecommerce data.
That same AI layer can help you:
- Identify which flows drive the most revenue, not just engagement.
- Spot segments or behaviors that deserve their own dedicated flow (e.g., high-LTV customers who haven’t ordered in 60 days).
- Iterate on timing and incentives using real performance data, not guesswork.
Because flows, AI reporting, and your storefront all use the same data warehouse, you don’t have to copy data out to another system to understand what’s working.