Abando

Women's boutique apparel demo

See how Abando reads shopper behavior and turns it into recovered orders.

This demo uses a women's boutique apparel store as an example. In production, Abando watches what shoppers view, search, and leave in their cart, then turns those sessions into a few clear shopper patterns instead of treating everyone who abandoned the same way.

Built forShopify

1 · Why segments instead of "everyone who abandoned"?

Some shoppers are almost ready. Others are still browsing.

Not every abandoned cart is the same. Some shoppers are checking outfits on their phone at work. Others park items while they wait for payday. Treating them all the same leads to noisy discounts and trained bargain hunters. Abando keeps your strategy simple and targeted instead of shouting at everyone.

2 · Three high-impact patterns in this boutique demo

Today's key patterns in this boutique demo

Names are just for clarity, not jargon. Each pattern is a different kind of hesitation Abando knows how to respond to.

Pattern 1 · Cart parkers

They park pieces "to think about it"

Shopper likes the item but isn't sure about fit, occasion, or total spend. They're mentally trying on outfits and need reassurance more than a bigger coupon.

How Abando responds

Sends a delayed nudge like "Still love this look? Here's how other customers styled it" instead of a generic 10%-off blast.

Pattern 2 · Size checkers

They bounce between sizes & size charts

Fear of ordering the wrong size—especially on dresses, denim, and fitted tops. They pause until they feel confident they won't have to deal with returns.

How Abando responds

Plays that lead with sizing confidence and fit proof (reviews, photos, try-at-home messaging) instead of pure discounts.

Pattern 3 · Drop watchers

They wait for new arrivals or a better deal

Shopper is engaged but waits for a signal—new drop, low-stock alert, or limited-time offer—before committing.

How Abando responds

Gentle urgency plays tied to low-stock sizes, bundle suggestions, or "last chance for this collection" instead of constant promos.

3 · What this means over a week

7-day recovered orders snapshot

This example boutique recovers a handful of extra outfits per day—small lifts that add up. In a live account, this view is driven by your real Shopify data and lets you compare patterns like cart parkers vs. drop watchers.

Across the full week, this demo recovers just over $5,000 in orders that would have been lost — all from small, pattern-driven plays instead of blanket discounts.

Weekly impact

40+ extra orders and just over $5,000 in recovered revenue in 7 days.

That's like adding an extra day of sales every week — without buying more traffic or blasting bigger coupons. In a live account, this roll-up ties directly to your real recovered orders.

Highlight of the day

Sat 8 orders: 8 recovered orders ($920 demo revenue)

Shopper pattern

Drop watchers

Shoppers were waiting on low-stock and restock cues before checking out.

What's really going on

Shoppers were waiting on low-stock and restock cues before checking out.

How Abando gets them back

Urgency plays tied to low-stock sizes and “last chance for this weekend” messaging.

4 · How Abando turns raw signal into guided plays

What the raw signal looks like

Under the hood, Abando is watching anonymous event streams such as views, size-guide checks, add-to-cart, and checkout steps. Those noisy events roll up into a small number of patterns your team can act on.

[
  {
    "session_id": "s_1432",
    "events": [
      "view/dresses/midi-wrap",
      "view/size-guide/dresses",
      "add_to_cart:SKU-DF-102",
      "view/returns-policy",
      "abandon_checkout"
    ]
  },
  {
    "session_id": "b3c__",
    "events": [
      "view/tops/cropped-knit",
      "add_to_cart:SKU-CK-204",
      "abandon_checkout"
    ]
  }
]

Abando sees raw events like this across hundreds of sessions, then groups them into patterns your team can actually act on.

Raw shopper events

Clicks, searches, size-guide views, add-to-cart, and checkout steps Abando receives from Shopify.

Behavior patterns

Abando clusters sessions into hesitation types like Cart Parkers, Size Checkers, and Drop Watchers instead of one big "abandoned" bucket.

Guided plays

Each pattern maps to a small set of proven plays so your team chooses tone and channels—not targeting logic.