Cyber Monday Order Threshold Discount on Shopify Using Flowly

"10% off orders over $50" is the first example in Flowly's own documentation. Here's the simplest possible build, and when it's actually enough.

Not every Cyber Monday promotion needs to be complicated. Flowly's own documentation opens its list of ten ready-to-build examples with the simplest possible version of a discount: "10% off orders over $50." No collection targeting, no customer segment restriction, no multi-tier structure, just a single spend threshold and a single reward.

Here's how to build it, and a genuinely useful question: when is this simple version actually the right call instead of something more elaborate.

What does the simplest Flowly discount actually look like?

A single-tier order threshold discount takes exactly three nodes: a Start node, a Condition node checking Cart subtotal against one threshold, and an Apply Discount node applying a Percentage off or Fixed amount off to the Order subtotal. This sits entirely within the Order discount class, using its one available target, Order subtotal, with no need for the Array-based cart-line or delivery-level conditions that more targeted promotions require. It's the fastest possible build in the entire system, and it's genuinely sufficient for a large share of straightforward Cyber Monday promotions.

How do you build "10% off orders over $50" exactly as documented?

The build takes three nodes total: Start, a Condition node with a leaf predicate checking Cart subtotal "Greater than or equal" to $50, and an Apply Discount node set to Percentage off (10%), targeting Order subtotal. Here's the sequence:

  1. Add a Start node.

  2. Add a Condition node with a single leaf predicate: Cart subtotal Greater than or equal to $50.

  3. Add an Apply Discount node, action set to Percentage off (10%), target set to Order subtotal, within the Order discount class.

  4. Save. Flowly's validator checks the shape before compiling the flow into a versioned rule config, synced to the shop's metafield and read by the shared Shopify Function at every checkout.

No Array condition, no Logical AND/OR/NOT nesting required, this is a single Leaf predicate feeding directly into a single reward. It's worth building exactly this simple version before adding complexity, both as a way to confirm the basic mechanics work as expected and as a legitimate standalone promotion in its own right.

When is a single flat threshold actually the right call instead of a tiered structure?

A single threshold makes sense for a store with a narrow, relatively consistent product price range, a straightforward catalog where a tiered structure wouldn't meaningfully differentiate between customer segments, or for a merchant testing Flowly for the first time before building anything more elaborate. Tiered structures, multiple thresholds each with a different rate, add real value for stores with a wide range of cart sizes, since they can reward the biggest carts more than a flat rate would. But for a smaller catalog or a first Cyber Monday campaign built on Flowly, the single-tier version is a legitimate, complete promotion, not just a stepping stone toward something more complex.

Does a simple threshold discount need a selection strategy at all?

If it's the only active Order-class discount, no, since there's nothing else to resolve a conflict against, but the moment a second Order-class discount becomes active, First or All still needs to be set explicitly rather than left to whatever Shopify's default behavior produces. A standalone $50 threshold discount running in isolation doesn't need to think about selection strategy at all. The moment a store adds a second offer, a logged-in customer discount, another spend tier, that same simple rule needs its resolution behavior defined, even if it started life as the only discount in play.

FAQ

Is $50 the right threshold for every store, or should it change based on average order value?

$50 is Flowly's documented example, not a universal recommendation. The right threshold for any specific store is typically set 20-30% above current average order value, high enough to meaningfully encourage a bigger cart, low enough to feel achievable.

Should this run as an automatic discount or a code?

Automatic, for Cyber Monday specifically. Automatic discounts apply the moment eligibility is met, with no customer action required, which matters more during a high-traffic shopping day than during a normal week, since every extra step between a customer and checkout costs some conversion.

Can a simple threshold discount be upgraded into a tiered structure later without starting over?

Yes. Since each tier is its own separate rule in Flowly, adding a second and third threshold later means building additional rules alongside the original, not rebuilding the first one from scratch.

Is there any downside to starting with the simple version instead of going straight to a tiered structure?

Not really, beyond potentially leaving some AOV upside on the table if your store's cart sizes vary widely enough that a tiered structure would meaningfully outperform a flat rate. For most first-time builds, starting simple and adding complexity once the basics are confirmed working is the more reliable path.

Where this fits into a bigger Cyber Monday picture

Even the simplest possible discount still only solves one problem: getting someone to buy today. It doesn't answer the bigger question of whether that customer buys again next month, or next year. That's a separate, ongoing relationship, and it's exactly what Subscribfy is built to create, paid memberships that turn a single Cyber Monday order into recurring revenue instead of a one-time transaction. Across Subscribfy's client base, member cohorts outperform non-members by 2 to 4x across every metric that matters, a gap that starts to close only once a store moves past thinking in single transactions.

Download Flowly directly from the Shopify App Store to build this simplest example for Cyber Monday, or book a call with Subscribfy's team to talk through what comes after the first sale.

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