Use case

The next product is already implied by the last one

Every order narrows what a customer is likely to buy next. RevBridge reads the catalogue against each customer's history and tests the recommendation, the moment, and the channel that lift basket size without discounting it away.

Live in the product

A recommendation is a claim about the customer. Test it like one

app.revbridge.ai/engagement/analytics

RevBridge AI

Dashboard

People

Engagement

Campaigns

Conversations

Warmup

Analytics

Growth

Assets

Definitions

Data

Settings

MR

Marina Reis

Verdant

Analytics

Measure campaign funnels, channel mix, attribution, and creative performance.

Creative Optimization

Traditional: 10%

RevBridge: 90%

Traffic Distribution per Round

Success Rate per Variant

Variants

V1

51%

Goes with what you already own

V2

27%

Customers who bought this also bought

V3

19%

Complete the set

V4

3%

Bundle both and save

Optimization Lift

Open Rate

33.1%

27.6%

+19.9%

Highly significant

Click Rate

23.9%

18.4%

+29.9%

Highly significant

Unsub Rate

0.21%

0.38%

-44.7%

Significant

Avg Reward

0.412

0.318

+29.6%

Significant
VariantSelectionsShareSuccess RateConfidence

V1

Goes with what you already own

BEST
3,94051%24.8%

High

Highly significant

V2

Customers who bought this also bought

2,61027%22.4%

Good

Significant

V3

Complete the set

1,72019%19.7%

Medium

Marginal

V4

Bundle both and save

3803%11.6%

Medium

Marginal

Creative optimization on a cross-sell campaign. The line that reasons from what the customer already owns is beating the bundle discount, which is losing traffic every round.

+19%

lift in average order value

2.8x

return on cross-sell spend

6

motivation archetypes tested per recommendation

Illustrative figures. RevBridge reports your own numbers against a randomized holdout.

The expensive way to lift a basket is to bundle and discount it

Bundling and discounting works: the basket grows and the margin shrinks by the same amount. That is why so many cross-sell programs report a lift in average order value and no lift in profit. A recommendation that is genuinely right needs no discount, because it is not buying the customer's yes, it is getting the product right.

RevBridge reads the catalogue against the history held in Customer 360 and treats each recommendation as a variant the Multi-Armed Bandit engine puts into competition. Brand DNA writes the versions, crossing the six motivation archetypes, and conversion decides which of them was right about that customer.

What this play requires

Unlike the others, cross-sell needs line-item detail, not just the order value. Shopify supplies this out of the box; an API or CSV feed has to carry the products. If your catalogue is still narrow, the second purchase and replenishment will move revenue faster.

What RevBridge brings to cross-sell

One optimization engine, pointed at the outcomes your team is measured on.

Bigger baskets without a bigger discount

The usual way to lift order value is to bundle and discount, which grows the basket and shrinks the margin. A recommendation that is genuinely right does neither. The engine tests both and lets the numbers decide which one you are actually running.

The adjacency is different for every customer

What goes with a purchase is not a property of the product, it is a property of the person who bought it. Customer 360 holds the history, and the engine tests the adjacency per customer rather than shipping one recommendation rule for the whole catalogue.

It is a message, not a merchandising project

Most cross-sell lives on the product page and dies there. Moving it into messaging means it reaches the customer when they are not shopping, which is where the incremental order actually comes from.

Why they buy, not just what

The same recommendation lands differently framed as a saving, a status, or a practicality. RevBridge tests across the six motivation archetypes, so the recommendation is matched to the appeal the customer responds to.

How teams put RevBridge to work

Concrete plays that go live in the first campaign, not the third quarter.

Post-purchase accessory and add-on

The highest-intent moment in the lifecycle. The customer has just committed to the category, and the complement is an easy yes if it arrives before the purchase cools.

Category expansion

Moving a single-category buyer to a second shelf is what turns a customer into an account. The engine finds which adjacent category each customer is closest to crossing into.

Upgrade and tier-up

Some customers bought the entry product and would have paid more. Test the upgrade against the accessory and find out which segment is which, instead of assuming everybody wants the cheaper add-on.

Basket building before checkout

Paired with cart recovery, the same engine can decide whether the message that brings a cart back should also carry a complement, or whether that only adds friction to the recovery.

Keep exploring

Related solutions

Different starting point, same engine underneath. See how RevBridge maps to the rest of your motion.

Frequently asked questions

See what RevBridge can do for cross-sell

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