A bicycle shop with bikes on the walls and cycling gear on racks

Industries

Built for sporting and outdoors brands

Model profit after freight and markdowns, then match the next offer to the product and season.

What each team gets

Illustrative scenarios and figures. We model your actual costs, customer behaviour and business rules.

Founder and finance

A healthy total hides customers whose costs exceed their sales.

TodayContribution

$9.8m

76,000 customers

With customer-level profitContribution

+$12.6m

52,000 customers24,000 customers −$2.8m

Action: See contribution by customer and cohort over an agreed period, then decide where to invest.

Growth

A discounted tent wins the sale. Freight can erase the profit.

TodayRevenue ROAS

The first order looks good Markdowns, bulky delivery and later purchases are disconnected

With customer-level profitCustomer contribution

Compare first-product cohorts Include acquisition, freight, returns and later accessory orders

Action: Recommend acquisition audiences using mature customer contribution.

Your expertise, embedded: Finance sets payback periods; merchandising keeps clearance objectives separate.

CRM

A runner may need shoes again. A tent buyer needs a different offer.

TodayOne repeat campaign

Same reminder for everyone Equipment and consumables have different purchase cycles

With customer-level profitProduct + season

The next useful purchase Distinguish durable equipment, replenishment and compatible accessories

Action: Trigger relevant reminders or accessory offers within the right seasonal window.

Your expertise, embedded: Your product experts define compatibility and timing; CRM sets contact limits.

Ecommerce

The same basket value can mean a parcel or an oversized carton.

TodayFree delivery

One threshold Dimensions and remote delivery costs disappear in the average

With customer-level profitActual fulfilment cost

Profit after delivery Join courier tariffs, product dimensions and customer contribution

Action: Flag costly delivery combinations and test a published threshold or bundle.

Your expertise, embedded: Operations defines delivery zones, service exceptions and customer promises.

The closest case to sporting and outdoors

Bikes on display racks in a large bike store

Closest case, apparel retail

A $80m apparel retailer, 25 stores and online

Customer data sat in POS, Shopify and Klaviyo with no way to act on it. We joined it into one record per customer, ranked by gross margin.

We don't have a sporting and outdoors client we can show yet. The closest is an omnichannel apparel retailer with the same store-plus-online customer problem.

Read the case study →

5%of customers make 38% of gross margin

66%of new customers didn't come back within a year

~$3mestimated extra revenue from targeted actions