Farmer Jane's loyalty members spend 18.5% more and come back 3.3 days sooner.
The Prairies are the densest, most price-sensitive cannabis market in Canada, and inducement rules take the old visit-based punch card off the table. Farmer Jane launched a spend-linked wallet program across 18 stores instead. This is what the first 100 days looked like.
Figures below are Farmer Jane's actual results over the program's first 100 days, taken from the joint Farmer Jane × Sticky Cards performance review.
Jane
The Prairies are dense, and they are price-sensitive.
Canada hit $482.3M in monthly cannabis retail sales in May 2025, with roughly 72% of demand now captured by the legal market. The trendline keeps climbing. So does the number of doors competing for it.
In a market this saturated, discounting is a race everyone loses. Farmer Jane wanted the other lever: knowing who their best customers were, and giving them a reason to come back sooner.
From counting visits to rewarding spend and relevance.
Inducement restrictions rule out the classic visit-based punch-card offer. Whatever you build has to earn its keep some other way.
SMS friction in the U.S. — SHAFT rules and 10DLC registration — is a preview of how fragile a single channel can be. Wallet push and email stay compliant and scale cleanly.
Wallet-based loyalty was the story at Hall of Flowers, MJBizCon and O'Cannabiz this year. Personalized, spend-linked value is where the durable advantage sits.
Farmer Jane came in already ahead: 18 dispensaries across Regina, Saskatoon and Winnipeg, scanner check-ins live at the counter, and an ops culture that could actually land a campaign in every store the week it was written.”
Three advantages Farmer Jane had on day one.
18 dispensaries positioned across Regina, Saskatoon and Winnipeg — a dominant regional footprint, and enough volume to see a signal fast.
A scan at the counter, and the customer is in. Fast and habit-forming, the way PC Optimum and Starbucks trained everyone to expect.
Strong leadership and a real ops culture. Campaigns deployed rapidly, and the team across all locations actually ran them.
Program performance at a glance.
One in ten orders came through the loyalty program. Those orders carried nearly twelve percent of the revenue. That gap is the whole story.
Loyalty drove 11.8% of revenue on 10.1% of orders — an index of 117against its own order share. Members aren't just showing up more, they're building bigger baskets when they do.
Three behaviours moved. Every one of them compounds.
Loyalty baskets are consistently bigger.
A loyalty member's average order came in at $47.39 against $39.99 for everyone else. That is $7.40 more on every single order, without a discount doing the work.
Members made up two-thirds of every repeat customer.
Of 4,564 returning customers in the window, 2,902 were loyalty members. A program touching one in ten orders accounted for nearly two in three people who came back.
Loyalty shortens the purchase cycle by 3.3 days.
Non-members took 19.0 days to come back. Members took 15.7. A 17.5% improvement in visit frequency, which is roughly one extra trip a year per member.
The whole 100 days on one receipt.
Every line below is measured against the non-loyalty cohort in the same stores, over the same window. No modelled uplift, no projections, just the two groups side by side.
The winning programs all do the same three things.
Software gets you a program. These get you a program people actually use.
An "arcade wall" of rewards consistently outperforms a flat percentage discount. Choice creates excitement. A discount just lowers the price.
Budtenders prompt sign-ups on every interaction, so enrolment becomes part of the transaction rather than a poster on the wall.
Regular contests, giveaways and promotional campaigns keep momentum up. A program that goes quiet gets forgotten in a week.
What if 20% of customers were loyal?
Loyalty adoption sat at 10.1% after 100 days. Doubling it — using the same measured spend and frequency behaviour, applied to the same store base — is where the program goes next.
Projection, not a measured result. Modelled by applying the observed loyalty AOV and return-frequency deltas to a 20% adoption rate across the same 18 stores.
Journeys: the next leap at Farmer Jane.
A strong foundation is built. The next 100 days are about making every one of those members feel individually attended to. Three things have to be true first.
Real-time segmentation.
Personalized journeys need advanced customer segmentation that updates as the customer moves — not a static list exported last Tuesday. Spend tier, category affinity, days since last visit, store preference.
Be omni-channel.
One channel is a single point of failure. Four channels, coordinated from the same customer record, is a program that keeps working when one of them gets harder.
Always be communicating.
Every customer should be inside at least one journey at all times, and usually more than one. Four foundational journeys cover most of the ground.
Greet new members with personalized offers and a guide to getting the most out of the program.
Remind customers about what they left behind, with a tailored incentive to finish.
Celebrate milestones with an exclusive offer that feels personal, not automated.
Bring inactive members back using past preferences and new arrivals they would actually want.
Always be fun.
The arcade wall, the contests, the giveaways. The reason the program stays top of mind between visits isn't the points balance, it's that opening the card is enjoyable. That is a design decision, and it has to be made on purpose.
Behind the numbers
How the figures on this page were measured, and what they do and don't say.
What counts as a "loyalty order"?
Any transaction where the customer checked in with their loyalty identity at the counter, via the in-store scanner. Non-loyalty is every other transaction in the same 18 stores over the same 100 days, which is what makes the two cohorts comparable.
Is the AOV lift caused by loyalty, or do bigger spenders just join?
Honestly, both are in there. This is a cohort comparison over 100 days, not a randomised test, so some self-selection is expected — engaged customers are more likely to enrol. The return-cycle number is the harder one to explain away: the same people came back 3.3 days sooner than the non-member baseline.
How does this work under Canadian inducement rules?
Inducement restrictions are why the program is built on spend and relevance rather than a visit-count punch card. Reward structure and campaign copy are set up province by province with the operator's own compliance team, and Sticky's AI content review flags language on the way out.
Is the +$500K figure a result?
No. Everything in the 100-day scorecard is measured. The 20%-adoption scenario is a projection: it applies the observed AOV and frequency deltas to a doubled adoption rate across the same store base. It is the target, not the outcome.
What Farmer Jane runs on
See your own first 100 days.
We'll build the same 100-day scorecard against your POS data — loyalty versus non-loyalty, basket size, return cycle, the lot — and walk you through what it would take to move it.