INDUSTRY/Retail
Turn every session into ARPU.
Markin unifies commerce, loyalty and CRM data, then executes the next best offer for every shopper, across app, web, email and store.
Markin for Retail
+22%
ARPU lift in 90 days
3.4x
conversion on re-engagement
-28%
voluntary churn on loyalty base
The reality today
What growth looks like in retail.
Every retail team we talk to fights the same set of frictions. Markin doesn’t add a tool on top, it replaces the rule trees and segments with a decision per user.
- Commerce, loyalty and CRM live in separate silos, so no channel sees the whole shopper.
- Broadcast campaigns burn margin on shoppers who would’ve bought anyway.
- Rules and segments age fast, and nobody owns the tree.
- Loyalty engagement stalls once the welcome offer is spent.
Use cases
How retail teams grow ARPU with Markin.
Acquisition
First-purchase, faster
Agents personalize the first 7 days across email, push and app, moving new signups to their first order without discounting the base.
Explore the solutionUser journey · scored live
Cross-sell
Grow basket, not friction
Real-time recommendations tuned per customer: complementary SKUs, bundles, and premium tier, placed at the exact moment intent peaks.
Explore the solutionNext best offer · scored per user
Loyalty
Reward the right behavior
Move members up tiers with 1:1 challenges and offers. Agents decide who gets what, when, and where, no rule trees to maintain.
Explore the solutionTier progress · Gold
3 more sessions this week to unlock a personal reward.
Personal challenge activeWin-back
Bring dormant shoppers back
Detect drop-off before it becomes churn and craft a personal reason to return, with the offer, channel and copy tuned per user.
Explore the solutionMessage composed · 1:1
Preview
Hey Sara, your usual weekend picks are 20% off through Sunday.
Sent 09:14 local · optimal open window
The actual difference
A decisioning engine picks the best action from a list you wrote. Markin writes the list, and runs it in your stack.
Think of Markin as a data science and growth team that never sleeps: it investigates, forms hypotheses, ships them into your own stack and proves each one against a control group, at a volume no human team can reach.
- Marketing
- Product
- Commercial
- Technical health
Hypothesis space
Everything a human growth scientist would look at.
Most growth problems are not message problems. Markin is not restricted to the campaign surface: if something is holding ARPU back, it is in scope, and it gets tested the same way.
Marketing
The classic surface, but chosen per customer rather than per segment, and always against a holdout.
- Which offer this specific customer is worth making
- Channel and timing chosen per person, not per campaign
- Contact pressure and fatigue arbitrated across every programme
- Win-back economics: who is worth a discount and who is not
Product
Where the customer actually experiences the value, and where most silent revenue loss happens.
- Onboarding steps that lose customers before first value
- A feature with high retention correlation that half the base never discovers
- Paywall and upgrade prompt placement
- In-product surfaces used as a treatment arm, not just email and push
Commercial
Pricing, packaging and the shape of the offer itself, tested rather than argued about.
- Plan and bundle structure by cohort
- Discount depth against margin, not against conversion alone
- Annual versus monthly framing per customer
- Dunning and involuntary churn recovery sequences
Technical health
Anomalies nobody asked it to look for. This is the category no decisioning engine covers.
- A checkout error rate that rose on one device and one region
- Payment failures concentrated in a single issuer or method
- A broken deeplink quietly killing a high-value journey
- Latency or delivery degradation eating conversion before any message does
Think of Markin as a data science and growth team that never sleeps: it investigates, forms hypotheses, ships them into your own stack and proves each one against a control group, at a volume no human team can reach.
Markin replaced twelve segments and a rules tree we’d been patching for years. In one quarter, ARPU on our loyalty base was up double digits, with fewer discounts, not more.
VP Growth
Top-5 European fashion retailer
Solutions
Solutions for retail.
The growth motions Markin runs on your retail stack, on day one.
Also in this space
Related industries.
FAQ
How fast can we see impact in retail?
Most teams run a first pilot in 30 days on a single motion (e.g. churn or cross-sell) and see measurable ARPU lift inside 90 days.
Do we need to move our data?
No. Markin reads from your warehouse, CDP or product events directly, nothing gets copied, nothing gets locked in.
How does Markin fit our existing CRM, app and contact center?
Markin executes into the systems you already have, Braze, Iterable, Salesforce, Twilio, your own app SDKs and contact-center tools, via native integrations.
How is this different from a rules engine or campaign tool?
You don’t author segments or rule trees. Agents decide per person, per moment, and are evaluated against ARPU, not opens or clicks.
What about data security and compliance?
Markin is SOC 2, ISO 27001 and GDPR ready, with least-privilege access, per-tenant encryption and audit logs on every agent decision.
See Markin run on your retail stack.
A 30-minute demo on your real data, the same agents, the same decisions, the same 1:1 execution.