INDUSTRY/Streaming
Convert trials. Prevent cancels. Keep watching.
Markin identifies at-risk viewers in real time and triggers content, plan and win-back moments that keep them watching, and paying.
Markin for Streaming
+41%
trial-to-paid conversion
-29%
voluntary cancels
+12%
annual plan mix
The reality today
What growth looks like in streaming.
Every streaming 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.
- Trials cancel silently at day 7, with no personal reason to stay.
- Cancel spikes track content gaps, but nobody acts in time.
- Plan mix skews toward the cheapest tier by default.
- Win-back sprays discounts and burns future ARPU.
Use cases
How streaming teams grow ARPU with Markin.
Trials
Convert trials, per viewer
Personal onboarding, content nudges and offer timing, moving each trial to paid without leaning on price alone.
Explore the solutionUser journey · scored live
Retention
Save the viewer, not just the sub
Predict cancels weeks out and trigger content, plan or price, only for viewers whose LTV justifies it.
Explore the solutionChurn risk · 30d
0.80
Plan mix
Right plan per household
Move viewers to annual, family, or ad-supported based on real behavior, not marketing segments.
Explore the solutionPlan match · per user
Basic
Recommended for this user
€9
Premium
€14
Annual
€119
Win-back
Personal reasons to return
New season, new content, new price, Markin picks the message that matches why they left.
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.
The magic isn’t the model, it’s the loop. Every save decision, every plan move, gets scored against ARPU the next day.
Director of Retention
Global streaming platform
Solutions
Solutions for streaming.
The growth motions Markin runs on your streaming stack, on day one.
FAQ
How fast can we see impact in streaming?
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 streaming stack.
A 30-minute demo on your real data, the same agents, the same decisions, the same 1:1 execution.