SECTOR / TELECOM AND MEDIA

Raise ARPU without buying churn.

For audience insights, subscription strategy, and pricing teams: test price, bundle, ad tier, and content bets before they ship. Subconscious turns one plausible forecast into thousands of measured subscriber experiments.

4.6%

Premium SVOD churn stabilized around a level where every price move matters. The upside is not cheaper research. It is knowing which offer lifts ARPU without pushing the wrong subscribers out.

Source: Antenna, Premium SVOD 2025 Year in Review

THE DECISION

Old world

Change pricing, bundles, and benefits across a $480M subscriber base, then wait for churn data to reveal the damage. A pricing mistake can cost subscribers before the team understands which cohorts were affected.

New world

Simulate competing plan designs by subscriber cohort before rollout. Find the configuration expected to reduce churn from 12% to 10.2%, a 15% relative reduction representing $8.6M in protected annual revenue.

Protect $8.6M in subscriber revenue before the new price reaches a bill.

How the figure is built

Subscriber revenue base
$480M
Churn today
12%
Churn under the ranked plan design
10.2%

$480M × 1.8pp retained = $8.6M in protected annual revenue

Modeled economics on a representative decision, not customer results. Audited customer records are at subconscious.ai/case-studies.

THE TIMING SHIFT

Today
  1. Price
  2. Bundle
  3. Ad tier
  4. First bill
  5. Churn read
Subconscious
  1. Price
  2. Bundle
  3. Ad tier
  4. First bill
  5. Churn read
Current teams learn after cancellations. Subconscious tests the tradeoff before customers see the offer.

CAUSAL OPERATING LOOP

KPI shift

ARPU up, churn protected.

ARPU lift

Price changes are judged after customers react.

Price, bundle, and ad load are ranked before rollout.

Retention guardrail

Cancellation patterns explain the damage later.

Churn risk is modeled before the offer ships.

Content leverage

Programming bets compete with price noise.

Content, offer, and creative are tested on the same cohort.

Relative decision leverage. Every read ships with cohort, confidence interval, and experiment trail.
Telecom and media causal decision graphSubscriber tenure and engagement confound the relationship between price, bundle, and ad decisions and ARPU, churn, and LTV outcomes. Subconscious isolates the causal effect.Utenure / engagementunobserveddo(O)price / bundle / ad loadYARPU / churn / LTV
Grey arrows are the correlations hiding in the subscriber file. The red arrow is the causal effect of price, bundle, and ad load on ARPU, churn, and lifetime value.

ONE CAUSAL ANSWER

Which offer raises revenue without training customers to leave?

Walk into the pricing committee with the offer stack ranked: which price to raise, which bundle to protect, which ad load to cap, and which content audience can take the move.

MODEL-PREDICTED

Predicted first, then measured.

The same method, audited: a paid media campaign where the model ranked the creative before spend, and the live campaign confirmed the ranking.

Predicted
The slogan a staff member had suggested would be the weakest of the set, and a $300 cash-back incentive would balance applicant interest against margin.
Observed
Run head to head against humans in Facebook and Instagram, that slogan was the worst performer in market. The campaign landed a 0.74 Result Rate against the prior campaign's 0.52.
Agreement
The ranking held: the slogan the model placed last placed last with real buyers.

Read the audited record: Nº 02 River City Federal Credit Union

PROOF

93%

validated against human outcomes

350+

replicated human studies

5 min

to run the next decision

SOC 2

enterprise-ready deployment