Industries

Media & Entertainment

Publishing platforms that survive their own headline traffic.

Media businesses are asked to do two things at once: hold a front page steady through a spike, and know exactly what the audience did next. Most stacks are good at one and expensive at the other. We build the publishing, delivery and measurement layer as one system, so a story that goes viral is an operations event rather than an incident.

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Google Cloud for media and entertainment

Where a managed service is the honest answer — BigQuery for audience data, Pub/Sub and Dataflow for the live event firehose, Cloud CDN and Media CDN for delivery — we use it, and we say so.

01 · Ingest

Pub/Sub · Dataflow

Every page view, play and podcast download lands in one stream.
02 · Store

BigQuery · Cloud Storage

One warehouse for editorial, audience and rights data.
03 · Serve

Media CDN · Cloud Run

Pre-rendered shells at the edge, so origin sees a fraction of the peak.
04 · Measure

Looker · BigQuery ML

What worked — per story, per cohort — without a CSV round trip.

+12.4%: game completion and retention uplift at a top gaming company in SG after unifying its player data; Source: Client engagement, anonymised

SASB TC-ME — Media & Entertainment

SASB standards ↗

Media’s material topics are mostly social and governance ones — content integrity and audience privacy — plus the energy behind delivery. Adapted: TC-IM-130a.1 for streaming infrastructure.

TC-ME-220a.1
Content integrity

% of published content reviewed against editorial policy

We put the review state in the CMS workflow, so the percentage is a query rather than a quarterly sample.
TC-ME-230a.1
Data security

breach count, % involving personally identifiable information

Structured logging on the identity and consent path, with PII tagged at the field level.
TC-ME-230a.2
Audience privacy

users whose data is used for secondary purposes, by purpose

Consent is stored as a purpose-scoped record, which is the only way this number stays true after a schema migration.
TC-IM-130a.1
Delivery footprint

energy consumed (GJ), % grid, % renewable

Cache-hit ratio and origin egress are already available in your CDN logs — we turn them into a per-request energy estimate.

Sustainability disclosures, their SASB code, the metric and how we would instrument it
Standard	KPI	Metric	How we instrument it
`TC-ME-220a.1`	Content integrity	% of published content reviewed against editorial policy	We put the review state in the CMS workflow, so the percentage is a query rather than a quarterly sample.
`TC-ME-230a.1`	Data security	breach count, % involving personally identifiable information	Structured logging on the identity and consent path, with PII tagged at the field level.
`TC-ME-230a.2`	Audience privacy	users whose data is used for secondary purposes, by purpose	Consent is stored as a purpose-scoped record, which is the only way this number stays true after a schema migration.
`TC-IM-130a.1`	Delivery footprint	energy consumed (GJ), % grid, % renewable	Cache-hit ratio and origin egress are already available in your CDN logs — we turn them into a per-request energy estimate.

Where we help

Delivery that absorbs the spike: Edge caching, origin shielding and pre-rendered shells sized against your real peak — not a staging benchmark. A publisher engagement in Singapore is this exact problem: roughly half a billion requests a month at the lowest cost per request we could find.
One event model, not five dashboards: Page, video, podcast and newsletter behaviour land in a single event schema, so editorial can answer "what worked" without asking three vendors for a CSV.
Rights and revenue, auditable: Ad ops, paywall rules and syndication rights modelled explicitly, with the audit trail a rights holder or advertiser will eventually ask for.

Working on something in Media & Entertainment?

A 30-minute call is usually enough to work out whether this is a quick win or a rebuild — and we will tell you if it is the second one before you spend anything.

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Calculator

What is peak delivery actually costing you?

Put in your audience numbers. We will model the peak egress and the spend that better caching, encoding and tiering would recover.

Indicative

Media & Entertainment

Recoverable spend / year

$2.2M

Peak egress at 6% concurrency: 6,000 Gbps
Egress per month: 540.00 PB
Indicative payback: 1 months

Monthly active viewers 20 M

1 M 200 M

Viewing hours per viewer / month 12 h

1 h 60 h

Average bitrate HD — 5 Mbps

Current annual infrastructure spend 8 $M

Model assumptions

Peak concurrency assumed at 6% of monthly active viewers.
1 hour of video at N Mbps ≈ 0.45 × N GB.
Recoverable spend of 28% assumes combined gains from cache hit ratio, encoding ladder and storage tiering.
Payback assumes a $250k engagement; your scope will differ.

An order-of-magnitude model, not a quote. We will send the version with your real baselines, the assumptions replaced, and the implementation cost netted out.

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