Stack Curator
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A curated weekly digest of the best martech-stack reads, tools, and threads — we scan the firehose so you get the 7 links worth your time.
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Reverse ETL reads worth your weekend
The layer that pushes warehouse data back into your tools is finally documented well. Five picks:

1. Hightouch's "Composable CDP" whitepaper — the clearest argument for ditching packaged CDPs in favor of your warehouse as the source of truth. Source: Hightouch docs.
2. Census on sync diffing — how incremental syncs actually detect row changes without re-sending everything; the section on watermark columns is the keeper. Source: Census engineering blog.
3. dbt's "metrics layer" RFC — read the original discussion thread, not the marketing page; the tradeoffs are in the comments. Source: dbt GitHub.
4. Snowplow's event modeling guide — schema design before you pipe anything anywhere. Source: Snowplow docs.
5. "Modern Data Stack is a fallacy" by Pedram Navid — the necessary counter-read so you don't drink it all. Source: pedramnavid.com.

Skip if you're under 1M monthly events. Essential if your activation is bottlenecked on engineering.

That's the stack for this week. Forward to a teammate.
Identity resolution without the vendor pitch
Stitching one human across devices is the hardest part of any stack. Vendor-neutral reads only.

1. "Deterministic vs probabilistic matching" — when a hashed email beats a fuzzy fingerprint, and the false-merge cost of getting it wrong. Source: Segment Academy.
2. Identity graph data modeling — how to store edges so you can un-merge later (you will need to). Source: RudderStack blog.
3. UTM hygiene as identity input — Avinash Kaushik on why dirty campaign tags poison every downstream join. Source: kaushik.net.
4. Apple's Private Click Measurement explainer — the model that survives without third-party cookies. Source: WebKit blog.

Skip if you have one channel and one device type. Essential if you run cross-device retargeting.

That's the stack for this week. Forward to a teammate.
Attribution reads that admit the limits
Every model lies a little. These tell you how.

1. "Incrementality over attribution" — the case for geo-holdout tests instead of last-click theater. Source: Recast blog.
2. Markov-chain attribution, explained simply — removal effect math without a PhD; the worked example clicks instantly. Source: Analytics Vidhya.
3. Media Mix Modeling for small budgets — Meta's open-source Robyn and when MMM is overkill. Source: facebookexperimental on GitHub.
4. "Why your CAC is wrong" — blended vs paid CAC and the trap of counting organic as free. Source: Lenny's Newsletter.

Skip if you spend under five figures a month. Essential before you reallocate a budget.

That's the stack for this week. Forward to a teammate.
From the network

Want more on Digital ops workflows? @TheOpsPlaybook covers it daily and goes deeper than most. Solid follow.
Email deliverability as an engineering problem
Not copywriting. Plumbing. These treat inbox placement like infra.

1. DMARC, DKIM, SPF in one diagram — the alignment rules that actually decide gmail placement, drawn clearly. Source: dmarcian.
2. Google and Yahoo's 2024 bulk-sender rules — the one-click unsubscribe header spec and spam-rate threshold. Source: Google Postmaster docs.
3. IP warming schedules that work — day-by-day volume ramps from a real ESP migration. Source: Postmark blog.
4. Seed-list testing vs Google Postmaster Tools — why both, and what each blind-spots. Source: Word to the Wise.

Skip if you send under 5k a day. Essential the week before any domain or ESP migration.

That's the stack for this week. Forward to a teammate.
Server-side tagging: the real tradeoffs
Moving tags off the browser fixes some things and breaks others. Curated honestly.

1. Server-side GTM cost reality — the Cloud Run bill nobody quotes you, with sizing math. Source: Stape blog.
2. First-party cookie restoration via sGTM — extending cookie lifetime past Safari's 7-day ITP cap. Source: Simo Ahava.
3. What you lose moving server-side — client-side enrichment you'll have to rebuild. Source: MeasureSchool.
4. Conversions API vs pixel — when CAPI genuinely recovers signal and when it's redundant. Source: Meta for Developers.

Skip if your client-side tags fire fine and you're not ITP-blocked. Essential if Safari conversions cratered.

That's the stack for this week. Forward to a teammate.
How to actually evaluate a martech vendor
Demos are theater. These reads are the homework you do before the call.

1. The "build vs buy vs API" decision tree — when a 200-dollar tool beats a custom internal one, and the maintenance cost you forget. Source: First Round Review.
2. Reading a SOC 2 report for real — which sections matter when the tool touches PII. Source: Vanta blog.
3. Data egress and lock-in clauses — the contract lines that decide whether you can ever leave. Source: a16z.
4. Scott Brinker's martech rationalization — auditing redundant tools before you buy a 41st. Source: chiefmartec.com.

Skip if you're a team of one with three tools. Essential before any annual contract.

That's the stack for this week. Forward to a teammate.
Event taxonomy: the schema you regret skipping
Name your events badly once and you pay for years. These fix it upstream.

1. Object-action naming convention — "Product Viewed," not "viewedProduct," and why consistency beats cleverness. Source: Segment spec.
2. A tracking plan template that scales — the spreadsheet structure that survives a 50-person product team. Source: Avo blog.
3. Property vs event: where to put the data — the decision that determines whether you can ever segment on it. Source: Amplitude docs.
4. Schema enforcement at the SDK level — catching bad events before they hit the warehouse. Source: Snowplow.

Skip if your analytics is read-once dashboards. Essential before you instrument a new product.

That's the stack for this week. Forward to a teammate.
Lifecycle orchestration beyond drip campaigns
The gap between "sequence of emails" and "real-time journey" is where these live.

1. Event-triggered vs time-based flows — why behavior beats calendars, with the abandoned-browse example. Source: Customer.io blog.
2. Frequency capping across channels — stopping the four-message-in-an-hour pile-on when channels don't talk. Source: Braze blog.
3. The "do-nothing" control group — measuring whether your lifecycle program does anything at all. Source: Reforge.
4. Quiet hours and timezone logic — the unglamorous detail that prevents 3am pushes. Source: OneSignal docs.

Skip if you send one newsletter on a schedule. Essential if you run triggered journeys across two-plus channels.

That's the stack for this week. Forward to a teammate.
Catching broken tracking before your CMO does
Nobody notices a dead pixel until the dashboard goes flat. These watch for you.

1. Anomaly detection on event volume — alerting when "Signup Completed" drops 40 percent overnight. Source: Metaplane blog.
2. Schema-change alerts — catching when a dev renames a field and silently kills a report. Source: Monte Carlo.
3. The data contract pattern — making producers responsible for not breaking consumers. Source: dbt blog.
4. Synthetic monitoring for conversion funnels — a bot that walks checkout hourly to confirm tags fire. Source: Checkly blog.

Skip if a human eyeballs your dashboards daily. Essential once tracking feeds money decisions.

That's the stack for this week. Forward to a teammate.
Feature flags, but for marketers
The experimentation infra engineers take for granted is finally reachable for growth teams.

1. Flags vs A/B tests — when you want a kill switch vs a measured experiment, clearly separated. Source: LaunchDarkly blog.
2. Server-side experimentation for SEO safety — running tests without cloaking risk or layout-shift penalties. Source: GrowthBook docs.
3. Sample ratio mismatch, explained — the silent bug that invalidates half of all A/B tests. Source: Microsoft ExP team.
4. Bayesian vs frequentist for small traffic — which framework lets you call a winner sooner. Source: Convert.com blog.

Skip if you can't get 1,000 conversions per variant. Essential if you're shipping page tests on real traffic.

That's the stack for this week. Forward to a teammate.
Owning your product analytics
The case for self-hosted, warehouse-backed analytics over yet another black box.

1. PostHog vs Amplitude vs Mixpanel — a real teardown on data ownership and query freedom, not pricing tiers. Source: PostHog blog.
2. Why marketers should learn the "funnels are joins" idea — once it clicks, every dashboard makes sense. Source: Mode blog.
3. Retention curve interpretation — flattening vs decaying, and what each tells you to fix. Source: Reforge.
4. Self-hosting cost vs SaaS at scale — the event-volume breakpoint where owning pays off. Source: PostHog docs.

Skip if 100k monthly events fit a free tier. Essential if per-event pricing is eating your budget.

That's the stack for this week. Forward to a teammate.