Technical implementation guides for developers working in marketing technology — SDKs, tracking code, tag management, and MarTech architecture.
Twelve states now require honoring universal opt-out signals, and regulators are fining implementation failures. Here's what that means at the code level.
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Re-running our five agent-readiness criteria against what actually shipped: Salesforce's two MCP servers, WordPress's Abilities API, and Adobe moving the other …
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A developer's grading rubric for agent-ready MarTech APIs: docs quality, granular auth, structured responses, MCP support, and rate-limit signaling that agents …
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What breaks in Klaviyo API integrations at scale — revision header mismatches, rate tier behavior, missing RateLimit headers on 429s, bulk operation limits, and …
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How to implement Model Context Protocol servers for MarTech platforms — tools, resources, transport options, and the practical gotchas before you wire AI agents …
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The three main MarTech data pipeline patterns, when a CDP is the right answer, identity resolution in depth, consent implications, and a framework for choosing …
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A developer's guide to choosing between webhook and polling patterns for MarTech data integrations — latency requirements, reliability tradeoffs, and …
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How to build robust rate limit handling for MarTech API integrations — token bucket implementations, adaptive backoff, queue architecture, and platform-specific …
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How to integrate third-party MarTech JavaScript SDKs without destroying page performance, data quality, or user privacy — loading strategies, consent gating, …
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How to implement server-side event tracking for marketing analytics — architecture patterns, identity resolution, consent handling, and migration from …
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The real architecture behind a MarTech stack — four layers, identity resolution, integration complexity, and how to evaluate whether a tool belongs.
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