Google Ads Developer Blog: podcast

Unlocking Data Strength with Data Manager API: Ads DevCast E7

Friday, June 26, 2026

We are thrilled to share the newest episode of Ads DevCast, the podcast series brought to you by Google’s Ads Developer Relations team. This episode features a conversation with Data Manager PMs Xuezhu Li and Stephen Chang on unlocking data strength using the Data Manager API. Watch it: goo.gle/watchadsdevcast Hear it: goo.gle/listenadsdevcast Streamlining Ingestion: Send Once, Fan Out Everywhere Ingesting first-party signals into disparate advertising and measurement platforms has historically required building and maintaining separate, asynchronous ingestion pipelines. In this episode, Xuezhu explains how the Data Manager API introduces a "send once, fan out everywhere" architecture. You push your first-party data in one time, and the system seamlessly routes and distributes it across whichever destinations you choose, such as: CM360, DV360, SA360, and GA4. Effortless Pipeline Monitoring with the Status API For developers managing high-volume ingestion pipelines, tracking execution health is critical. The episode explores the new Status API — a dedicated request-tracking service that lets you monitor pipeline health using a simple request ID. Instead of digging through legacy multi-step offline queries, you get unified status checks with aggregated row-level error reporting. Built-In Privacy & Confidential Compute The Data Manager API is built from the ground up to keep sensitive user signals secure. That’s why it provides Confidential Match. Confidential Match relies on Confidential Compute, utilizing hardware-isolated Trusted Execution Environments (TEEs) to ensure your data remains completely locked down even during active processing. Four Reasons to Adopt & Engineering Best Practices Stephen and Xuezhu break down the four core reasons to adopt the Data Manager API today:

Performance

Privacy

New Features

Developer Experience

We Want to Hear From You Your feedback is vital to help us tailor future episodes. Please take a minute to share your thoughts at our Episode Survey. Be sure to subscribe on YouTube and join our Discord community to keep the conversation going! If you have any questions or want to discuss this post, please reach out to us on our “Google Advertising and Measurement Developers Community” Discord server. Also follow our new Google Advertising and Measurement Developers” LinkedIn page.

Cory Liseno

Google’s Advertising and Measurement Developer Relations team

The “What” and “Why” on Meridian: Ads DevCast E6

Thursday, May 28, 2026

Measuring the true impact of your marketing spend is complex, especially when you look across channels and mediums. In Episode 6 of Google’s Ads DevCast, "The 'What' and 'Why' on Meridian," we sit down with Product Manager Katie Munro and Developer Relations Engineer Jeff Li to explore Meridian, Google's open-source Marketing Mix Modeling (MMM) framework, and how it helps advertisers make data-backed strategic budget decisions. Watch the full episode Hear the full episode Here is a summary of the talking points from our discussion on what Meridian is, how the math works, and the newly announced surfaces to help you implement it. What is Meridian? Meridian is Google's open-source Marketing Mix Modeling (MMM) framework. It provides a holistic, privacy-safe view of marketing ROI by analyzing aggregated historical data across all channels (digital, TV, print) alongside non-advertising factors (seasonality, economic conditions). It helps you determine the incremental lift of your marketing (sales caused by ads) versus baseline sales (sales that would have happened anyway). The Core Math: Hill Curves & Adstock Meridian uses statistical models to capture the real-world behavior of advertising:

Hill Curves: Models diminishing returns, showing where you have room to increase spend (headroom) and where you have saturated a channel.

Adstock: Models the lagged effect and decay of advertising over time, capturing the delay between seeing an ad and making a purchase.

The Measurement Trifecta Meridian completes the modern measurement framework:

Attribution (GA4): For day-to-day tactical campaign tweaks.

Incrementality Experiments (Meridian GeoX): To test specific hypotheses in the real world.

MMM (Meridian): For macro-level, strategic budget planning.

New Meridian Releases from GML 2026 We discuss three major additions designed to make MMM more accessible and accurate:

Meridian in GA360: A turnkey, integrated MMM solution within Google Analytics 360 that uses existing behavioral data to provide cross-channel ROI insights without requiring a data science background.

Meridian Studio: A Google Cloud-based enterprise platform to build and scale models, featuring native agentic AI to automate data quality checks, suggest model health improvements, and assist in scenario planning.

Meridian GeoX: An open-source geo-based incrementality solution that acts as a calibration engine, allowing you to run geographic experiments and feed "ground truth" causation data back into your Meridian model.

Next Steps:

Watch the full episode on YouTube (or listen to it)

Try Meridian: https://goo.gle/try-meridian

Try Meridian Studio: https://goo.gle/try-meridian-studio

Try Meridian GeoX: https://goo.gle/try-meridian-geox

Check out the Meridian Developers website to read the documentation.

Join our developer community on Discord to ask questions and discuss.

Cory Liseno

Google’s Advertising and Measurement Developer Relations team

Ads DevCast: Google Marketing Live 2026 bonus episode

Thursday, May 21, 2026

We're excited to bring you a special bonus episode of Google’s Ads DevCast! We’re going over a few of the bigger announcements and updates from Google Marketing Live (GML) 2026 that directly affect our developers and technical users, across Tagging, Data Manager, and Meridian. Watch it at goo.gle/watchadsdevcast Hear it at goo.gle/listenadsdevcast Key Highlights from the Episode

Tagging improvements: Discover the new Google tag gateway In-UI setup offerings (featuring GCP, Akamai, Cloudflare, and Fastly) and new CMS integrations. We also discuss Visual Tagging for troubleshooting purchase conversions, and how we are bringing GTM capabilities directly to the Google tag.

Data Manager API: Learn about the value of single ingestion and multi-feed, allowing you to flow first-party data to multiple Google products with a unified schema. We also touch on Confidential Matching for privacy-safe audience building.

Meridian (open-source MMM): Get an overview of the new Meridian offerings announced at GML, including Meridian in GA360, Meridian Studio (featuring native agentic capabilities), and Meridian GeoX for incrementality calibration.

Listen to the episode to get all the details and prepare for next week's deep dive into Meridian! Don't forget to take our Episode Survey to let us know what you think! If you have any questions or want to discuss this post, please reach out to us on our “Google Advertising and Measurement Community” Discord server.

Cory Liseno

Google’s Advertising and Measurement Developer Relations team

Managing your integrations at scale: Ads DevCast E4

Thursday, May 7, 2026

Scaling an advertising integration is more than just writing code—it requires a deep understanding of efficiency, resilience, and auditability. In Episode 4 of Ads DevCast, "Managing your integrations at scale," we break down universal architectural best practices and product-specific solutions to help you optimize your advertising integrations. Watch the full episode Hear the full episode Whether you are working with the Google Ads API, Google Ads scripts, Data Manager API, DV360, or Google Analytics, here is a summary of the key takeaways to build high-performance, scalable systems. Universal Principles of Robust Integrations

Respect Rate Limits: Rate limits are a reality of using APIs at scale. Understand your limits beforehand to prevent lockouts and maintain a healthy integration. Read the error messages — they may contain instructions on what to do next. For transient or retry-able errors, don't hammer the server with rapid retries. Instead, implement exponential back-off with jitter to give the system time to recover.

Prioritize Logging and Monitoring: Always consider logging in production where appropriate. Capture crucial metadata, like the Google Ads API request_id, in your structured logs to trace failures instantly. If a call is erroring, write that error payload to logs. Set up proactive alerts to catch errors before they impact operations.

Use Official Client Libraries: While direct REST/gRPC calls are supported in many of our products, using official libraries saves development time and handles heavy lifting (e.g., serialization and authentication) out of the box.

Cache Smartly: Reduce redundant queries. If you are querying historical data that will no longer change, cache it locally to save bandwidth and rate limits.

Product-Specific Best Practices

Google Ads API: Optimize efficiency by Batching Operations. Group operations logically to reduce round-trips. Order your operations correctly to improve execution efficiency.

Data Manager API: Batch ingestion requests to process events efficiently. Understand the difference between synchronous errors (structural issues returned instantly that reject the whole batch) and asynchronous validation (monitored via the Diagnostics endpoint).

Google Ads scripts: Avoid sequential iterations when dealing with many accounts at once. Use Bulk Uploads with CSV tables to apply scaled operations, and leverage the executeInParallel method for MCC scripts to run up to 50 concurrent execution threads.

Display & Video 360 API: Utilize Structured Data Files (SDFs) to manage YouTube line items and ad group bulk operations that aren't natively supported by the API.

Google Analytics: Enable daily BigQuery Exports for event-level data, and utilize Long-running Asynchronous Report Tasks in the Analytics Data API v1alpha to build scalable, customized reports without HTTP timeouts.

Next Steps: Watch the full episode on our YouTube channel (or listen on YT Music) Check out our Advertising and Measurement Developer Hub. Join our community on Discord and share your scaling stories or questions with Googlers and other developers. Learn more in our guides below:

Google Ads API Best Practices and Batch Processing

Google Ads scripts Bulk Upload and Best Practices

Analytics BigQuery Solution and Report Tasks Fundamentals

Data Manager API Best Practices, Limits, and Diagnostics

Display & Video 360 Structured Data Files (SDFs)

Cory Liseno

Google’s Advertising and Measurement Developer Relations team

Ads DevCast E3: Improving your Advertising Workflows

Thursday, April 16, 2026

Improving your Advertising Workflows It’s an incredible time to be a developer in the advertising space. Innovation is moving at a breakneck pace, and we’re shifting from incremental API integrations to fundamental improvements in how technical users interact with our platforms. In the latest episode of Ads DevCast, I sat down with my colleague Matt Landers to discuss how AI is moving from "hype" to "utility," decreasing friction in development and delivering tangible business results. The Power of Multi-Product Insights One of the most exciting developments we’re seeing is the value of Advertising MCPs (Model Context Protocol) servers showing up. These open-standard tools allow your AI agents to interact directly with the Google Ads and Google Analytics APIs. Historically, solving a problem like "why is my high-CTR ad not converting?" meant a lot of manual data joining between Ads and Analytics. By combining the Google Ads and Analytics MCPs, you can now perform this analysis in seconds using natural language. You can verify engagement rates, identify content mismatches on landing pages, and even suggest ROI improvements in the time it takes to brew a cup of coffee. Efficiency and Speed with Natural Language We’re also seeing AI make technical tasks more accessible. A great example is the recent update to our Sheets Report Builder add-on for Google Analytics 4. Previously, creating complex reports required manually adding dimensions, metrics, and filters in the UI. Now, with Gemini integrated directly into Sheets, you can simply ask, "What's my highest converting landing page?" and the tool automatically sets all the parameters in the UI, sends the API request, and imports the data for you. The Senior Pair Programmer in Your CLI For developers deep in the code, the Google Ads API Developer Assistant is a game-changer. Think of it as a senior pair programmer that has memorized the entire API schema and every possible error code. Whether you’re troubleshooting conversion uploads or finding hidden problems in your account, the assistant doesn’t just explain what’s wrong—it can generate, debug, and even run the fix directly in your environment. Health, Diagnostics, and Seamless Migrations Beyond AI-driven insights, we’re focused on improving the underlying health of your technical systems. The Data Manager API will soon feature integrated diagnostics in the UI, allowing you to track what went wrong with your integrations. Last but not least, for publishers, we’ve released a new migration skill for the AdMob SDK to help you transition between versions with the help of your coding agent. Experiment, Fail Fast, and Build Great Things The barrier to entry for building sophisticated, data-driven advertising solutions is dropping. By automating the busy work, you’re freed up to focus on high-impact projects that drive real business growth. Ready to dive deeper? Watch the full episode: goo.gle/watchadsdevcast Listen on the go: goo.gle/listenadsdevcast Take our Episode 3 Survey: goo.gle/adc-survey-e3 Join our Discord Community: goo.gle/ads-and-measurement-discord

Cory Liseno

Google’s Advertising and Measurement Developer Relations team

Introducing: Ads DevCast

Friday, March 20, 2026

A new podcast for the ads technical community

We are thrilled to announce the launch of Ads DevCast, a new bi-weekly vodcast and podcast series brought to you by Google’s Advertising and Measurement Developer Relations team. Hosted by Developer Relations Engineer Cory Liseno, this show is dedicated to deep dives into our latest technical updates, insights from the engineers building our tools, and expert discussions on products like Google Ads, Google Analytics, Display & Video 360, Meridian, and more. While you might already be familiar with the Ads Decoded podcast — where Ginny Marvin does a fantastic job bridging the gap for marketing teams on campaign strategy — Ads DevCast is built specifically for builders and developers. You can tune in on our Google Ads Developers YouTube channel or find the podcast on Google Ads Developers in YouTube Music. Episode 1: MCPs, Agents, and Ads. Oh My! In our premiere episode, we explore the "agentic shift" currently reshaping the advertising landscape. We’re seeing a world where agents, not just humans, are becoming primary consumers of our APIs. To help you stay ahead, we’ve released several tools designed to make your integrations smarter, faster, and more accessible. Getting Smarter with MCP Servers One of the covered topics is Model Context Protocol (MCP), and how it allows your agents like Gemini CLI to securely access your data. We’ve recently released open source, self-hosted MCP servers for the Google Ads API and Google Analytics API. These tools allow you to ask natural language questions directly to your agent, such as:

"What are my active campaigns?"

"Which properties had the highest traffic yesterday?"

"What are my top-selling products over the last month?"

The real magic happens when you combine this data with generative power. In the episode, we discuss how you can use the Analytics MCP to not only pull reports but then ask Gemini to generate a data-justified marketing plan based on those specific results. Moving Faster with the Developer Assistant Technical speed is another major focus. To reduce the time spent digging through documentation, we’ve launched the Google Ads API Developer Assistant. This Gemini CLI extension allows you to use natural language to generate, debug, and even test-run integration code. In one real-world test, we used the assistant to solve a complex reporting issue regarding policy disapprovals. What would normally take days of back-and-forth with email support was resolved by the assistant in minutes, providing the exact GAQL query needed to get the job done. Improving Accessibility AI tooling is also changing who can interact with our technical systems. We’re seeing a shift from the "Ads Developer Community" to a broader "Ads Technical Community." Marketing power users are now leveraging MCP servers to perform real-time data operations without waiting for a full development lifecycle. This frees up engineering teams to focus on high-impact "blue sky" projects while giving marketers the agility they need. We want to hear from you This show is a pilot, and your feedback is important so we can tailor our content to what is most useful for you. Please take a moment to fill out our Episode 1 Survey and let us know what topics you want us to cover next. Be sure to also join our Discord Community where you can join the conversation with Googlers and fellow developers. Thanks for tuning in! We'll see you in two weeks for Episode 2.

Cory Liseno

Google’s Advertising and Measurement Developer Relations team

Ads Developer Blog

Unlocking Data Strength with Data Manager API: Ads DevCast E7

The “What” and “Why” on Meridian: Ads DevCast E6

Ads DevCast: Google Marketing Live 2026 bonus episode

Managing your integrations at scale: Ads DevCast E4

Ads DevCast E3: Improving your Advertising Workflows

Introducing: Ads DevCast

Labels

Archive