LinkedIn Ads

By Yashasvi Saxena

If you are a traditional demand-gen team shifting to account-based marketing, it’s going to be easier for you than it was for most teams when AI didn’t exist or wasn’t good enough. I’m talking about the operational tax: researching accounts one by one, checking engagement account by account, rebuilding the same report every Monday, writing... Continue reading AI-powered ABM: How AI is Changing Account-Based Marketing in 2026

By Yashasvi Saxena

AI LinkedIn ads optimization splits into two layers, and if you only run one, you leave most of the return on the table. The first layer is LinkedIn’s own AI (Predictive Audiences, automated bidding, AI-drafted creative) that optimizes the auction: it spends your budget toward more clicks and conversions from individual members. That layer is... Continue reading AI LinkedIn Ads Optimization: A Practical Playbook for ABM

By Yashasvi Saxena

The LinkedIn Ads minimum audience size is 300 members per ad set, and that one number breaks more ABM programs than any creative or bidding mistake I see. You build a tight list of 40 dream accounts, layer on the two job titles you actually care about, add the location, and Campaign Manager throws back... Continue reading LinkedIn Ads Minimum Audience Size: Rules & ABM Workarounds

By Yashasvi Saxena

LinkedIn ads automation with AI usually consists of a set of toggles in Campaign Manager: automated bidding, predictive audiences, AI-drafted creative, etc. When we ran our LinkedIn ABM program, none of those toggles could answer the most important question that mattered, which was what each target account saw and did across our campaigns. LinkedIn optimizes... Continue reading LinkedIn Ads Automation with AI: Workflows for ABM Teams

By Yashasvi Saxena

AI ABM tools are changing how ABM gets done in 2026. They make shipping ad creatives and personalized landing pages faster and cheaper, they show you how campaigns perform and which target accounts engage (now through MCP servers too), and they help you optimize campaigns e.g. with bidding agents. But as usual, it’s hard to... Continue reading Best AI ABM Tools to Run Account-Based Campaigns in 2026

By Yashasvi Saxena

How to connect LinkedIn Ads to Claude Code through an MCP server, what you can ask, and how to build reports, dashboards, and alerts without exporting a single CSV.

By Yashasvi Saxena

What the LinkedIn Ads API really is, how to get developer access, the endpoints and auth involved, and why most teams put an MCP server on top of it.

By Yashasvi Saxena

There is no official LinkedIn Ad Library API. Here is what the Ad Library offers, the realistic access options, and a step-by-step competitor research workflow.

By Yashasvi Saxena

A deep dive into the LinkedIn Ads Reporting API: finders, pivots, metrics, and the honest limits around eCTR, attribution, and the CRM join.

By Yashasvi Saxena

How to audit your LinkedIn Ads with AI: a six-area checklist plus the settings most audits miss, with copy-paste prompts and a clear list of what to fix first.

By Yashasvi Saxena

The analysis playbook for Claude Code: format efficiency, ABM stage movement, account cohorts, period deltas, and creative analysis, with prompts you can reuse.

By Emilia Korczynska

Looking for a LinkedIn Ads MCP server? Well, there is no official one. But you can use third-party MCP servers built on the official LinkedIn Ads APIs, such as ZenABM’s LinkedIn Ads MCP server. LinkedIn does not have its own Model Context Protocol server (at least as of June 2026), which means you cannot just... Continue reading LinkedIn Ads MCP Server: How to Analyze Your LinkedIn Campaign Data in Claude Code or ChatGPT