ZenABM

ZenABM's LinkedIn Ads AI Analyst is a set of AI-powered tools for creating, launching, understanding, optimizing and reporting on LinkedIn Ads. It works in two ways: through Zena, ZenABM's native AI agent, and through the ZenABM MCP server, which lets you build, manage and optimize LinkedIn ads and campaigns directly from Claude, ChatGPT, Perplexity, Gemini or any other AI tool. Zena, the MCP server and the API are all powered by the same company-level ABM data, so campaign building, analysis and reporting draw on LinkedIn Ads, ABM, CRM and revenue data together. The product is aimed at people who run LinkedIn Ads and ABM campaigns and want to do that work inside the AI tools they already use. ZenABM frames the core problem simply: running LinkedIn Ads today often means copy-pasting between your tools and LinkedIn Campaign Manager. Campaigns, ad sets, ads, copy and settings all have to be moved by hand, and reporting tends to arrive as a raw data dump rather than a set of insights and next actions. The result is slow campaign launches, fragmented performance data, and reporting that takes time to turn into decisions. ZenABM's approach is to remove that manual middle layer - generation, management, optimization and reporting happen through AI, with the user reviewing and approving the outcome rather than doing the assembly work. Rather than replacing Campaign Manager, ZenABM hands you a link to review and approve there, so nothing launches until you approve it. Zena, ZenABM's AI agent, builds and manages LinkedIn campaigns directly. You describe the campaign you want and Zena builds it end to end: the campaign, ad sets, targeting and the ads themselves - copy written for you and creatives pulled from your media library. Before committing, you can check the audience size, and you can reuse your saved audiences and lead forms or duplicate what already works. Nothing goes live until you confirm it, which keeps a human in the loop at the approval step while the assembly is automated. Through the MCP server, the same capability is available wherever you already work. You ask Claude, ChatGPT, Perplexity or Gemini for the ads you need; the ZenABM MCP generates them, pushes them into a new ad set with the objective, budget and bidding you asked for, and returns a link to review and approve in Campaign Manager. The site describes the MCP server as offering 15 expert skills built in and 96 read and write tools across your LinkedIn ads and ABM data, extending the agent's reach beyond ad creation into the data around your campaigns. Those expert skills are 15 ready-made ABM skills you run as slash commands, covering tasks such as audits, monthly reports, strategy planning, ad decay checks and sales handoff lists, all graded against ZenABM benchmarks. Underneath them sit the 96 read and write tools spanning LinkedIn Ads, ABM, CRM and revenue data. The point of combining skills with tools is that the AI is not only answering questions about your ads - it has defined, benchmark-aware routines it can execute against your own account data. Reporting is automated rather than assembled by hand. Zena produces weekly, monthly and quarterly reports written for you and sent straight to your inbox, with insights and action items Zena can carry out on your approval, rather than a raw data dump. You can also request a report on the spot: performance is cross-referenced with your pipeline, top and low performers are surfaced, and the result is shareable in seconds. Optimization follows the same pattern. Zena finds and fixes underperforming LinkedIn Ads and campaigns without leaving the chat. It surfaces your lowest and best performing assets, then lets you act on them: pause inefficient ad sets and campaigns, change bids and budgets, and build retargeting audiences from ad engagement and CRM events. Every change waits for your approval, so the AI proposes and the user decides. Alongside execution, ZenABM positions Zena as an advisor. Zena is trained on knowledge from 30+ ABM and LinkedIn ads experts, including Tim Davidson, Ali Yildirim and Max Herzeg, drawn from their own posts. When you ask about list building or ABM strategy, the answer comes back tied to your own data and to benchmarks from other accounts, so the comparison is real rather than generic. The site also advertises expert LinkedIn Ads advice available 24/7. The third surface is the API, which lets you connect your LinkedIn Ads data anywhere and build your own dashboards. It pulls LinkedIn ads engagement, campaign performance and intent stages into whatever system you need. ZenABM notes that whether you use Zena, plug ZenABM into your AI client, or build on the API, it is all powered by the same company-level ABM data - so the agent, the MCP server and the API are three ways into one data foundation rather than three separate products. The benefits follow from that setup. Campaigns that previously required manual rebuilding in Campaign Manager can be generated from a description or a prompt in an AI client. Reporting that previously required pulling data and writing commentary arrives weekly, monthly or quarterly with insights and action items attached. Optimization that previously depended on someone spotting a poor performer moves into the same chat where the performance surfaced, with pause, bid and budget changes queued for approval. And because answers are tied to your own data and benchmarks from other accounts, advice is comparative rather than abstract. Concrete scenarios appear throughout the site. In one illustrated workflow, Claude generates four document ads for a ZenABM workshop in London, with draft ads named for the event, including single-image ads tied to a London Event ad set. Another scenario is ongoing program management: asking Zena to analyze LinkedIn ads performance, find top engaged companies, and surface and pause underperforming ads. Reporting scenarios include a scheduled monthly report cross-referenced with pipeline, and an ad-hoc report requested on the spot. Audits, ad decay checks and sales handoff lists are listed as skill-driven tasks, while retargeting audiences built from ad engagement and CRM events support follow-up campaigns. On targeting and access, ZenABM addresses the product both to people running LinkedIn Ads and to those running ABM programs, including users who want to work inside Claude, ChatGPT, Perplexity, Gemini or Cursor. The site includes FAQ entries asking whether you need to be technical, which AI clients the MCP server works with, whether ZenABM AI can take actions or only read data, whether data is secure, which ZenABM plans include the AI features, and whether you can try ZenABM AI before paying - indicating both a free way to start and tiered plans. Calls to action invite you to start for free or book a demo, and a three-minute walkthrough video is offered. In summary, ZenABM's LinkedIn Ads AI Analyst takes the manual work out of LinkedIn Ads - building campaigns, creating ads, understanding performance, optimizing spend and reporting results - and delivers it through an AI agent, an MCP server for your preferred AI client, and an API, all on the same company-level ABM data.