For ABM

By Emilia Korczynska

LinkedIn ABM reporting goes wrong in a way that is hard to see because the reports look fine. For a long stretch of our program, I was reporting on ads and calling it ABM reporting. Impressions, CTR, cost per click, best-performing creative – all accurate and well presented.

By Emilia Korczynska

AI ABM segmentation is marketed as an algorithm that finds hidden clusters in your account list, and that promise is where most programs waste their first quarter. In reality, the segments that predict a meeting are not always the ones you can draw from a firmographic spreadsheet. Moreover, oversegmentation is a problem too.

By Emilia Korczynska

AI intent data sounds like it should solve account prioritization for you. Feed a model every signal you have, get back a ranked list, and work the top of it. That is the pitch, and it fails in a specific way that I want to name early. AI does not fix bad intent data.

By Emilia Korczynska

AI account scoring for ABM only works when it tells your team which accounts to act on today, and it fails the moment it produces a confident number nobody trusts enough to chase.

By Emilia Korczynska

ChatGPT for ABM usually means asking it to write ad copy, and that is the smallest thing it can do. When we ran our first LinkedIn ABM program, every step was manual: sizing the market, building the account list, researching accounts, auditing the account, reporting to execs, routing hot accounts to sales, and more.

By Emilia Korczynska

AI ABM reporting is not about buying another AI wrapper that gives generic advice, or an automation that drops report PDFs into Slack. All of that is too basic for 2026.

By Emilia Korczynska

When we ran our LinkedIn ABM program, every step was manual: sizing the market, building the account list, researching accounts, writing ads, auditing the account, reporting to execs, and routing hot accounts to sales.

By Emilia Korczynska

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.

By Emilia Korczynska

A pipeline-level ABM audit in Claude Code: pipeline per dollar, stage movement, the campaigns touching open and closed-won deals, and the intent that predicts deals.

By Emilia Korczynska

Using Claude Code for ABM is not a theoretical concept anymore. It is already reshaping how B2B marketers run account-based marketing from their terminals.

By Emilia Korczynska

Claude is the new cool kid of the block, and context engineering using Claude code is now the differentiator between actually successful AI-powered LinkedIn account-based marketing (ABM) campaigns and bogus ones.

By Emilia Korczynska

Practical AI ABM workflows from the ZenABM Bootcamp 2026 – ICP scoring at scale, derived signal detection, closed-won analysis, and the tool stack for running it without enterprise budgets.