LinkedIn Offline Conversion Tracking: Should You Take the Plunge?

A couple of things are true for B2B advertisers looking to navigate the major ad platforms these days: 1) automations and machine learning are taking away lots of bidding and targeting controls; 2) if you’re forced to give up control and let AI take the wheel, anything you can do to train the algorithms is something to consider putting into play.

Offline conversion tracking (OCT), where you feed down-funnel data (e.g. MQLs, SQLs, opps, revenue) from your CRM into the ad platforms to teach it more about the leads you want the algorithm to find, has finally come to LinkedIn. This is welcome news for B2B advertisers – and for LinkedIn, considering Google and Facebook already offer more advanced OCT options.

But should you dive in right away? It’s complicated.

At Blackbird, we’ve always been almost exclusively manual in setting bids and targeting for LinkedIn. This is in part because, pre-OCT, we tested their automations and got very poor results – so poor that I’m skeptical OCT would make a big enough difference for us to use it in full.

If you do want to test it, there are two options for integration: 1) uploading CSV files manually; 2) setting up a Conversions API for any of LinkedIn’s marketing partners (which don’t include Salesforce):

As far as testing, I’d say keep your expectations in check. We’ve dipped a toe, but to really lean into the combination of automation and CRM data, I’d recommend using Campaign Group Budget Optimization (where LinkedIn shifts budget between campaigns within the Campaign Group based on performance) in tandem with OCT being auto-ingested through Conversions API. 

That said, Campaign Group Budget Optimization itself is also fairly new and unproven compared with manually controlled bidding. With Campaign Groups sometimes being previously used for purely organizational purposes, testing OCT with Campaign Group Budget Optimization in some cases will require a complete account structure overhaul. At Blackbird, the tests we run won’t be from retrofitting current client accounts; they’ll most likely come from building new client accounts in a structure that enables clean testing between manual and Campaign Group Budget Optimization setups. If the testing results are promising enough, that gives us a reason to restructure existing accounts. 

In summary, this is good news for LinkedIn and B2B advertisers – but it’s still more theoretical good news than it is a game-changer. It means advertisers will be able to influence the LinkedIn algorithm to some extent, but whether that algorithm is worth investing in yet is very much an open question.