A smarter way to see what really works on LinkedIn

Pull up a chair, grab a bambrew, and let’s talk about something that could quietly transform the way tech brands measure success on LinkedIn.

Attribution, figuring out which touchpoints really help someone take action, has always been one of marketing’s trickiest puzzles. Was it the webinar that sealed the deal? The carousel ad? Or that thought leadership article your CEO penned three weeks ago that planted the seed?

Until now, most models have been instruments. They hand all the credit to the first click, the last click, or spread it out evenly like butter on toast. Useful, but hardly accurate in a world where buyers zigzag across channels, devices, and time.

Enter LinkedIn’s Data-Driven Attribution model (LiDDA). It’s an AI-powered approach that promises to bring nuance, fairness, and clarity into the measurement game. And if you’re a tech marketer hungry for better ROI from LinkedIn, it’s worth paying attention.

Why attribution still keeps marketers awake at night

Every marketer knows the frustration of launching a campaign that mixes paid social, organic posts, a webinar, and an email nurture track. Leads roll in, but the reporting feels…off.

• Last-click models overvalue the final action and ignore the hard work done earlier.
• First-touch models credit the opening move, missing the long, patient nurturing that usually leads to enterprise sales.
• Multi-touch models spread credit around, but without really understanding influence.

This matters in tech, where buying cycles are long and decisions involve whole teams. As McKinsey notes, B2B journeys now span six to ten distinct touchpoints before purchasing. Without better attribution, budgets risk being misallocated, undervaluing the steady, trust-building activities that actually move the needle.The company trained its AI to mimic human language through vast text data. It uses this and the power of the internet to deliver responses.

What makes LiDDA different?

LinkedIn’s LiDDA doesn’t just guess or follow simple rules. It learns from real data. It looks at entire journeys, whether someone saw three ads or thirty, and determines the role each one played.
In plain terms:

• It learns from experience – LiDDA studies historical conversion patterns across campaigns.
• It embraces complexity – it can handle winding, non-linear customer journeys.
• It gives fairer credit – by sharing the glory across touchpoints, it reduces wasted spend and highlights which formats are really pulling weight.

In testing, LiDDA has already shown it can outperform traditional models at spotting the true drivers of campaign success.

Why we (tech marketers) should care

Tech audiences are rarely impulse buyers. They research, compare, and validate, often over weeks or months. Along the way, they’ll encounter multiple LinkedIn touchpoints:

• A thought leadership post from your CTO
• Sponsored content promoting your whitepaper
• An InMail invitation to an industry webinar
• A LinkedIn native newsletter like this one
• A product demo ad

Traditional attribution makes it almost impossible to know which interaction tipped the balance. LiDDA gives you a clearer picture, so you can:

• Allocate budget smarter – stop over-funding last-click lead gen ads and give proper weight to brand building and awareness campaigns.
• Tell a clearer story – show your board exactly how early interactions shape the journey.
• Optimise with confidence – if video ads are quietly doing the heavy lifting, LiDDA helps reveal their true impact.

A sign of where things are heading

LiDDA isn’t happening in isolation. Google has already moved away from last-click in Google Analytics 4, and Meta is experimenting with AI-powered attribution. But LinkedIn’s move is particularly important for B2B and tech marketers because:

• It’s built for LinkedIn’s dynamics – where professional influence and thought leadership matter just as much as clicks.
• It recognises messy journeys – it doesn’t try to squeeze B2B buying into a neat funnel.

While LiDDA currently focuses on LinkedIn, it hints at a future where marketers stitch together AI attribution across platforms for a more holistic view.

How to get started

Curious to try LiDDA? Here’s a simple step-by-step guide to get started:

1. Audit your current model – does it reflect your customer journey?
2. Segment campaigns by objective – LiDDA works best when goals are clearly defined.
3. Test and compare – run it alongside your existing model and see where the differences lie.
4. Share results internally – build confidence by showing early wins.
5. Think big picture – use LiDDA insights not just for reporting but to shape your 2025/26 LinkedIn strategy.

Putting people first

At Bamboo, we’ve always believed that tech marketing should be both human as well as smart. LiDDA is a step in that direction. It acknowledges that buyers aren’t robots marching through funnels, but people making complex decisions, sometimes emotionally or even irrationally, over time.

For marketers, this means less guesswork, more clarity, and a better story to tell about where your budget goes – and why it’s working.

Turn insight into action with Team Bamboo

Attribution will never be perfect. Human decisions are too nuanced for any model to capture completely. But tools like LiDDA bring us closer to understanding the messy, fascinating journeys our audiences take and help us build campaigns that respect both creativity and accountability.

And isn’t that what modern marketing is all about?

Want to put LinkedIn’s new attribution tools to work for your brand? Whether running organic thought leadership or paid campaigns, Team Bamboo can help you unlock better ROI from LinkedIn. Get in touch today for campaigns that truly reflect your customer journeys.