Practically every article on trends or predictions from the past 18 months has talked about AI revolutionising how we work. While that’s true to a degree, machine learning has been a core element of Performance Marketing for nearly ten years (an absolutely horrifying realisation for those of us who think we’re still young). Most famously, this was represented by the launch of Smart Bidding in Google Ads way back in September 2016, but since then, the ecosystem has been punctuated by ever more frequent evolution and innovation.
Of course, the mainstream acceleration of AI-powered tools and platforms has brought the terminology to the fore and the landscape (not to mention the content you’ll consume on a daily basis) is packed with AI recommendations. With that in mind, we want to dig down below the AI surface and focus on the specific technical elements that could have the most impact on B2B brands over the next 12 months.
- First-Party Data: The Ultimate Competitive Advantage
The end of third-party cookies isn’t just a B2C challenge – in fact it’s arguably a bigger inflection point for B2B performance marketing, where multiple decision influencers require nurturing towards an MQL conversion point over weeks and months.
We’ve had a few false dawns, but third-party cookies look like they’ll finally be phased out in Chrome by 2025, following the tightening of Intelligent Tracking Prevention (ITP) in Safari and Firefox. With B2B buying cycles being longer and more complex, tracking across multiple touchpoints will be even harder than it is today.
It’s likely that attribution as we know it will break down, with performance marketers being pushed towards first-party data strategies and modelled ‘probabilistic’ attribution models, which in plain English is basically taking a best guess at output.
To stay ahead, think about implementing Server-Side Tagging (sGTM) to own and control your first-party data pipelines – this also has the added benefit of stripping code off your website and speeding up load times. B2B companies can also use historical CRM data to create audience segments based on prior intent signals.
- Ad Automation vs. Manual Campaign Management
As we mentioned at the outset, Smart Bidding has been around for a long time now but further iterations are allowing the platform to manage performance at a scale humans simply can’t match through manual bid adjustments.
Google and Meta, in particular, are shifting towards black-box automation (e.g. PMAX, Advantage+,) which kind of feels like taking your hands off the wheel while driving, but if set up in the right way and with an appropriate amount of data to learn from, it can enhance performance to new heights.
In this predictive world, feeding the right signals to the algorithm through first-party CRM data, offline conversions, and detailed audience insights is essential and shouldn’t be skipped. Combine this with Value-Based Bidding (VBB) to train platform models to optimise towards profit instead of a CPA, and you’ll be ahead of the curve.
Aside from bidding, utilising AI models to support creative testing and copywriting is another route to improve the overall performance of campaigns and shouldn’t be seen as a cheat code – the direction of travel is a shift from traditional execution to a much more nuanced skill set around signal optimisation.
- LinkedIn Performance: Cracking the Algorithm
We work exclusively with B2B clients and all, without exception, utilise LinkedIn Ads for demand generation. We see 2025 as the year when LinkedIn finally scales up and rivals Google in terms of B2B demand generation, but only if advertisers move beyond the expensive CPC trap generated by the native audience targeting in the platform.
LinkedIn ad formats are evolving, and their AI-driven targeting is getting smarter, meaning manual audience layering is becoming obsolete. The introduction of lead generation forms and offline conversion tracking are primary signals for optimisation, and native content amplification through formats such as document ads are essential for engagement-driven retargeting.
Utilising the LinkedIn Website Demographics tool will help segment high-intent accounts and synchronise the data with LinkedIn Matched Audiences. Doing this allows advertisers to adopt a full-funnel approach, with TOFU thought leadership, MOFU lead gen forms and BOFU retargeting using nurturing sequences.
It’ll take time to break the habits of LinkedIn Campaign Manager users, but ditching the native audience targeting in favour of first-party account lists (especially useful for ABM-type targeting) and offline conversion data will help your LinkedIn campaigns optimise towards bottom-line revenue instead of low-value leads.
- Privacy-First Measurement vs. Traditional Attribution Models
Google Ads has been sunsetting last-click attribution for some time, and in 2025, we expect the final nail to be put into the coffin of what historically was the most popular way to report on performance. Advertisers will be pushed (if they are not already there) to Data-Driven Attribution and modelled conversions to construct their reports.
We talked about Server-Side Tagging a little earlier, but this, alongside Conversion APIs (CAPIs) will effectively be mandatory for accurate B2B tracking. Gaps in data will be filled using blended data, something which usually generates heated internal debate with clients around what is ‘real’ data, particularly when consent rates are low.
Our advice is to embrace it – we’re all in the same boat, so shifting to probabilistic attribution via Google Enhanced Conversions will get us closer to the truth, as will the use of UTM-based URL enrichment to track multi-touch engagements across your gated and ungated content.
The main point to emphasise is that due to privacy and consent, you are NEVER going to see the full picture again. Once that’s accepted by Performance Marketers (and perhaps more importantly, senior leaders), we can be at peace knowing that attribution will never be perfect, but modelled measurement will unlock the path to optimisation.
- B2B Paid Search: From Keywords to Intent Signals
Google has for some time been deprioritising manual keyword targeting in favour of intent-based Smart Bidding and Performance Max. We see nothing to suggest that this direction of travel is going to change, rendering manual targeting essentially obsolete for end users and changing the face of search optimisation.
From a B2B perspective, broad match keywords plus audience signals will outperform manual targeting in most campaigns, while on the user side of the coin, conversational search and AI-generated search results (SGE) will redefine how the SERPs are interacted with (and more importantly, how a user journey progresses).
We don’t recommend putting all eggs in the Smart Bidding basket and never have – in some instances, a Single Keyword Ad Group (SKAG) managed manually can extract better performance than automated bid strategies – but taking a step towards broad match combined with first-party conversion data is a great way to maximise reach.
The great keyword obsession is starting to dwindle, and feeding Google Ads as many data signals as you can, from first-party audience lists to offline conversions to CRM data, will help move you towards full-funnel audience intent modelling and a route to accelerating high-quality relevant traffic and leads.
Final Points: Performance Marketing Predictions in 2025
The future of performance marketing is technical, data-driven, and privacy-first. B2B brands that see incremental success in 2025 will master first-party data activation and server-side tracking, shift away from manual campaign management to AI-driven optimisation and crack LinkedIn’s engagement-based ad ecosystem.
However…at The Honeybee Group, we don’t just follow trends – we engineer strategies that drive long-term, sustainable B2B growth that goes beyond lead generation. If you’d like our assistance in building a Performance Marketing strategy or enhancing your Paid Media performance with a Paid Media Consultant, then let us know, and we’ll be delighted to connect 🙂