The beauty of working in paid media is that no two days are the same – and that’s because we work in constantly developing markets with constantly developing tech & laws.
The paid media landscape has shifted yet again, but fear not, we’re letting you know how to keep your competitive edge against competitors and smash those revenue targets in a somewhat challenging digital world.
AI has taken the wheel, but paid media managers still need to steer
It’s no shock that paid media platforms have invested in AI products. Let’s cast our minds back to the launch of autobidding, which was a somewhat revolutionary AI campaign optimisation (when used properly), and then the launch of PMAX, advantage+ & AI Max. I can comfortably say that we’ve all had conversations regarding efficiency vs control.
AI won’t be taking our jobs any time soon.
Ultimately, the strategic takeaway hasn’t changed much: AI campaigns help free up our time to get stuck into deeper probing and revenue-unlocking actions, such as optimising those pesky product feeds in eCom and finding high-intent search signals to enhance your smart bidding strategy.
Google’s having an existential crisis: it turns out, when you deprecate the cookie, everyone else gets a piece of the pie.
There’s been a lot of noise in recent years about GDPR, changes to cookieless tracking and paid media managers have had to find new ways to contextualise their performance whilst adopting a first-party data strategy. But the challenges didn’t stop there. The rise of AI search advertising from providers like ChatGPT and Perplexity has added another round of hurdles (or opportunities) for paid media managers, and diminished Google’s shrinking market share some more, on top of the challenge of Gen Z shifting search behaviours by adopting TikTok to search.
It’s imperative that paid media mangers are aware of what high-intent keywords look like right now to ensure no revenue is left on the table, but also that we’re adopting multi-channel strategies to stay ahead of competitors in a shifting market.
The traditional marketing funnel is collapsing. In today’s world, consumers are digesting a record-breaking amount of signals from different platforms, but increasing budgets in retail media such as Amazon, and increased social commerce utilisation across brands, pose another risk to a brands market share… or opportunity.
At Embryo, we recently acquired Novaro, who offer TikTok Shop management, Sprii integration and support, live shopping and affiliate marketing solutions – ultimately, the next generation of retail is transforming how brands connect with audiences, and it’s proven to tap into new growth opportunities.
Is measurement broken, and how do we fix it?
Let’s recap – we’ve had a loss of third-party signals, and heavy reliance on first-party data in the last 12 months. The data available has been reshaped, and AI is inflating our metrics. Traditional multi-touch attribution models are failing.
What is MMM?
Marketing mix modelling is not a new tool, the methodology has been around since the 60’s but typically, it was dismissed for being too slow or expensive, and modern alternatives like XYZ attribution platforms (who no doubt cold messaged you on LinkedIn) took charge… Until we entered a cookiless world.
MMMs, such as Google’s Meridian, use aggregated data without relying on cookies and overlay external factors such as seasonality to statistically model the contribution of each channel. But be sure to use MM for the right reason, it’s a strategic compass, not a live dashboard.
How does incrementality testing help?
Whilst MMMs suggest which channels are working over time, incrementality testing can identify specific campaigns that are driving revenue… or whether it would happen anyway.
In a nutshell, these tests will show an ad to one group, and withhold serving ads to another and measure the difference n conversion rate. It’s not a perfect science, but it is an honest review in a cookieless world. Google offers it’s own incrementality testing, as does Meta.
What should brands do?
It’s my personal opinion that there is no perfect attribution solution, but paid media managers can cut through the data smoke screen by using marketing mix modelling (MMM) & incrementality testing for a more true and informed reporting style that actually works well and informs your strategy.
Connected TV (CTV), creator ads & user generated content (UGC) are no longer experimental
Us marketers love to tap into emotion for effective campaigns. It’s no surprise that video creative is surging.
Why CTV?
Connected TV has scaled – and advertisers are realising how cheap and effective it can be to reach your audience at peak viewing times.
Why use Creator Partnerships?
Social platforms are diversifying monetisation options beyond standard ad revenue, giving creators new ways to earn income. Brands should carefully select creator partnerships based on engagement and monetisation alignment.
Why use UGC?
UGC is organic content created by your customers, which is often seen as unbiased and helps reinforce positive brand awareness, increases engagement, grows a brand’s following and ultimately, leads to more sales.
There are countless blog posts about UGC, so I won’t regurgitate the same information… but I will say that they’re perfect content types to run on YouTube Shorts, Meta, TikTok, and even Reddit and Pinterest to help fill the ‘top of your funnel’.
So what?
AI is a great tool, and it isn’t going anywhere – we have a duty to adopt AI products and algorithms to help automate and handle some of the execution side of things, whilst we use our great human brains to improve strategy and oversee the data & signal quality we feed to the algorithms. By doing so, we will gain a better understanding of what channels are working best from our MMMs, whilst we keep an eye on incrementality too.
