How smart tech is reshaping your strategy - and what to do about it
When people talk about AI in marketing, it’s often with a mix of excitement, overwhelm and suspicion. Think chatbots, voice assistants, or headline-grabbing tools like ChatGPT. But here’s the truth: the most powerful AI in your business isn’t futuristic - it’s already quietly running inside the tools you use every day.
If you’re sending Klaviyo campaigns, launching Advantage+ ads, or selling through Shopify, AI isn’t something you might use in the future. It’s already there, shaping your strategy whether you realise it or not.
So, where is this ‘hidden’ AI?
It’s in features with names like “smart send time,” “predictive audiences,” and “personalised merchandising.” You’ve likely seen these prompts while setting up a campaign - maybe even used them without realising they were powered by machine learning.
Let’s break it down with some real-world examples:
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Klaviyo: an email marketing platform built for e-commerce - uses predictive analytics to send emails at the moment each customer is most likely to open them. The feature is called Smart Send Time, and it learns from user behaviour, so your emails land when they’re most likely to convert.
One client saw open rates increase by 7.63% and click-through rates by 33.7% - with no changes to the audience or messaging. Just better timing, powered by machine learning.
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Meta Ads (Facebook & Instagram): a campaign type in Facebook and Instagram Ads - uses machine learning to automatically test different images, headlines, and audience segments. It reallocates budget to the top-performing combinations in real time - removing much of the manual guesswork.
In fact, businesses using AI in their Google Ads campaigns saw an average 30% increase in click-through rates back in 2022. Whilst Meta and Google use different systems, results from AI-led Google campaigns show similar patterns - with some reporting a 30% uplift in click-through rates.
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Shopify: one of the world’s most-used e-commerce platforms, offers AI-powered product recommendations. These are personalised based on a shopper’s browsing history and purchase behaviour - helping boost basket size without extra work from your team.
One study of 100+ e-commerce sites found that adding product recommendations to the checkout page led to a 915% uplift in conversion rate. A client we work with has started seeing a lift in conversions since adding this capability to their checkout drawer - a small tweak with measurable results.
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HubSpot and other CRMs: use predictive lead scoring to help your sales team focus on the hottest prospects. AI analyses how users engage with emails, website content, and forms - then ranks them based on how likely they are to convert.
In one Salesforce study, teams using AI-powered lead scoring were more than twice as likely to prioritise high-quality leads effectively. For growing brands, that can mean less time chasing cold prospects - and more time closing the right ones.
These aren’t futuristic features. They’re here now - and brands that understand how to use them are seeing better targeting, stronger engagement, and smarter use of resources.
Why brands miss it
The irony? Many marketers and founders in our space don’t realize they’re using AI. In a recent trend scan, we found real user questions like:
“Is Klaviyo AI or just analytics?”
“What’s actually happening with Advantage+?”
“How do I know if my tech stack is using AI?”
This quiet revolution is happening behind the scenes - and because it’s baked into tools you’re already using, it’s easy to miss.
But ignoring it means missing out on valuable optimisation - and wasting time doing things manually that your platforms could automate better and faster.
Take imagery, for example. Some brands are already using tools like Canva’s Magic Studio or Adobe’s generative fill to clean up assets, extend backdrops, or create visuals from text prompts - all powered by AI. But because it’s so seamless, they often don’t think of it that way.
And that’s the catch. When you don’t recognise where AI is working for you, you’re less likely to spot where else it could help. That means missed optimisation - and wasting time doing things manually that your platforms could handle faster, and better.
What you can do now
You don’t need a PhD in machine learning. But you do need to know what your platforms are capable of - and how to use them to your advantage.
Audit Checklist
Here’s a quick audit to get you thinking:
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Are you using predictive send times - or still blasting emails manually?
Platforms like Klaviyo or Mailchimp can send at the optimal time for each contact based on past behaviour.
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Is your subject line being auto-tested, or are you going with your gut?
Smart tools test multiple subject lines in real time and prioritise the top performer automatically.
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Do you segment based on real customer behaviour, or just broad demographics?
Actions speak louder than age or location. Your data can go deeper.
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Are your ads set to Advantage+ - and are you feeding it enough creative variety to learn from?
Meta’s Advantage+ and Google’s Performance Max both work better with diverse inputs (images, headlines, CTAs).
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Does your site recommend products automatically - or in the same order for everyone?
Shopify and BigCommerce offer AI-driven recommendation engines to personalise suggestions based on user history.
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Is your search bar ‘learning’ what people are actually looking for - or just matching keywords?
AI-powered search tools can refine results based on intent, patterns and even fuzzy terms.
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Is your product feed optimised for Meta or Google ads - or are you editing manually?
Feed management tools can clean, format, and sync your data automatically – improving relevance and saving hours.
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Do you know what content drives conversions - or just clicks?
Predictive analytics tools help tie content to actual revenue outcomes, not vanity metrics.
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Is your platform suggesting the next best action – and are you acting on it?
CRMs often surface AI-powered nudges like “This lead is going cold” or “It’s time to follow up” – but they only work if you pay attention.
If you’re answering “I’m not sure” more than once, you’re probably leaving performance on the table.
Final thought
The best part? You don’t need to chase AI – it’s already in your stack. The opportunity now is to start using it on purpose.
If you're not sure where to start, Sciart is offering a free “AI in your stack” mini-audit for EAN readers. We’ll show you what’s already working behind the scenes – and where a few small changes could make a big difference.
The robots are here. They just look like your favourite tools.
