Predictions, not proxies: The data

If you’ve read our original piece on Predictions, Not Proxies, you’ll already understand why ecommerce teams need to move beyond outdated signals like traffic source and funnel stage.

To recap, it’s time for a mindset shift in ecommerce. To go from using surface-level proxies to using real-time intent predictions based on actual behaviour. This follow-up brings data to back up that claim.

What is the quality of a visitor? What are their preferences? And are they progressing towards a purchase?

These are critical questions in ecommerce. They underpin everything from targeting and messaging to optimisation and conversion. And yet, most teams still rely on proxies to answer them. Proxies that are easy to measure, but misleading. Easy to action, but often off the mark.

Proxies became popular not because they were particularly predictive, but because they were easy. They were what was available. And in the absence of better tools, convenience often beat accuracy.

In this article, we explore three key areas where Intent-proxy metrics lead to incorrect assumptions about our visitors.

• Visitor Quality: Why source-based assumptions break down the deeper a visitor engages
• Visitor Preference: Why relying on add-to-cart ignores 6.6x more signals of interest
• Visitor Progression: Why real journeys aren’t linear and what that means for timing

It shows where proxies lead teams astray, what gets missed, and what becomes possible when you see the real story underneath.

Visitor Quality: The Proxy vs The Prediction

One of the most ingrained habits in ecommerce is defining visitor quality by how they arrive. PPC traffic is high intent. Social traffic is low intent. Mobile users convert worse. Returning visitors convert better.

These assumptions are so common they’ve become unquestioned. But they’re all based on aggregate averages. And averages flatten nuance.

When we analysed session-level intent across millions of visits, we saw a different story. Yes, there are differences at the top of the funnel. But as users engage more deeply, the source matters less. What matters is what they do now.

The difference between ‘high’ and ‘low’ quality traffic almost disappears when we look at visitors by their 46th event, rather than their 1st.

‍

Our data shows that the gap between “low” quality traffic and “high” quality traffic closes the deeper they engage. Due to lower intent visitors progressively dropping off over the course of a journey, the remaining visitors will have a naturally higher intent.

We looked at how quality changes over time. Early on, yes, traffic source matters. But by the 30th, 40th, 50th event, it flattens out. The intent is shaped more by what visitors do than where they came from.

Social traffic looks low intent at first glance, but the ones who engage actually build really strong purchase intent.

But knowing which visitors have potential is only half the story. To personalise effectively, you also need to understand what they actually care about.

Visitor Preference: The Proxy vs The Prediction

It’s easy to think we know what visitors want. Add-to-cart events, product views and recency are the typical signals we treat as indicators of preference. But they’re all blunt. They assume interest based on the most trackable action, not the most telling one.

When we analysed onsite behaviour, we saw that affinity builds well before someone clicks ‘add to cart’. And in many cases, people never reach that point, even when they’re highly interested.

In our data, we identify a product affinity in 6.6x more visitors than we see actually add to cart.

‍

Tracking the movement of a visitor’s intent to add to cart reliably indicates their affinities to products and attributes.

Only a small number of online shoppers add to cart, but many more show product interest through how they browse. Through scrolls, hesitations, returns and comparisons, we can see strong signals of affinity well before any CTA click.

In fact, we see product affinity in over 6 times more sessions than we see add-to-cart events. That’s a huge chunk of opportunity that goes unnoticed if you’re stuck with proxies.

Put another way, if you’re only reacting to add to cart events, you’re often too late to really influence what matters. You’ve missed the moment they started to care.

And once you understand what they want, there’s one final question: are they getting closer to buying, or drifting away?

Visitor Progression: The Proxy vs The Prediction

Most ecommerce sites still treat the typical page funnel as a reliable guide. Homepage to PLP to PDP to cart to checkout. And on paper, it works. But real journeys don’t follow that script. They loop. They stall. They rewind.

And yet, many personalisation and performance decisions still hinge on page depth. Someone in checkout must be ready to buy. Someone on PDP must be evaluating. Someone who’s viewed 10 pages must be high intent.

Not quite.

Intent declines in over 65% of journeys at some point. It’s the norm, not the exception.

‍

It’s very common for visitor journeys to fluctuate as they engage. This graph demonstrates that the rate of visitors that indicated a drop in intent to purchase at some point increases the longer they shop. On average, 65% of visitors will lose intent at some point, with converting visitors showing a clear divergence from the typical visitor.

We found that intent doesn’t just rise as sessions go on. It’s not that people always leave with less intent, but that there are points within most sessions where the intent dips. That fluctuation is what matters.

Even among converters, a good chunk of them show a dip somewhere mid-journey. So if you’re only acting on high-intent signals, you’re missing the nuance.

If ecommerce journeys are this non-linear and you want to optimise experiences as much as possible, then real-time prediction isn’t a luxury. It’s a necessity.

The Real Opportunity

The previous Predictions, Not Proxies article made the case for change. I hope this one validates it, and shows what happens when you make it.

The truth is, ecommerce teams aren’t misreading intent because they’re careless. They’re misreading it because proxies were the only thing available for a long time. They were measurable. They were familiar. And they made things feel predictable.

But customer behaviour isn’t predictable. Not through proxies. Not in the way we’d like it to be as ecommerce teams. It’s dynamic, contextual and deeply individual.

And that’s the good news. Because once you stop relying on proxies, and start responding to predictions, everything sharpens. Personalisation becomes meaningful. Experiences become appropriate. And performance follows.

You can’t scale personalisation on proxies. But you can scale it by predicting intent.