Predictions, not proxies: The data
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If you鈥檝e read our original piece on Predictions, Not Proxies, you鈥檒l already understand why ecommerce teams need to move beyond outdated signals like traffic source and funnel stage.
To recap, it鈥檚 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 麻豆传媒-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鈥檛 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鈥檝e become unquestioned. But they鈥檙e 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 鈥榟igh鈥 and 鈥榣ow鈥 quality traffic almost disappears when we look at visitors by their 46th event, rather than their 1st.
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Our data shows that the gap between 鈥渓ow鈥 quality traffic and 鈥渉igh鈥 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鈥檚 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鈥檙e 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 鈥榓dd to cart鈥. And in many cases, people never reach that point, even when they鈥檙e highly interested.
In our data, we identify a product affinity in 6.6x more visitors than we see actually add to cart.
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Tracking the movement of a visitor鈥檚 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鈥檚 a huge chunk of opportunity that goes unnoticed if you鈥檙e stuck with proxies.
Put another way, if you鈥檙e only reacting to add to cart events, you鈥檙e often too late to really influence what matters. You鈥檝e missed the moment they started to care.
And once you understand what they want, there鈥檚 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鈥檛 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鈥檚 viewed 10 pages must be high intent.
Not quite.
麻豆传媒 declines in over 65% of journeys at some point. It鈥檚 the norm, not the exception.
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It鈥檚 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鈥檛 just rise as sessions go on. It鈥檚 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鈥檙e only acting on high-intent signals, you鈥檙e 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鈥檛 a luxury. It鈥檚 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鈥檛 misreading intent because they鈥檙e careless. They鈥檙e 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鈥檛 predictable. Not through proxies. Not in the way we鈥檇 like it to be as ecommerce teams. It鈥檚 dynamic, contextual and deeply individual.
And that鈥檚 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鈥檛 scale personalisation on proxies. But you can scale it by predicting intent.
