Affiliate marketing has always been competitive, but over the past few years it has become brutally data‑dependent. Traffic sources have diversified, Google’s algorithm has reshaped the SEO landscape, and affiliates now operate across multiple platforms, channels, and markets. In this episode, Michael Filletti, Co‑Founder of Routy, broke down what data‑driven performance really looks like — and why affiliates who still rely on instinct are leaving money on the table.

Michael’s background in business intelligence gives him a unique vantage point. He entered the affiliate world in 2018 and immediately saw the same pattern everywhere: affiliates were generating traffic, but they weren’t tracking it properly. Revenue was leaking, optimisation was guesswork, and decisions were based on incomplete information. Routy was built to solve exactly that problem — helping affiliates understand where their revenue comes from and how to grow it.

One of the biggest themes Michael highlighted was the impact of Google’s algorithm changes. Entire businesses saw their traffic drop by 75% overnight. For many affiliates, SEO had been their only channel — and suddenly, it wasn’t enough.

The result was a major industry pivot. Affiliates who once relied solely on organic search began expanding into paid media, email, SMS, and hybrid models. The shift wasn’t optional; it was survival. And with diversification came complexity — more data, more platforms, and more decisions to make.

This is where structured data becomes essential.

Every affiliate tracks clicks, FTDs, and revenue. But Michael emphasised that these are only the surface layer. Real optimisation happens when affiliates dig deeper into metrics that reveal why performance looks the way it does.

• Earnings per click (EPC) shows the true value of each outbound click.
• Revenue by acquisition month separates current performance from legacy traffic.
• Player value reveals whether a brand is actually worth promoting.

These metrics expose patterns that surface‑level dashboards miss. They also prevent affiliates from chasing vanity numbers — impressions, click‑outs, or traffic spikes that look impressive but don’t convert.

Michael’s advice is simple: choose a small set of KPIs and focus on incremental gains. Trying to optimise everything at once leads to overanalysis and paralysis.

Real‑time data is one of the biggest advantages affiliates can leverage, especially those running paid media. Clicks happen on the affiliate’s own platform, but conversions — signups, deposits, revenue — often arrive hours later through operator back‑ends.

Postback tracking changes that. When set up correctly, it sends conversions to the affiliate instantly, allowing them to adjust campaigns before they burn the budget. It also enables platforms like Google Ads to optimise automatically based on real conversion signals.

Setting up postbacks can be time‑consuming, but once the system is in place, it becomes a performance machine. Faster insights mean faster decisions — and faster profit.

AB testing has existed for decades, yet many Affiliates still measure success only by click‑outs. Michael explained why this is misleading. A landing page that generates more clicks doesn’t necessarily generate more FTDs. Sometimes the messaging encourages curiosity, not commitment.

The only meaningful comparison is the one that tracks the full journey — from click to conversion to revenue. With proper tracking, affiliates can test landing pages, content blocks, CTAs, and even brand placements with precision.

AB testing works because it’s simple, controlled, and actionable. And in a landscape where every percentage point matters, simplicity wins.

Traffic sources can make or break an affiliate campaign. Michael encourages affiliates to analyse markets, devices, and brand performance together rather than in isolation.

Some GEOs convert exceptionally well and deserve more focus. Others underperform because the landing page isn’t localised. Mobile traffic may dominate in emerging markets, while desktop still performs better in certain regions. Some brands convert strongly in one market but poorly in another.

The goal is to see the full picture — not just where traffic comes from, but where revenue comes from.

While predictive analytics is standard in many industries, it’s still emerging in affiliation due to fragmented data. But Michael believes it’s only a matter of time before affiliates adopt it widely.

Basic forecasting — projecting monthly revenue based on trends — is already accessible. More advanced models, such as recommendation systems that personalise brand suggestions based on user behaviour, are on the horizon. These systems could mirror the logic behind Netflix or Amazon: “Users like this tend to convert on that.”

The potential is enormous, and the affiliates who embrace it early will gain a competitive edge.

Attribution remains one of the hardest problems in affiliate marketing. Affiliates want to know not just how much they earned, but where it came from — which pages, which campaigns, which emails, which placements.

The solution is not a single tool but a complete tracking ecosystem. When affiliates can see the full journey, they can finally make decisions based on truth rather than assumptions.

Michael’s criteria for selecting a data platform are straightforward: coverage, insights, and support.

Coverage ensures the affiliate can track as many brands and data sources as possible.

Insights turn raw numbers into actionable decisions. Support matters because the data landscape changes constantly — platforms update, APIs break, and integrations shift.

A good tool doesn’t just collect data. It helps affiliates grow.

Data isn’t just a performance enhancer — it’s the foundation of modern affiliate marketing. Affiliates who embrace structured tracking, real‑time optimisation, and deeper analysis will outperform those who rely on instinct. As Michael put it, incremental gains compound. And in a competitive industry, that’s what separates the leaders from the rest.