The Education Marketing Trends & Benchmarks Heading into 2027

Education marketing is becoming harder to measure at exactly the point when the student journey is becoming more complex. 

Prospective students rarely discover a course, decide on a provider, and apply in one sitting, which creates a problem for marketers. The channels that influence the decision aren’t necessarily the channels that get value.

This matters because education organisations are often making significant budget decisions using data that only captures part of that journey. GA4, ad platforms and last-click reporting can tell you where someone converted, but they don’t necessarily tell you what persuaded them to get there in the first place. 

Offline conversations, events, multiple devices, returning visitors and channels that influence without generating a click can all disappear from the picture.

So what does the data tell us about how education marketing is performing?

We’ve analysed enquiry data across education providers to look at where traffic is coming from, which channels convert best, and how the balance between forms and calls changes depending on the source. The results reveal some fairly significant differences between volume and actual enquiry performance.

We cover:

• Why measurement is hard in education
• Traffic share vs enquiry share by channel
• Forms versus calls
• Conversion rate by channel

💡 TL:DR

• Direct gets nearly a third of all traffic (36.5%), but many of those visits may be the final step in a journey that started through another channel, with earlier influence lost along the way.

• The smallest traffic sources can be some of the strongest converters. Referral, organic social and email all convert above 8.5%, showing why judging channels by traffic volume alone can miss where genuine intent and trust are being created.

• Students don’t always apply where they first show intent. Education is heavily forms-led overall (90.6%), but students can go on to apply or enrol offline through open days, campus visits or meetings with admissions teams. Those interactions are important data points in the journey, but can be missed by tracking and ad platforms, leaving them with incomplete data to use when deciding where to optimise and invest.

• Paid social brings in almost a fifth of all traffic and converts at 8.3%, well above paid search, suggesting its contribution may be underestimated when measurement focuses too heavily on the final click.

Why measurement is hard to get right in education

The education journey creates three particularly difficult measurement problems.

Long consideration windows. A student might first encounter an institution through paid social or an event, then return weeks later through branded search or direct traffic to apply. Last-click reporting gives the final touchpoint the value, while much of the earlier influence disappears.

Offline interactions. Open days, campus tours, careers fairs and conversations with admissions teams can be critical to the final decision. If those interactions aren’t connected back to the marketing that generated the original interest, the journey looks shorter and less marketing-driven than it really was.

Fragmented platform reporting. Google, Meta and other platforms each report applications using their own attribution models and windows. They can all claim value for the same eventual applicant, making it difficult to understand what’s genuinely driving results when each platform is viewed in isolation.

Cookie loss and identity gaps. Privacy changes have made a complicated tracking problem harder still. Prospective students often make several visits across different devices, researching anonymously before eventually submitting an enquiry, application or enrolment. Losing visibility partway through that journey doesn’t just leave a data gap, it can quietly remove the earlier touchpoints from the record altogether, leaving whatever came last, direct, branded search, or a form fill, to take the value for work that started somewhere else entirely.

The result is a familiar problem. Channels can look more or less valuable than they actually are, simply because the measurement model isn’t capturing the full journey.

With that context in mind, here’s what we’ve found when we look at the education sector specifically, using the data we’ve tracked across our own customers in the education sector.

💡 Pro Tip

If a lot of this sounds familiar, particularly the long consideration periods, offline interactions, or channels that influence a decision without directly generating a click, it’s worth looking at unified measurement. We’ve put together an ebook that explores how to combine different measurement methodologies to build a fuller picture of what’s working and where to focus going forward.

It’s particularly useful for education organisations managing long decision journeys across online and offline channels, where a student might start their journey online but ultimately convert through an offline interaction. Because when those offline interactions disappear from your measurement, platforms are left with an incomplete picture of what drove applications and enrolments. That can then feed into the bidding and optimisation decisions they make on your behalf.

Read the unified measurement framework for Education

Traffic share versus application rate by channel

Direct traffic often includes people returning to a site after being influenced by other marketing activity, particularly when they’re already familiar with the institution. That means some of the earlier marketing influence can disappear from the attribution record, while Direct gets recorded as the source of the eventual visit.

Social Paid generates 18.9% of sessions but 28.2% of applications, while Organic Search generates 17.4% of sessions but 23.3% of applications. 

Both are contributing a considerably larger share of applications than their share of traffic would suggest. That doesn’t necessarily mean either channel is responsible for the entire journey, but it does show that looking at traffic volume alone can seriously understate their contribution.

The same pattern appears, on a smaller scale, across Email, Referral, Social Organic and AI Referral. Each generates a larger share of applications than sessions, suggesting that the people arriving through these channels are more likely to be further along in their decision-making process or arriving with stronger intent.

What this highlights is the measurement challenge we outlined earlier. The channel generating the most traffic isn’t necessarily the channel generating the most application activity, and the channel getting the final application doesn’t necessarily explain what influenced the decision. 

In education, where journeys can span weeks, multiple devices and online and offline interactions, those are two very different questions.

Forms versus calls

At an overall level, education is a forms-driven sector. Just over 90% of applications come through a form, with the remaining 9.4% coming through a phone call. But that split only tells part of the story, because the application recorded online isn’t necessarily where the student journey ends.

Education is particularly prone to offline interactions influencing the final decision. A prospective student might first discover an institution online, but go on to attend a school or college event, attend an open day, meet with an admissions team or speak directly with an advisor before eventually enrolling. 

Those interactions can be highly influential, but they’re often difficult to connect back to the marketing activity that generated the original interest.

That’s especially important when it comes to paid media. Ad platforms are increasingly using application data to decide which audiences to target, where to bid and which campaigns to prioritise. If a student was influenced by an ad but ultimately enrolled through an offline interaction, that outcome may never make its way back into the platform. 

The platform is then optimising against an incomplete set of outcomes, potentially favouring the activity that generates the application it can see rather than the activity that is actually driving the most enrolments.

So while forms account for the vast majority of recorded applications, education marketers shouldn’t assume that online form submissions represent the full picture of marketing-generated demand. 

Connecting offline outcomes back to the marketing activity that influenced them can give both marketers and ad platforms a much clearer signal about what’s actually driving enrolments.

Forms versus calls by channel

Every other channel is overwhelmingly forms-led, most above 90%, but email flips to 51.7% calls versus 48.3% forms. That makes sense when you think about what email is usually being used for by this point in the journey. 

It’s rarely a first-touch channel, it’s more often a nurture sequence, an admissions follow-up, or a direct line to someone who has already shown interest and is now further along, at which point picking up the phone is a natural next step rather than filling in another form.

Paid search also stands out a little, with 15.3% of its applications coming through calls, noticeably higher than organic search, social or referral. 

That’s probably worth a second look if you’re running click-to-call extensions or prominent phone numbers on paid search landing pages, since it suggests that channel in particular is pulling in people who are ready to have a conversation rather than fill in a form.

Application rate by channel

The top five channels by application rate are all clustered tightly between 8.3% and 8.9%, and every one of them relies on some form of prior trust, whether that’s a recommendation, an AI-generated referral, an organic social following, a subscribed email list, or a paid social audience that’s been built up over time.

Paid search can play a supporting role that doesn’t always convert on the first visit, and direct, as we’ve already covered, is frequently the final step of a journey that started elsewhere. 

Neither number should really be read at face value without factoring in what’s happening earlier in the journey.

Final thoughts on measurement in education

The main takeaway is that no single measurement method is going to capture the full picture of education marketing. Student journeys are too long, too fragmented and too often split between online and offline interactions for a single last-click view to tell you what is really driving applications and enrolments.

A more practical approach is to use a combination of measurement methods. First-party tracking and multi-touch attribution can help connect the individual touchpoints across the student journey, while impression modelling can account for channels that influence prospective students without generating a click. 

Marketing mix modelling can then bring in the channels and outcomes that are harder to track at an individual level, including TV, events, out-of-home and other offline activity.

The aim isn’t to find one “perfect” attribution model. It’s to build a measurement framework that gives you enough signal to understand what each channel is contributing, where your budget is actually working and where the gaps in your data might be.

That’s particularly important for education because the same data isn’t just used for reporting. Signals increasingly feed back into the platforms running your campaigns, influencing bidding, targeting and optimisation. The better the signal you give them, the better informed those decisions can be.

If you want to explore what a more unified approach could look like for your own education marketing, book a demo with Ruler and we’ll walk through your data with you.