A working tour of Guilford's Google Analytics — what the plumbing does, what the words mean, which five screens answer real questions, and a guided lap you can do in ten minutes. Every number in this guide is your number, pulled from your own property.
Two different products, and almost everyone mixes them up. Tag Manager decides what gets sent. Analytics decides what you can see. If a number is missing, the answer is almost always that nothing is sending it yet — not that the report is broken.
| What | ID | Think of it as | What it actually does |
|---|---|---|---|
| GA4 property | 359308554 | The warehouse. | Where all the data lands and where you build reports. One property covers guilford.edu. |
| Measurement ID | G-09SSBH3WCE | The address on the parcel. | The web data stream inside that property. Anything tagged with this ID reports into 359308554. |
| GTM container | GTM-WZHR49S4 | The delivery van. | Google Tag Manager. It sits on every page, watches what visitors do, and sends the events to GA4. |
| Retired | GTM-5BZ4942 · UA-9584163-1 | The old van, and a dead one. | The previous container plus a Universal Analytics tag that stopped processing in 2023. Both removed. |
Guilford's four most valuable actions do not happen on guilford.edu. Applying goes to
Slate (apply.guilford.edu). Requesting information and booking a visit go to Slate.
Giving goes to giving.guilford.edu / GiveCampus. Your website's job is to get someone to those
systems — so what GA4 measures on your site is intent, and the finish line lives somewhere else until
those systems are tagged too.
They are not broken and they are not hiding. In the 90-day baseline there were 7,044 conversions and every one of them was enrollment-flavored — applications, information requests, email and phone clicks. Giving was not tracked at all. Standing that up is the point of the external-systems rollout, not something you can fix inside a report.
Nearly every reporting mistake is a vocabulary mistake. Learn these eight and most of GA4 stops being mysterious. The right-hand column is Guilford's own 90-day baseline, so you have a feel for what normal looks like on your site.
| Term | What it means | Yours, in 90 days |
|---|---|---|
| User | One person — really, one browser on one device. | 78,234 in 90 days. The same person on a phone and a laptop counts twice. |
| Session | One visit. Ends after 30 minutes of inactivity, then a new one starts. | 120,036 — so the average person came back about 1.5 times. |
| Event | Anything that happened. In GA4 everything is an event, including a page view. | A page view, a click on Apply, a form submit, a search, a file download. |
| Key event | An event you have flagged as mattering. (Google renamed "conversion" to this.) | 7,044 in 90 days. You choose which events get the flag — it is a switch, not a calculation. |
| Engaged session | A visit that lasted 10+ seconds, or saw 2+ pages, or fired a key event. | The bar is genuinely low. It is the opposite of a bounce. |
| Engagement rate | Engaged sessions ÷ all sessions. | 45.0%. Our post-launch target is ≥ 47%. |
| Dimension | A what or where — always text you can group by. | Page path, channel, device, country, event name. |
| Metric | A how many — always a number. | Sessions, users, event count, engagement rate, average duration. |
A dimension and a metric only mean something together. 45% engagement rate is not a fact about Guilford — it is the average of every page, device and channel mixed together. Split it by device and desktop and mobile behave differently. Split it by channel and Direct behaves nothing like Display. The number at the top of a report is the least interesting version of that number.
Sessions are 120,036. Split by channel, that is 51.8% Organic Search,
31.2% Direct, 5.1% Display, 4.0% Referral, 3.1% Organic Social, 2.6% Paid Other. Split by device it
is 63.9% desktop and 35.3% mobile. Now the same total tells you three different stories — a
search-led site, with a very large group of people typing you in from memory, mostly on a laptop. That last
group is largely current students and staff, which is why /current-students
(15,946 views) sits second only to the homepage.
GA4's menu is large and most of it you will never open. These five carry the work. Each one below is written as the question it answers, because that is how you will actually go looking for it.
Reports → Realtime
The last 30 minutes. Use it to prove a tag fires or a page is live — never to judge performance. Open your site in another tab, click something, and watch yourself appear.
Reports → Acquisition → Traffic acquisition
Sessions by channel. This is where you see Organic 51.8% and Direct 31.2%, and where paid campaigns show up. Set the dimension to Session source / medium for detail — that is where encoura / display (6,113) lives.
Reports → Engagement → Pages and screens
Your top-pages list. / 44,537 · /current-students 15,946 · /faculty-and-staff 8,193 · /admissions/apply 7,840 · /program-finder 6,179. Sort by engagement rate rather than views to find pages punching above their weight.
Reports → Engagement → Events
Every event by name and count. This is where Guilford's own events live — cta_click, apply_start, form_submit, site_search. Click any event name to see its parameters.
Reports → Tech / User → Demographics
Device, browser, screen size, city. Desktop 63.9% / mobile 35.3% / tablet 1.1%. Useful when a page looks fine to you and broken to a third of your audience.
The date picker is the most important control on the screen. It sits top-right and it defaults to the last 28 days. Change it once and it follows you from report to report. Tick Compare and pick "preceding period" or "same period last year" — on an admissions site, year-over-year is nearly always the honest comparison, because your traffic has a season and last month does not.
Ten minutes, start to finish, in your own property. Nothing here changes any setting, so nobody can break anything. The point is to end up somewhere you did not already know.
359308554. If you see a different number, every figure in this guide will
disagree with your screen.guilford.edu in another tab and click an Apply button.
Find yourself in the event list. You have just watched the container fire — that is the whole pipeline
in one motion.Session source / medium
and find encoura / display.cta_click. Click it. Scroll to the parameter
cards and look at cta_type — apply, give, visit, rfi, learn. You are now looking at which
calls to action people actually press./visit. You have just filtered the whole report to one section. This is how you answer
"how is my page doing?" without building anything.Check the date range first — it is the cause about eight times in ten. Then check whether the event existed that far back. Then check whether you are looking at users where you meant sessions. Only after all three is it worth calling it a problem.
GA4 gives every site the same generic events. These are the ones written specifically for Guilford, fired from the container on every template. They are the difference between "3,000 people clicked something" and "3,000 people clicked Apply, from the hero, on mobile."
| Event | Fires when | The question it answers |
|---|---|---|
| cta_click | Every call to action on the site, classified. | Which CTA earns the click — and where on the page it was. |
| apply_start | Someone left for the application portal. | The top of the enrollment funnel. Replaces three overlapping legacy events. |
| form_start / form_submit | A form was begun, and finished. | Carries form_type, so RFI is finally separable from every other form. |
| site_search | Someone used the site search. | What people cannot find. Read the search terms weekly — it is the cheapest content research there is. |
| card_click | A card in any grid was clicked. | Which stories, programs and profiles pull. |
| program_interest | A program page or the program finder was engaged. | The leading indicator for applications, by program. |
| filter_use / load_more | A listing was filtered or paged. | Whether your listings are usable or people give up. |
| donation_start / donation_complete | The giving flow began and finished. | Built and waiting — it turns on when GiveCampus is tagged. |
Each event carries parameters — registered in GA4 as custom dimensions, which means you can group and filter by them like any built-in field. This is where the real answers live.
The old setup fired three different events that all meant "someone tried to apply" — guilford_application_button
(1,889), guilford_app_click_to_apply_site (1,068) and application_page_visit (183) — which overlap
and cannot be added together. Forms were worse: 15,767 starts and 12,708 submits, with no way to tell an
information request from a help ticket. One clean event per action, with labels, is what makes a funnel possible at all.
Give new parameters 24–48 hours. A newly registered custom dimension takes a day or two to appear in the field list. If one is missing, that is nearly always the lag rather than a mistake.
Analytics rarely gets caught being wrong. It gets caught being read wrong. These are the five that will come up in your first month.
The site runs a cookie consent banner with Google Consent Mode. Visitors who decline are measured in a reduced, modelled way. If consent rates move — a banner redesign, a new regulation — your traffic will appear to move with it. Always ask whether the site changed or the measurement changed.
GA4 counts browsers; Slate counts applicants. One person applying from a phone and a laptop is two users and one application. GA4 tells you how many started; Slate tells you how many finished. When the two disagree, Slate is right about applications and GA4 is right about intent. Neither is broken.
Both mean GA4 could not tell. Direct is 31.2% of your sessions — some of it is genuinely people typing you in, and some is an untagged link, an email client, or a QR code. Treat a rising Direct share as a question about link tagging before you treat it as brand strength.
When someone crosses to the apply portal, that hop has to be configured or GA4 records a new session
referred by your own systems. You could see this in the baseline: portal.mist.com appeared as a
referral source with 1,834 sessions — your own applicants, counted as strangers arriving from outside.
A launch, a tag change, an email send, a snow day. Six months from now nobody will remember why the third week of March spiked, and someone will build a theory on it. GA4 has annotations — use them the day it happens, not the day you are asked.
Standard reports tell you what happened. Explore tells you where people stopped — and for an admissions site that is the whole game. It is one menu item down the left, and a funnel takes about three minutes to build.
cta_click where cta_type = apply, then apply_start.template. This is the moment you find out that
mobile drops out somewhere desktop does not.| Next | What it gives you |
|---|---|
| Looker Studio dashboard | The same data as a one-page read, organised by your four audience priorities — enrollment, giving, reach, wayfinding — so nobody has to learn GA4 to get the answer. |
| Scheduled email | Weekly to marketing, daily to us. The report finds you rather than the other way round. |
| External systems tagged | Slate and GiveCampus carrying the same container — the point at which apply_submit and donation_complete start reporting, and the funnel finally has a bottom. |
| Post-launch comparison | The 90-day baseline in this guide is the "before". Annotate the launch date and the before/after is honest by construction. |
Enrollment intent is well measured today. Giving is not measured at all, and application submits are inferred rather than confirmed, because both finish on systems that are not yet tagged. Anyone who tells you the giving number is zero is reading the tracking, not the donations.
This is the real test of the training. Every one of these is answerable from the five screens in section C plus one funnel from section G — no new tagging, no engineering, no ticket.
site_search. It is the shortest route to
knowing what your site fails to say.cta_click where cta_type = apply, and
apply_start. Those two are your leading indicators, weeks ahead of Slate.A closing word on judgement. Analytics is very good at telling you what people did and completely silent on why. Every number in here is the beginning of a conversation with someone who knows the audience — it is not the end of one. The colleges that get value from this are the ones that let the data pick the question, and let people answer it.