Web Analytics
Web Analytics
What is web analytics?
- Analyzing visitor traffic, behavior, and conversions
- Improve with data, not gut feeling
- GA4 is the leading tool
Once web analytics takes hold, the first thing that changes is the language in the meeting room. “This landing page feels a bit disappointing” becomes “Of 1,240 entries, 62% left at the 25% scroll mark.” The debate shifts from taste to metrics, and that is the real payoff of web analytics. The same goes for budget allocation: channel-level data on contribution to consultations replaces the claims of the loudest voice. Still, data doesn’t hand you answers on its own. What question you bring when you open the dashboard decides whether the same screen is just a report or a plan for improvement.
B2B web analytics is designed differently from B2C. Purchase evaluation takes three months to a year, and monthly conversions often number only a few dozen at most, so comparing conversion rates page by page leaves too small a sample and mostly yields meaningless numbers. That is why you plant micro-conversions such as catalog downloads, spec sheet views, and quote form starts as intermediate metrics to build up data volume. It is also why GA4 is built around events rather than sessions. Two more things you can’t skip are a UTM convention sheet and hidden form fields. Only when traffic-source values travel with the lead into your CRM can you answer “which channel actually led to a closed deal?”
It also helps to be clear about what web analytics can and can’t answer. Log data tells you “what happened, and how many times,” but “why did they leave?” is the territory of heatmaps, session replays, and customer interviews. Finding the pages with high drop-off and fixing those pages are separate jobs. Add privacy regulations to the mix, and data goes missing after cookie consent banners, which is why more companies are moving to server-side tagging. Writing a one-page measurement plan before you switch tools pays off far more.
The most common misstep in practice is stopping at a “dashboard for reporting.” Someone screenshots the monthly visits chart and drops it into a meeting, but no one can say what changed compared with last month. When you set traffic growth as the KPI, you get the same pattern again and again: page views climb while inquiries stay flat. There are also basic mistakes that destroy trust in the data. Internal IPs and bots aren’t filtered out, so employees working late show up as visitors, and UTM labels scatter into “naver, Naver, naver_ad,” throwing off channel totals entirely. Conversion events get applied to both page views and button clicks, so the numbers come out at double the real figure. Once the numbers are wrong, sales stops looking at the data altogether.
John KimInstructor John Kim, author of B2B Marketing Design and CEO of Nanum Consulting
Junyoung NohConsumer and generational trend analyst & AI content marketing specialistA field that grew alongside the web. As tools like Google Analytics became widely available, it turned into a must-have marketing skill.
Consider a hypothetical case. Company A, which makes industrial measuring instruments (120 employees, annual revenue of about KRW 40 billion (≈ US$29,926,700)), got 9,000 website visits a month but only 12 quote inquiries. The head of sales dismissed the leads, saying, “Everything from the website is students or junk,” and the marketing team couldn’t say which channel actually generated real sales conversations. Over six months, they rebuilt their GA4 tracking from scratch.
- When Manager Kim of the marketing team opened the account, internal IP traffic and partner access were being counted as is, and the conversion was set to “any page view.” After excluding bots and the company’s IP range, monthly visits dropped from 9,000 to 6,400.
- We built a one-page UTM rulebook that standardized how source, medium, and campaign are written. Once the same rules were applied to Naver search ads, the newsletter, and the QR code on the trade-show banner, the three scattered buckets of Naver traffic merged into one.
- We broke the conversion into four steps: catalog PDF download, spec comparison table view, quote form start, and quote form submission. It revealed that only 12 of 88 form starts were submitted, and the cause was the 11 fields, including company name, department, and budget.
- Working with the web developer, we cut the form to 5 fields and moved the quote form to the bottom of the product detail page. Once UTM values were carried in hidden form fields and saved to the CRM, the head of sales said, “Now we can finally see where each lead came from.”
- Six months later, monthly quote inquiries rose from 12 to 31, and the form completion rate went from 13.6% to 34%. Trade-show QR visitors converted to consultations at 3 times the rate of search ads, so we shifted part of the ad budget to trade-show follow-up campaigns.