How Web Data Powers Smarter Marketing Decisions
In this Marketing Stack fireside chat, Marco Giordano, Founder of SEOtistics and a trusted voice in web analytics, joined the session to explain why most teams need to rethink the way they measure marketing performance.
Marco’s main point was clear. Teams should stop treating page views, sessions, clicks and bounce rate as default success metrics. These numbers can be useful, but they do not mean much unless they are connected to the business model.
He explained that there are no marketing KPIs in isolation. There are only business KPIs. Once a team starts with the business model, the right measurement approach becomes much clearer.
Why Page Views and Sessions Are Not Enough?
Marco explained that traditional metrics are not useless. They simply need the right context.
For a publisher, page views and traffic matter because the business may depend on display ads. More traffic can directly support more revenue.
For a B2B SaaS company, the story is different. Total users or sessions may not be the most useful measure. What matters more could be active users, product usage, qualified leads, demo requests or customer retention.
For ecommerce, revenue alone can also be misleading. A business does not just need more sales. It needs profitable sales. That means looking at margin, product mix and unit economics, not just transactions.
The larger point was simple. The same metric can mean different things for different businesses. A publisher, ecommerce brand, service company and SaaS platform should not measure success in the same way.
Why Business KPIs Should Lead Marketing Measurement?
Marco said teams need to begin by asking what the business actually needs to achieve.
For ecommerce, that may be profitable sales.
For SaaS, it may be active usage, retention or expansion.
For a publisher, it may be traffic quality, ad revenue and content performance.
For a service business, it may be qualified leads and sales opportunities.
Marketing metrics such as users, sessions, clicks and traffic can still help. They show how people are reaching the business. They help explain acquisition. They help identify movement. They help diagnose problems.
The mistake is treating them as the final goal.
Marco’s view was that marketers should use channel metrics to understand how marketing influences the business KPIs, not to replace them.
How to Use Web Data Based on the Business Model?
A strong part of the discussion focused on using web data with more discipline.
Marco explained that before teams worry about advanced analytics, they should understand how their metrics are calculated. This is especially true in GA4, where definitions have changed.
He used bounce rate as an example. Many marketers still think of bounce rate in the older Universal Analytics way, where it meant someone entered a page and left without further interaction.
In GA4, bounce rate works differently because it is tied to engagement rate. That means teams need to understand the tool before using the number in a report.
His advice was direct. Learn what the metric actually means before using it to make decisions.
He also explained that advice from one business model does not always apply to another. A news publisher may need speed and volume. A B2B SaaS brand may need authority, trust and relevance for a specific audience.
Good analytics starts with understanding the business, not copying a dashboard template.
Why Page Location Matters for Better Content Audits?
Marco also spoke about the difference between looking only at landing pages and looking at page location in GA4.
For content audits, he recommended looking at the full traffic picture of a page, not only the moments when it served as a landing page.
A page may not always be the first page someone visits. It may be the second, third or fifth page in a journey. If the team only looks at landing page data, they may miss how that page supports navigation, engagement or conversion later in the session.
This becomes important when combining data from Google Search Console and GA4.
Google Search Console mainly shows search related page data. GA4 can show broader behaviour across channels and journeys. Looking only at landing pages can make the analysis incomplete.
Marco’s point was simple. If you are auditing content, look at the full role a page plays, not only whether it brought someone in first.
What a Simple Analytics Stack Should Look Like?
The session then moved into what next generation analytics looks like in practice.
Marco said small businesses do not need to overinvest in data too early. If a business is very small, it should focus first on growth, marketing and the website itself.
Once a company becomes larger and has enough data to make analysis useful, it can start with a simple stack.
His suggested stack included BigQuery for storing data, Looker Studio for visualisation and Dataform for transforming the data.
This setup is simple, cost effective and useful for teams that want more control without building an overly complex system.
For larger businesses, the stack can become more complex. They may use more advanced tools, larger data warehouses, engineering support and stricter architecture. Still, the principle remains the same. Store the data properly, clean it, model it and report it in a way that supports business decisions.
Why Owning Your Data Matters in the GA4 and BigQuery Era?
Marco strongly recommended storing web data in BigQuery.
He explained that relying only on direct connectors or APIs can create limits. APIs can restrict how much data teams can access, how fast dashboards load and how much control they have over calculations.
With BigQuery, teams get more raw and granular data. They can calculate metrics properly, combine multiple sources, improve dashboard performance and keep historical records.
This matters because some platforms do not retain data forever. Google Search Console, for example, has limits on historical data availability. If teams do not store their data, they may lose important context over time.
Marco also pointed out that dashboards built directly through connectors can break, slow down or give limited views. When data is stored and modelled properly, teams can build faster and more reliable reporting.
The larger message was clear. If data matters to the business, the business should not depend only on surface level tools.
Why Attribution Is Not the Whole Answer?
The conversation also covered attribution.
Marco was honest that attribution is not his core specialty, but he shared a practical view. There is no perfect attribution model.
Last click attribution is limited because it gives credit only to the final touchpoint. That does not reflect how people actually discover, compare and decide.
At the same time, Marco warned that not every business needs to obsess over attribution. If a company has only a few channels and a simple journey, complex attribution may not be necessary.
Attribution becomes more important when a business spends heavily across many channels and needs to understand where budget should go.
Even then, Marco said the better focus is incremental impact.
Why Incremental Impact Matters More Than Perfect Attribution?
Marco explained that marketers should focus on proving what changed because of their work.
If revenue goes up after an SEO effort, that does not automatically mean SEO caused the full increase. Seasonality, brand activity, paid campaigns, word of mouth and other channels may also play a role.
That is why incremental impact matters. Teams need to understand what additional value a channel created after accounting for other factors.
He gave a simple way to think about channel value. If a leader doubts the value of SEO, imagine no indexing the website and watching what happens to sales over time. If a leader doubts paid ads, stop ads in a specific market and observe the business impact.
The point was not to make reckless changes. The point was to show that channels need to be judged by real business movement, not only isolated reports.
Why Brand Demand Still Matters in Analytics?
Marco also spoke about brand demand and long term awareness.
He explained that not everyone is ready to buy immediately. In many categories, especially B2B and high ticket purchases, only a small percentage of the audience is in market at any given time.
The rest may not be ready yet, but they still matter.
This is why brand building matters. People often buy from brands they already know, trust and remember. In B2B, this becomes even more important because buying decisions can involve many stakeholders, longer timelines and higher risk.
Marco explained that SEO and paid media both play a role. Paid can capture demand and support remarketing. SEO supports long term visibility, trust and discoverability. Neither should be treated as free or effortless.
SEO may compound over time, but it still requires resources, maintenance, people and investment.
What Leaders Should Take Away from This Session?
The strongest takeaway from the session was that analytics has not disappeared. It has become more serious.
Teams need to stop reporting numbers just because tools make them easy to report. They need to understand which metrics matter for their business model, how those metrics are calculated and how marketing activity connects to business outcomes.
Marco’s advice was practical. Do not chase vanity metrics. Do not overbuild your analytics stack before the business needs it. Do not trust every default dashboard. Do not treat attribution as perfect.
Start with the business. Define the KPIs that actually matter. Store your data properly. Use GA4, BigQuery, Looker Studio and Dataform in a clean and simple way. Measure incremental impact where possible. Build reporting that helps leaders make better decisions.
The session ended with a clear message. Next gen analytics is not about having more dashboards. It is about using the right data to understand what is actually helping the business grow.
