Why data is important when building a website

Why Data Matters When Building a Website

Data matters because, when properly collected and structured, it directly increases conversions and reduces wasted ad spend. Without accurate data on visitors and products, your online store or website operates in the dark: you don't know where customers get stuck, and you don't know why your ads aren't paying off.

Two benefits are measurable right away. First: properly configured analytics reveal where users abandon the checkout process, allowing for immediate fixes. Second: complete product data prevents rejections in advertising systems, keeping your budget where it actually delivers results.

In practice, this means three things:

• a properly configured GA4 setup for tracking the user journey,
• a properly structured product feed for Merchant Center,
• and a contractor, like Moxy-web, who builds this into the planning phase, not only after launch.

Key Takeaways

Data only increases conversions and lowers advertising costs when it's collected in a structured way and regularly checked for reliability.

Table of Contents

• How Data Affects Conversions and Business Decisions
• Which Types of Data You Actually Need for a Web Project
• Where in a Project Data Actually Creates Value
• What a Client Should Require From a Contractor Before and After Launch
• What Moxy-web Brings to Every Such Project
• Why Data Quality and Reliability Determine a Project's Success
• Data Security and Privacy Aren't a Separate Project
• The Role of Data in Leadership's Strategic Decision-Making
• Qualitative and Quantitative Data: Why You Need Both
• How Data Drives Innovation and Better Processes
• Practicality Over Perfection: What Actually Matters With Data
• How to Start Working With Moxy-web
• Sources
• Frequently Asked Questions

How Data Affects Conversions and Business Decisions

Every KPI in e-commerce reflects the data behind it. Conversion rate tells you how many visitors actually buy, average order value (AOV) tells you whether you're selling the right product combinations, and cart abandonment rate reveals where the checkout process is turning buyers away. Without these three numbers, every decision about design or advertising is a guess.

Rec LJ's guide to online store optimization clearly shows that customer segmentation and regular monitoring of these KPIs lead to concrete sales improvements, not just nicer-looking charts in reports.

Expert tip: Before commissioning a site redesign, ask your contractor to first review existing cart abandonment data. It often turns out the problem isn't the design — it's a single step in the checkout process.

Data mistakes cost money in two ways:

• incorrectly configured sources in Google Analytics distort the picture of channel performance,
• missing or incorrect GTINs in a product feed cause entire categories to be rejected in advertising systems.

Research on the use of web analytics among Slovenian small and medium-sized businesses finds that while businesses do measure traffic better after implementing analytics tools, they often underuse the data they collect for actually optimizing their processes. Analytics without action is just a nice-looking table.

Which Types of Data You Actually Need for a Web Project

Clients often think "data" just means Google Analytics. In reality, it's four separate categories that need to work together.

Analytics data measures what users do on the site: clicks, add-to-cart events, completed purchases, time before leaving the page. Without properly configured events (not just basic visit counting), you don't see the real user journey, as confirmed by an analysis of Google's business tool, which points out how often GA4 is misconfigured at smaller businesses.

Product data is the second pillar, essential for any advertising through Google. Required attributes include:

• a precise product title (no abbreviations),
• a GTIN or another valid identifier,
• price and currency in the correct format,
• real-time stock availability.

Google's Merchant Center guidelines precisely specify which attributes are mandatory. A missing GTIN or an incorrect price means the product gets rejected before the ad even has a chance to show.

Structured data (schema.org markup) tells search engines what's on a page. Without it, Google has a harder time understanding whether something is a product, an article, or a service, which reduces visibility in search results.

Content and integration data from PIM or ERP systems ensure that prices, stock, and product descriptions stay aligned across the warehouse, the online store, and advertising channels without manual duplicate work.

Where in a Project Data Actually Creates Value

Data isn't something you tack on at the end of a project. Its value shows up across three distinct phases of building or redesigning a website, and each phase has its own job to do.

1. Planning phase. This is where you define which data sources already exist (an existing GA4 setup, an old product feed, an ERP system) and which KPIs will measure success. If a contractor doesn't ask about this, the project starts without a goal.
2. Launch phase. Before the site goes live, every tracking event needs to be tested, and you need to verify that the product feed transfers correctly into Merchant Center. An improperly tested event means months of blind data.
3. Optimization phase. This is where data actually gets used: segmenting customers by behavior, A/B testing landing pages, and iterating on design based on results.

A/B testing and segmentation are considered the most direct tools for improving conversions, since they allow for iterative improvement of the user journey without major risk, as also emphasized in the sales optimization guide. Instead of changing the entire page based on a hunch, you change one element, measure the result, and only then roll the change out further.

Each of these phases requires a different kind of attention, and businesses that skip the planning phase often end up returning to it after several months of wasted budget. It's worth thinking about how testing web solutions contributes to a business's success before signing a contract with a contractor.

What a Client Should Require From a Contractor Before and After Launch

A good contractor will ask you about this data before they even start designing. If they don't ask, ask yourself.

Before work begins, verify access to your existing Google Analytics and advertising accounts, a list of SKUs with valid GTINs, quality image assets for every product, and a clear pricing, discount, and returns policy, since all of this feeds into the structure of the product feed.

Technically, the following points fail most often:

• the correct structure of the product feed (title, price, availability, category),
• a unique item_group_id for every product variant (color, size),
• a valid, accessible image_link for every variant,
• a working GTIN without duplicated or made-up values.

Businesses with larger product catalogs often automate feed management, since manually maintaining hundreds of SKUs simply isn't feasible without errors.

In the first month after launch, track three things: the number of completed purchases relative to traffic, the share of rejected products in Merchant Center, and cart abandonment rate broken down by checkout step.

What Moxy-web Brings to Every Such Project

When building or redesigning websites and online stores, Moxy-web doesn't treat data as an add-on tacked on after the project wraps up — it's part of the core design. In practice, this means concrete work across several areas:

• custom development of websites, stores, and apps, with a structure for analytics and tracking built in from day one,
• integrations with external systems (ERP, PIM, advertising channels), so product data doesn't go stale from manual upkeep,
• hosting and technical maintenance that keeps tracking events working even after updates,
• a user-friendly content management system, where the client can update descriptions and prices themselves without a developer.

The collaboration starts with the client's input data: existing analytics accounts, product list, target KPIs. From this, Moxy-web designs the site and product feed structure so that measurement is possible from day one, not only after it turns out something is missing.

Why Data Quality and Reliability Determine a Project's Success

Unreliable data is worse than no data at all, because it leads to the wrong decision with a false sense of certainty. If GA4 counts internal visits from employees as "real" visitors, the conversion rate drops artificially, and leadership might unnecessarily shut down a channel that's actually performing well.

Reliability of product data matters just as much. If the price in the product feed differs from the price on the site, Google Merchant Center either rejects the product or, worse, shows the customer the wrong price, leading to complaints and eroded trust that's hard to rebuild.

Data quality improves through three concrete measures: excluding internal traffic from analytics, regularly reconciling the product feed with actual stock levels, and verifying that all required attributes are filled in before every major publication. According to findings from an analysis of Google's tool, properly configuring GA4, including excluding internal visits, significantly improves data reliability and prevents faulty optimizations.

For a business, this comes down to one rule: data needs to be checked regularly, not just once at launch. The market, inventory, and prices change weekly, sometimes daily, and a data source that was accurate in January can already be wrong by March.

Data Security and Privacy Aren't a Separate Project

Website data security isn't solved with a single add-on at the end — it's built through decisions made during the design phase. The foundation is an encrypted connection (HTTPS), which protects the data transferred between a user's browser and the server. Without it, browsers flag the site as untrustworthy, which lowers trust and, in turn, conversions.

Privacy is the other side of the same coin. An online store that collects email addresses, delivery addresses, or payment information needs a clear data processing policy and technical protection against unauthorized access. This isn't just a legal obligation — it's a business one too: a single security incident can destroy years of customer trust.

In practice, this means regular software updates, restricting admin panel access to authorized people only, and data backups that allow for quick recovery in case of problems. Businesses that hire a contractor for maintenance don't have to worry about these issues day to day, since they're built into the monthly service.

A similar principle of caution applies to analytics data: user data should be handled anonymized where possible, and stored only for as long as it's actually needed for business decisions. Security and privacy, then, aren't an obstacle to using data — they're the condition that lets you use data at all without risk to your business and your customers.

The Role of Data in Leadership's Strategic Decision-Making

A strategic decision made without data is a guess with more expensive consequences. When leadership decides whether to expand the product line, enter a new market, or increase the advertising budget, they need an answer to three questions: which products actually generate profit, which channels bring in customers who actually buy, and where in the checkout process the business is losing the most potential customers.

Without these answers, decisions get made based on gut feeling or on what worked last year. The market changes faster than leadership's intuition does.

Data also allows for faster correction of wrong decisions. If a new campaign is poorly designed, clear metrics let you catch that in the first week, not at the end of the quarter when the budget's already spent. That's the difference between a business that adapts on the fly and one that finds out it was wrong when it's already too late.

For small and medium-sized businesses, this mainly comes down to one thing: data-driven strategic decision-making isn't a privilege reserved for big corporations with their own analytics departments. Basic infrastructure — a properly configured GA4 and a well-organized product feed — is accessible to any business that commissions a site redesign from a contractor who treats this as part of the core offering, not as an extra service.

Qualitative and Quantitative Data: Why You Need Both

Quantitative data tells you how much and what is happening. Conversion rate, number of visits, average order value, cart abandonment rate — these are all numbers you can compare over time and across channels.

Qualitative data tells you why it's happening. This includes user session recordings, post-purchase surveys, customer comments, and direct feedback through chat or email support. Qualitative data is what tells you the reason is a delivery cost that's too high and only shows up at the very last step.

Businesses that focus only on quantitative data often end up optimizing the wrong thing, because they see the symptom, not the cause. Businesses that rely only on qualitative impressions without numbers, on the other hand, can't prove whether a change actually improved the outcome.

The best approach combines both types: quantitative data shows where the problem is, qualitative data helps you understand why, and then a new quantitative measurement after the change confirms whether the fix actually worked. This loop is the foundation of any serious online store optimization process — not a one-time fix.

How Data Drives Innovation and Better Processes

Innovation in e-commerce rarely means a completely new idea out of nowhere. More often, it means data reveals a pattern nobody had noticed before, and the business responds with a change competitors don't have yet.

For example, analyzing the user journey might show that a certain group of customers regularly browses products on mobile in the evening, but rarely completes a purchase on the mobile version of the site. That's not data for a one-time fix — it's a signal for a broader overhaul of the mobile experience, one that could open up a new sales segment.

Product data offers similar insights on the supply side. If a certain product category consistently gets a lot of views but a low purchase rate, that could point to a wrong price, poor photos, or missing information in the description — concrete fixes, not just a general "improve marketing."

Internal business processes improve in a similar way. When an inventory data source is connected directly to the website through an integration, manual entry errors disappear — errors that previously led to selling products that were actually out of stock. That's not just a technical improvement; it's fewer customer complaints and less time spent fixing mistakes after the fact.

Businesses that regularly review their data spot opportunities for improvement faster, before competitors do. Those that collect data but never review it have the same infrastructure, but no results.

Practicality Over Perfection: What Actually Matters With Data

The biggest mistake I see among clients working on web projects isn't a lack of data — it's the belief that you need a perfect analytics system in place before you can even start optimizing. That's backwards.

Conventional advice says a business should first build a comprehensive analytics infrastructure and only then think about conversions. In reality, it's better the other way around: start with three or four key events that directly measure revenue, and only then expand the system. A perfect system nobody reviews is just as useless as no system at all.

An underrated factor is discipline in maintaining product data. Businesses invest in an advertising budget but forget that a single missing GTIN or a mismatched price can wipe out the effect of an entire campaign. The order of priorities should be: first a well-organized, reliable data source, and only then a bigger advertising budget.

A reader commissioning a site redesign should ask their contractor for a concrete answer to the question of which three metrics will be tracked from day one, and how they'll be used for decisions in the first month. If the contractor doesn't have an answer, the project probably won't deliver the promised results, no matter how nice the site ends up looking.

How to Start Working With Moxy-web

When building or redesigning websites, stores, and apps, Moxy-web's approach is to build analytics and product data into the project from the very first sketch, rather than adding them at the end once the fix-it budget has already been spent. That means fewer surprises after launch and a concrete measurement system from day one.

The collaboration starts with a review of your current state: which analytics accounts already exist, how your product catalog is organized, and which business goals are the priority. From that, Moxy-web designs a site, product feed, and integration structure tailored to your scope — not a generic template.

Beyond development and integrations, Moxy-web also offers hosting, domain registration, graphic design, and ongoing technical support, so you don't have to go looking for a new contractor for every minor change after launch. If you'd like a concrete proposal for your project, take a look at the offering at Moxy-web and request a quote for building or redesigning your web solution.

Sources

• Analysis of Web Analytics Use Among Small and Medium-Sized Businesses in Slovenia
• Improving Online Store Sales Through Analysis and Optimization - Rec LJ
• Google Ads: Required Product Data Attributes for Merchant Center

Frequently Asked Questions

Why does data matter when building a website?

Data shows where users get stuck in the checkout process and which products or channels actually generate revenue, allowing for concrete fixes instead of guesswork.

What data do I need to provide a contractor before starting a project?

You'll need access to your existing analytics, a product list with GTINs, image assets, and a clear pricing and returns policy.

What happens if a GTIN is missing in Merchant Center?

Google rejects the product or limits its visibility, which reduces the impact of your advertising budget regardless of its size.

How often should I check data quality after launch?

Check product data and analytics at least once a month, since stock, prices, and user behavior change on an ongoing basis.

Does Moxy-web also help with setting up analytics and product data?

Yes, Moxy-web builds integrations and tracking setup into the project planning phase, not only after the website or store launches.

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