The 360° E-commerce View: the Power of Combined Analytics

At Balkan eCommerce Summit 2026, Urszula Sury explored one of the biggest challenges modern eCommerce businesses face: the inability to fully trust their own data. The lecture focused on how fragmented analytics, attribution inconsistencies, and disconnected data sources prevent companies from understanding the real customer journey and making effective growth decisions. Through the concept of the “360° eCommerce view,” she demonstrated how combining marketing analytics, product analytics, and AI-powered insights can create a more accurate understanding of business performance and customer behavior.

The Biggest Problem in eCommerce Is Often Broken Data Trust

Urszula opened the presentation by addressing a frustration shared by many businesses:

reports frequently do not match.

Companies often see:

• different conversion numbers in Google Ads and Google Analytics
• conflicting attribution models
• inconsistent campaign performance data
• and incomplete customer journeys.

Over time, this creates:

a loss of trust in analytics itself.

Businesses begin making strategic decisions based on:

• incomplete information
• fragmented data
• or inaccurate attribution.

According to the lecture:
this silent data inconsistency is one of the biggest hidden risks in eCommerce growth.

Marketing Analytics Alone Is Not Enough

One of the key themes of the presentation was that:

many companies focus too heavily on acquisition metrics while ignoring user behavior after the click.

Most businesses analyze:

• campaigns
• channels
• ROAS
• and acquisition costs,

but fail to properly track:

• how users behave on-site
• what drives retention
• why customers return
• or why they abandon purchases.

Urszula emphasized that:

revenue is generated through user behavior, not only traffic.

Without understanding the complete customer journey,
companies cannot accurately optimize long-term growth.

Walled Gardens Create Attribution Problems

A major part of the lecture focused on:

“walled garden” platforms.

Platforms such as:

• Google
• Meta
• TikTok

keep much of their data private and do not fully share information with external systems or with one another.

This creates attribution distortions because:
multiple platforms may claim credit for the same conversion.

As Urszula explained:
a single customer purchase can appear as:

• one conversion in Meta
• one conversion in Google
• and another conversion elsewhere,

even though only one real sale actually happened.

This results in:

“ghost conversions”

and incorrect budget allocation decisions.

Synthetic Impressions Help Reconstruct the Real Customer Journey

To solve attribution gaps,
Full Stack Experts partnered with ROYvenue to use:

synthetic impressions.

Synthetic impressions use advanced algorithms to estimate:

• whether ad impressions likely occurred
• where they appeared
• and which platform contributed to the conversion journey.

By rebuilding these missing impression touchpoints,
businesses gain:

• more accurate attribution
• better ROI measurement
• and clearer understanding of channel contribution.

The lecture described this process as:

rebuilding the missing puzzle pieces inside the conversion path.

Product Analytics Reveal Why Customers Return

Another central topic was:

combining product analytics with marketing analytics.

Urszula explained that:
companies often know:

• where customers came from,

but do not know:

• what product interactions drove retention
• which products caused repeat visits
• or what behaviors created loyalty.

The presentation argued that:

true growth comes from understanding post-click behavior.

By combining:

• acquisition data
• behavioral analytics
• and retention signals,

companies can finally see the complete customer journey.

AI Enables Predictive Analytics and Retention Forecasting

The lecture also highlighted how AI can enhance analytics systems by adding:

predictive capabilities.

Through the integration of:

• marketing analytics
• product analytics
• and AI tools like Amplitude,

companies can not only analyze past behavior,
but also:

• predict future customer actions
• estimate return probability
• and identify behaviors linked to retention.

This allows businesses to:

• invest more intelligently
• prioritize high-retention customer journeys
• and optimize long-term value creation.

Retention Analysis Is More Valuable Than Raw Traffic Metrics

Urszula shared several examples of AI-generated reports designed to answer deeper business questions.

One of the most important examples was:

second-week retention analysis.

This report identifies:
which specific customer actions correlate most strongly with users returning to the website later.

Instead of measuring only:

• clicks
• sessions
• or purchases,

the analysis focuses on:

which behaviors transform casual visitors into loyal customers.

Another example involved:

retention by product category.

This allows businesses to identify:
which products or categories create repeat visits and long-term engagement,
rather than only short-term sales spikes.

True Transparency Creates Better Business Decisions

A major conclusion throughout the lecture was:

companies cannot optimize what they do not fully understand.

Without:

• unified analytics
• trustworthy attribution
• and connected customer journey data,

businesses risk:

• wasting marketing budgets
• optimizing the wrong channels
• and misunderstanding customer behavior.

The “360° eCommerce view” was presented as a framework for:

• restoring trust in data
• combining fragmented systems
• and creating a single source of truth for decision-making.

Key Takeaways

The lecture demonstrated that:
many eCommerce companies suffer from fragmented and inconsistent analytics data
different platforms often report conflicting conversion results due to attribution mismatches
“walled garden” ecosystems such as Meta and Google limit data transparency
ghost conversions can lead to incorrect marketing budget allocation
synthetic impressions can help reconstruct missing attribution touchpoints and improve ROI accuracy
marketing analytics alone are insufficient without understanding user behavior after the click
product analytics are essential for understanding retention and customer loyalty
revenue growth depends more on user behavior than traffic volume alone
combining marketing analytics, product analytics, and AI creates a complete customer journey view
AI-powered analytics can help predict retention and future customer behavior
businesses should focus more on retention-driving actions rather than only acquisition metrics
a unified “360° eCommerce view” enables smarter, more confident business decisions based on trustworthy data.