Analytics as the Foundation of Digital Decisions
Data is only valuable when it is collected correctly, interpreted properly and helps you make concrete business decisions. That is why analytics work doesn't start with a dashboard. It starts with defining goals, KPIs, data sources and how measurement will work.
Promodex works with web analytics, marketing data, product data and business information, from basic tracking setup to data science and machine learning.
Web Analytics
Web analytics shows how users find your website, interact with it and move toward conversion.
We analyze:
- traffic sources;
- landing pages;
- user behavior;
- events;
- conversion funnel;
- ecommerce;
- customer journey;
- marketing effectiveness.
Analytics Audit
Even if GA4 and GTM are already installed, your data may be incomplete or inaccurate.
During an audit, we check:
- tracking structure;
- events;
- conversions;
- duplicates;
- ecommerce data;
- UTM parameters;
- cross-domain measurement;
- connections to ad platforms;
- quality of the actual data.
GA4 and Google Tag Manager
We configure Google Analytics 4 and Google Tag Manager according to your business's measurement plan.
We can implement tracking for:
- forms;
- calls;
- registrations;
- downloads;
- checkout;
- purchases;
- subscriptions;
- custom product events.
For ecommerce, we separately validate products, transactions, revenue, currency and other commerce parameters.
Analytics Goes Beyond GA4
To get the full picture, data may come from multiple sources:
- website;
- mobile app;
- CRM;
- ERP;
- Google Ads;
- social media advertising;
- call tracking;
- ecommerce platform;
- internal databases.
When needed, this data can be combined for further analysis.
Conversion Funnel
Funnel analysis shows not just how many conversions you get, but the exact stage where your business loses users.
For example:
- traffic;
- product or service view;
- interaction;
- lead or add to cart;
- checkout or qualification;
- sale.
This makes it easier to set priorities for UX, marketing or development.
Competitor Analysis
Digital analytics should cover not only your own website but also the competitive landscape.
We can research:
- competitor site structure;
- SEO visibility;
- content;
- advertising activity;
- traffic channels;
- positioning;
- offers;
- digital presence.
Data from third-party tools should be treated as estimates unless it is the competitor's actual data.
Data Processing and Analysis
For businesses running several systems, the main problem is often not a lack of data but its fragmentation.
Data science work may include:
- data collection;
- cleaning;
- normalization;
- merging sources;
- exploratory analysis;
- pattern discovery;
- visualization;
- preparing datasets for models.
Business Data Analysis
We can analyze more than marketing metrics: sales, customer, product, order, retention and operational data as well.
For example:
- revenue trends;
- customer segments;
- repeat purchases;
- churn;
- seasonality;
- product performance;
- sales patterns.
Machine Learning
Machine learning makes sense when there is enough high-quality data for the task and a model can improve an existing process.
ML solutions can be used for:
- forecasting;
- classification;
- scoring;
- recommendations;
- anomaly detection;
- segmentation;
- other predictive tasks.
Forecasting
Predictive models can help estimate future values based on historical data.
For example:
- sales;
- demand;
- inventory requirements;
- customer activity;
- churn risk;
- other business behavior.
Forecast accuracy depends on data quality, process stability and the type of task, so we do not guarantee absolute model results.
AI Integration
AI can be more than a standalone chatbot. It can be part of a business application.
For example, for:
- search;
- data classification;
- document processing;
- content generation and structuring;
- customer support;
- recommendation systems;
- internal assistants;
- automation.
AI in Web and SaaS Products
Promodex can integrate AI functionality directly into a web service or SaaS product: frontend, backend, API, access control, history, analytics and connection to your business data.
The specific model or AI provider is chosen based on the task, cost, privacy and technical requirements.
Machine Learning and AI Are Not the Same Thing
Machine learning usually involves working with models and datasets for a specific prediction or classification task.
AI integration can use existing foundation models or external AI APIs without training a custom ML model.
That is why we offer them as separate services.
Data Quality
You can't build reliable analytics or an ML model on bad data.
Before complex analytical tasks, we check:
- completeness;
- duplicates;
- formats;
- missing values;
- historical consistency;
- business meaning;
- availability of required attributes.
Dashboards and Reporting
Analysis results can be turned into dashboards and a regular reporting system.
The goal of a dashboard isn't to show as many charts as possible, but to give your team the set of metrics it needs to make decisions.
Ecommerce Analytics
For ecommerce, we can analyze:
- traffic;
- product views;
- cart;
- checkout;
- purchases;
- revenue;
- AOV;
- repeat purchases;
- product performance.
SaaS Analytics
For SaaS, key metrics may include registration, activation, usage, conversion to paid, retention, churn and revenue.
The right measurement model depends on your business model and customer lifecycle.
B2B Analytics
In B2B, a single form submission is often not enough. A full picture requires combining marketing data with your CRM to track the path to a qualified lead, opportunity and sale.
Privacy and Data Handling
Analytics and AI solutions must account for the nature of the data, permissions, consent and the requirements of the applicable jurisdiction.
We do not use personal or confidential data in third-party AI services without the appropriate architecture and the client's permission.
Why Promodex for Analytics and Data Science
Promodex combines analytics with web development, ecommerce, SEO, PPC, SaaS and system integrations. So we don't just deliver a report: we can implement tracking, data transfer, CRM/API integrations, dashboards or AI functionality directly in your product.
We start with the business goal and the data, not with a particular tool. If properly configured web analytics is enough, we won't overcomplicate the project with machine learning. If the task calls for a predictive model or AI integration, we build a dedicated technical architecture around the real use case.
