Data Solutions to Drive Your Profitability and Growth

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What We Do

We help companies from ambitious startups to large enterprises leverage automation and data in a privacy-safe way to optimise their marketing ROI, achieve sustainable growth and prove marketing value on the company’s top and bottom line.

Data Integration & Tracking

Collect and unify all your marketing data. 
End-to-end tag management & tracking setup.                            

Insights & Analytics

Marketing mix modelling. Forecasting, Attribution modelling.
Customer journey analytics.
Custom ML/AI modelling

Data Activation

Translating insights into better ROI. Connecting signals back to Facebook, Google Ads, TikTok, CDPs and other tools

how we can help you

  • Measuring and optimizing marketing channels ROI using modern Marketing Mix Modelling
  • Fully automated reporting – have all your marketing and sales KPIs in one place
  • Proving the ROI of your marketing activities – both short- and long-term
  • Complete tracking setup – Google Analytics 4, server-side tracking, tracking data enrichment, Conversion API
  • Connecting data from 200+ data sources and enriching them with ERP, CRM or finance data
  • Building your team’s data + analytics capabilities for a post-cookie world

Our products

Mi.Marketing Mix Modelling

Mi.Marketing
Reporting & Analytics

Our Solutions & Services

Marketing
Optimisation

Data
Analytics

Reporting &
Visualization

Development &
Data Engineering

Data & Measurement
Strategy

Google
Analytics 4

Tracking &
Data Collection

Cookieless
Marketing Measurement

Helping Leading brands with Marketing Effectiveness & Efficiency

our clients

We Are Ready to Hear from You & Improve Your Marketing ROI

What they said about us

Testimonials

Get in touch

our office

Billing Info

Marketing Intelligence s.r.o.

IČO: 09546529     

DIČ: CZ09546529

 

Lidická 884/6, Smíchov

150 00 Prague, Czech Republic

Let's talk

We are ready to hear from you & improve your marketing ROI

Let's Talk

Get in touch with Marketingintelligence team

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Coming Soon

Predictive analytics in GA4

One of the new and exciting features of GA4 is called “predictive metrics” – with these you can learn about your customers and their shopping behavior. These are added automatically to your data and are based on Google’s machine learning expertise.

GA4 currently includes the following predictive metrics:

  • Purchase probability: The probability that a user who was active in the last 28 days will log a specific conversion event within the next 7 days.
  • Churn probability: The probability that a user who was active on your app or site within the last 7 days will not be active within the next 7 days.
  • Predicted revenue: The revenue expected from all purchase conversions within the next 28 days from a user who was active in the last 28 days.

You can create audiences based on these values and leverage them in your advertising campaigns – for example, you could exclude users who have a high purchase probability as you may assume that these users will buy anyways and you don’t have to spend additional marketing dollars on them (test it) or try to win back an audience with higher churn probability with a special campaign or communication.

Data export to BigQuery

Google BigQuery is a cost-effective and highly-scalable cloud data warehouse optimized for high performance on very large data sets. With GA4 you can export all your event-level data to BigQuery for additional analytics or data science initiatives.

Example use cases might be

  • Joining GA4 data with other sources in your company – CRM, customer data, backend sales, and margin data.
  • Using GA4 data for advanced customer analytics for a better understanding of customer lifetime value or churn prediction.
  • Automate reporting in your BI tool.
  • Move the data to your on-premise or cloud data lake and data warehouse.

Example use cases might be

  • Joining GA4 data with other sources in your company – CRM, customer data, backend sales, and margin data.
  • Using GA4 data for advanced customer analytics for a better understanding of customer lifetime value or churn prediction.
  • Automate reporting in your BI tool.
  • Move the data to your on-premise or cloud data lake and data warehouse.

You will need to have a Google Cloud account set up and maintained for this purpose. That is why we are here and can solve all the infrastructure for you and with you!

Free data driven attribution in GA4

Since 1/2022 GA4 has made a data-driven attribution model available to all users – unlike in Universal Analytics where the DDA model was only available to GA360 customers.

DDA is an algorithmic attribution model that quantifies the value of each touchpoint in the user journey (such as campaign click) and it does so by smart modelling behind the scenes without human bias that is always present in rule-based models.

The DDA model in GA4 is also better than the one on GA360 as it takes into account up to 50 touchpoints in the user journey vs. the GA360 only took 4 touchpoints.

It is also possible to set the default attribution model to DDA (or another model) from the old Last Non-Direct Click. And then all your reports and data exported to BigQuery will use the newly selected model as default.

DDA in Google Analytics 4 excludes almost all direct visits from receiving credit – you may or may not like that, but as it’s been always the case with attribution we recommend validating any model using marketing experiments.

World without Cookies and GA4

GA4 is built for a world where more and more users opt out of cookie consent and other methods for data collection.

Google uses machine learning modeling to fill in the data gaps – some of these are already in the current GA4 others will be deployed in the future.

For example, modelling conversions allows GA4 to properly attribute conversions without user identification – this is crucial for optimized advertising campaigns and automated bidding. This covers situations such as some browsers limiting the time window for first-party cookies, conversions for unconsented users, Apple’s App Tracking Transparency (ATT) impacts, cross-device user behaviour, and others.