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We provide an end-to-end solution for reporting needs of marketing executives and specialists – covering the whole process from data integration and cleaning to customized dashboards covering:
Channel and campaign performance incl. Data-Driven Attribution, Media Mix Modelling
Slice data by product brands, categories or individual SKUs
Customer lifetime value models, cohort analysis, segmentation
Do you want to know more? Get in touch with Mi team
Examples of Reports Visualisation
Cover all your data and reporting needs in marketing
Easily model scenarios “what would happen if I made change X to my marketing plan”
Understand future lifetime value of your customers
Predict customer churn, propensity to buy and act on these information
Understand full profit & loss on SKU, brand or product line granularity
Identify top-value customers and see what is important to them
Understand the incremental business impact of TV, Youtube, TikTok, Snapchat or influencer marketing
See what the most profitable products, categories, brands are and boost their promotion in Facebook and Google
Find optimal allocation of marketing budget across channels and improve your total marketing ROI
Quickly identify areas that are at risk of not fulfilling the budgeted numbers
Optimize online marketing using advanced data signals about products and customers - activate to Facebook, Google, your emailing tool or other advertising platforms
Over 200 Marketing And Other Data Sources
..and more
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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:
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
Example use cases might be
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!
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.
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.