Migrate to Google Analytics 4 ?

No, really, you are fine…

 it’s just Google considers UX and QA staff redundant. 

OUR EXPERIENCE WITH GA 4

 

Makes us cry

  • Absence of basic metrics (bounce/conversion rate, etc)
  • Buggy Reports Constructor
  • Malfunctioning Realtime Report
  • 24 hours data reflection latency
  • Heartbreaking DYI UX -> Your Team Will Never Use This Tool
  • DataLayer pushes that will make your devs grey-haired

Exciting stuff

  • BigQuery Integration - advanced visualisation and ML-models
  • Ability to align attribution model with Google Ads
  • Possible to merge with data from CRM, DB, SAS, DCP etc.
  • Advanced spam traffic filtering
  • Cookieless tech based on Google Signals
  • Granular Remarketing Audiences

DYI ENTHUSIAST?

Get FREE GA4 implementation checklist and... good luck

NEED BASIC SETUP ONLY?

Fill in this form and get it done within 48 hours

Basic setup includes:

  • Free Audit (instructions will be emailed)
  • Property settings (filters, dimensions, etc)
  • dataLayer pushes documentation
  • Funnel / ecommerce events
  • Google Ads & BigQuery Linking
  • Funnel Exploration Report
  • Behavioral events setup (microconversions)
  • utm_parameters setup tool
  • Main KPIs Data Studio dashboard

READY TO ROCK AS A GRANDPA?

Six steps that will elevate data analytics in your org to the moon

Intro call & Data Architecture Sketch

Output:

NDA signed
Business needs defined
Data Architecture scheme

Tracking documentation to Developers

Output:

In case some dataLayer pushes or API calls are needed (in sheets, Jira, you name it)

Tracking deployment on prod

Output:

One more quality check and your data smootly flows to analytics tools

Audit & Implementation Scoping

Output:

Full data infrastructure scheme and the implementation scoping broken down into phases

Setup and testing on staging environment

Output:

We make sure everything is working smoothly before pushing to production

Data Visualisation & ML-models

Output:

We use BigQuery ML to build models that predict behaviors, segment traffic, spot anomalies and more

Intro call & Data Architecture Sketch

Output:

NDA signed
Business needs defined
Data Architecture scheme

Audit & Implementation Scoping

Output:

Full data infrastructure scheme and the implementation scoping broken down into phases.

Tracking documentation to Developers

Output:

In case some dataLayer pushes or API calls are needed.

Setup and testing on staging environment

Output:

We make sure everything is working smoothly before pushing to production

Tracking deployment on prod

Output:

One more quality check and your data smootly flows to analytics tools

Data Visualisation & ML-models

Output:

We use BigQuery ML to build models that predict behaviors, segment traffic, spot anomalies and more

Hop on a call with our data engineer      and have fun

TYPICAL DATA ARCHITECTURE

This is the basic architecture big boys and girls set in place

Build customizable dashboards and report that you and all stakeholders are gonna use on a daily basis.

Capitalise from all the data sources you have. Let's create a data architecture that tells the story about your customers.

Merge and manipulate raw data from all your data sources, send it to ads / visualization / machine learning tools.

Optimize your ad campaigns with ML-enriched data from every paid click you're getting. Skyroket the ROAS.

Predict behaviors, spot annomalies, segment customers, optimize advertising campaigns using machine learning models in BigQuery ML

Build customizable dashboards and report that you and all stakeholders are gonna use on a daily basis.

Capitalise from all the data sources you have. Let's create a data architecture that tells the story about your customers.

Merge and manipulate raw data from all your data sources, send it to ads / visualization / machine learning tools.

Optimize your ad campaigns with ML-enriched data from every paid click you're getting. Skyroket the ROAS.

Predict behaviors, spot annomalies, segment customers, optimize advertising campaigns using machine learning models in BigQuery ML

CASES

Some fun we had with our partners from E-commerce, product and content

FEEDBACK

Adam L. Correa CMO, Glimja.se

Ivan did an incredible job with everything. The Data Studio he built to track our online performance was exactly what we asked for. Fast, responsive, and skilled - I look forward to doing more projects together in the future!

Kate O. CMO, Cloudlinux

Nick and the Permetrix team really dug into our Google Analytics and provided some very helpful insights to issues we have with the setup. On top of that, they're super nice guys who treat their clients right!

Alexander Erin Owner, LinkedHelper

Was happy to have a business with Denis. We were lucky to benefit from his growth hacker’s mindset and excellent google ads, google analytics, google tag manager skills. Appreciate clear communication and ability to deliver on time. Will continue cooperation after some business model reshuffling. Looking forward.

Testimonial #3 Designation

Yaroslav did a great job setting up our initial analytics instance! We hope to work with him again as we continue to add to our website and optimize analytics tracking. I've recommended him and Denys from Perfmetrix to fellow founders in search of analytics and data assistance. Thank you!

Remko Brokherius Owner, DiamondsByMe

Denis has been extremely helpful with our marketing projects. His deep knowledge of Analytics and Adwords make him our go-to guy when it comes to setting up new marketing campaigns. He is dedicated to the success of the projects and client satisfaction. I will re-hire him in a heartbeat.

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