Analytics

Introduction

I’m a long term follower of some famous people in this field such as:

I follow their advice, have read their books and blogs, have implemented some of their suggestions, and can adhere to their vision on analytics.

The most important Analytics project is to define, implement, execute and finetune the Digital Marketing & Measurement Model for your company and its business units.

My former ICT experience designing and implementing CRM solutions, enterprise data warehouses, data mining solutions (big data) and a sense for number crunching and workflows, have helped me a lot to get a strong footprint in Analytics.

A technical ICT background is very handy in the field of Analytics, for example when implementing – deploying – validating the tracking for websites and mobile apps.

Welcome to the Awesome World of Data-Driven Decision Making where you should be aware of potential data smog.

Current Tasks

  • Implementing Google Data Studio for business reporting purposes.

Certificates

  • Google Analytics Academy – Digital Analytics Fundamentals 2013 (my score = 94%).
    Download the PDF.

Google Analytics Academy - Digital Analytics Fundamentals 2013

Analytics Strategy

An Analytics Strategy judges Tactics based on Parameters and measures them using KPI’s against Goals.

A Goal is a measurable outcome that measures company success.

A KPI is a value used to measurable progress towards a Goal.

Parameters put tactics and KPI’s in context.

Tactics are the things you do.

Universal Analytics

The concept of Universal Analytics, which can be implemented in all analytics platforms, makes it finally possible to move away from traditional page views analysis to tracking real people / customers across online devices and offline environments. This is made possible in Google Analytics by assigning real User-Ids to the visitors, by importing data from your CRM system and data warehouses, and the innovative Measurement Protocol.

Universal Analytics is the analysis of qualitative and quantitative data of your properties and the competition, to drive a continual improvement of the online experience that your customers, and potential customers have, which translates into your desired outcomes (online and offline).

Analytics is no longer constrained to typical Web Properties (desktop websites). Its scope is actively being extended to all the touch points with your target audience; i.o.w also mobile apps, mobile websites, social media platforms, Internet Of Things, etc.

Analytics is popping up all over the place because it is becoming an integral part of many platforms, being desktop, mobile, social, advertising or optimization platforms. A good analyst knows what tool to use to get the best quality data.

The Google Analytics web analytics tool has opened the world of Analytics to the public; formerly it has been mostly the exclusive playing field of big companies that could afford to pay for it. We are now at the beginning of the verge to Universal Analytics.

Areas of Expertise

  • **Define a Digital Marketing & Measurement Model for your business.
  • A/B Testing – Split Testing.
  • Analytics Dashboards (both Strategic and Tactical) for web properties, mobile properties, infrastructure monitoring, business applications.
  • App Analysis (for native mobile apps).
  • Attribution analysis.
  • Audience segmentation.
  • Big Data (with Spark).
  • Buyer Persona definitions.
  • Competition Intelligence.
  • Conversion Funnel Optimization.
  • Desktop App Analysis (e.g. Google Chrome Web Store).
  • eCommerce Analytics for Webshops.
  • Heat Map Analysis.
  • Mobile App Analytics (Google Play, Apple iTunes, Firefox Marketplace, Amazon Kindle).
  • Keyword Analysis.
  • Performance and Stability Analysis on all platforms.
  • Social Media Analytics using various platforms.
  • Streaming Analytics.
  • Tag Management.
  • Time-Series Databases.
  • Traffic Analysis.
  • Trend Analysis.
  • User Experience Optimization.
  • Web Analysis.

The Major Analytics Platforms and Tools

I have the most experience using the Google Analytics platform.

The conceptual knowledge of Analytics can easily be applied to other Analytics tools such as Adobe Analytics and IBM WebTrends.

For example, I have also implemented and used these Analytics platforms:

  • MixPanel: an analytics platform which is more user- and event-centric (opposed to Google Analytics which is more pageview centric).
  • Woopra: the best platform for real-time analytics.
  • The analytics modules of the major social platforms such as Facebook page analytics, Facebook app analytics, Facebook advertising analytics, Twitter analytics, YouTube Analytics, etc.
  • The analytics modules of various App Stores such as the Google Play Store and the Firefox Marketplace.

Statistics

Google Analytics

I master most of the features of this product including some of its relatively new ones such as Universal Analytics tracking, multi-channel attribution (the solution to the Last Click disaster), Demographics and Interests feature, and Cohort Analysis.

  • Main areas:
    • Implementation, with or without the Google Tag Manager platform.
    • Reporting.
    • **Analysis (=transforming raw data into strategic and tactical insights for the business).
  • Autotrack.js
  • Conversion Funnels.
  • Custom Events implementation, reporting and analysis.
  • Develop Custom Dashboards outside the Google Analytics web interface using the Google Analytics API’s. The target platform is a web app or a Google Docs spreadsheet.
  • Develop standard Dashboards within the Google Analytics web interface.
  • Development using the Google Analytics API.
  • eCommerce Tracking.
  • Google Apps Script integration.
  • Google AdWords data sharing.

Tag Management Systems – Google Tag Manager (GTM)

Google Tag Manager is a relatively new tag management platform which is being adopted by the market very rapidly. The tag platforms will soon become pervasive (as Analytics already is today). This tag manager integrates very well with Google Analytics.

Main areas:

  • Project Setup.
  • Implementation.
  • Operations and Deployment.

Highlights:

  • I master Version 2 of GTM which was released in November 2014 and is evolving very rapidly as we speak.
  • I implemented Google Analytics tags, triggers, and a custom workflow solution using GTM Custom Events to issue Google Analytics Events in custom Javascript code of a web client.
  • I implemented a GTM Data Layer to manage the data flow from the web client to the GTM Backend.

Statistics

Related Mini-Projects

A/B Testing – Split Testing – Multivariate Testing

Main areas:

  • Google Analytics Experiments.
  • Optimizely: an analytics platform to manage A/B Tests.
  • Programmatic implementation using the PHP libraries namshi/AB (Namshi is a big eCommerce player in the Middle East), lwc/kumite and etsy/ab.
  • Feeding the PHP split test results into Google Analytics using GA Custom Events. This implementation required a custom developed PHP/Javascript bridge which passes the data from the split test logic (PHP on the server) to the Google Analytics code (JavaScript on the client).

Tools and Services

  • AdClarity (ads competition analysis).
  • Bing Webmaster Tools.
  • Collectd system metrics collection daemon.
  • ClickTale click tracking, heatmaps, conversion tracking.
  • Facebook Insights for Apps and Pages.
  • Follow.net (Competitor Analysis and Brand Analysis service. Customer Acquisition and Engagement).
  • Google Analytics.
  • Google Analytics addon for Google Sheets.
  • Google Tag Manager.
  • Grafana metrics dashboard and graph editor.
  • Google Webmaster Tools.
  • InfluxDb Time-Series Database Engine.
  • Optimizely optimization platform (a platform to manage A/B and multivariate testing).
  • TyNt Publisher Tools (CopyPaste tracking, SpeedShare feature).
  • Twitter Analytics.
  • Woopra Real-Time Customer Analytics.
  • WebLog Expert (analysis of raw webserver logs).
  • YouTube Analytics.
  • …many more…

Streaming Analytics Dashboards

An interesting development in the field of analytics is Streaming Analytics. It covers (near real-time) monitoring of various properties, e.g. putting metrics and events in a time perspective in a visual way. Note that this does not replace the standard approaches to Analytics; it is merely an addition.

These dashboards can be categorized as follows: Operational (DevOps), Strategic (CxO), Analytic dashboards (Marketing/Accountancy).

I believe that the implementation of Streaming Analytics Dashboards opens opportunities for other software products than the typical web analytics products such as Google Analytics and Adobe Analytics. You can already see that time-series databases and real-time monitor dashboard implementations are quickly gaining in popularity.

This is why I have executed in 2014 the following projects (amongst other ones):

These projects can easily be reused in other subject areas such as monitoring the traffic of people and trains at the metrolines system in Brussels, the status of your customer service department, the status of your e-commerce webshop or a live stream of all incoming leads and conversions.

You will start to realize that these dashboards can and should offer more than a typical Web Analytics product can do. I also think these high volume of time-series data with many custom metrics and attributes does not belong in a typical cloud analytics product or a Relational DBMS, such as Oracle, or a simpley key-value store. They should be implemented using a dedicated time-series database backend and a metrics dashboard frontend (remember the monolitic one-fits-all data warehouses and business intelligence tools which are typically not agile enough for these projects).

Related Skills

Analytics is becoming pervasive. This also means it becomes interwoven with many other skills such as:

Related Training

My Projects

Discover various Analytics implementations in my Project Portfolio. Or you can go to one of these Analytics mini-projects: