This article explores data and digital analytics, how to avoid the pitfalls, with a focus on the role of web analytics and tag management to optimise website performance.
A strategic approach which blends human centred design principles can ensure that data becomes a tool for clarity and progress, not confusion and complexity.
The data and digital analytics space encompasses a wide range of tools and techniques used to collect, clean, store, analyse, and interpret data for the purpose of gaining insights and making informed decisions.
In today's data-driven world, the ability to measure nearly everything can quickly lead to information overload. Organisations often find themselves drowning in a sea of data, responding by creating a multitude of dashboards and reports that can further complicate the situation. This overwhelming abundance of information can obscure meaningful insights and hinder effective decision-making.
A more strategic approach is needed, one that incorporates human-centred design principles. By understanding the needs and goals of the people who use the data, we can cut through the noise and focus on the metrics and visualisations that truly matter, ensuring that data becomes a tool for clarity and progress, not confusion and complexity.
Data and digital analytics landscape
The data and digital analytics landscape is both a broad space as with many areas of specialisation. Some key areas include:
Measurement models - a framework which defines and organises the metrics and dimensions used to analyse data, relevant to your business goals
Web analytics - for capturing user interactions, track website traffic, and monitoring performance, such as with Google Analytics
Data visualisation - such as though dashboards and automated reports with various BI tools, such as Looker Studio
Notebooks - for data exploration, interactive analysis, and machine learning model development, such as with LiveBook or JupyterLab
Data processing pipelines - such as ETL (Extract, Transform, Load) processes
Data storage - centralising and consistently storing data from various sources, such as with data warehousing, data lakes, and data lakehouse
Specialised databases - such as analytics databases (designed to handle large volumes of data and support complex analytical queries such as BigQuery), time series databases (to store and manage time-stamped data), GIS databases (store and manage geographic data) or graph databases (for complex, interconnected data).
Context Digital has a core focus on measurement models and web analytics but also data processing pipelines with Elixir when needed (more below). An example of the use of a data pipeline may be to clean and blend email campaign data from an email marketing system with web analytics and digital advertising data and load it into an analytics database, such as BigQuery, for reporting and visualisation in a Looker Studio dashboard. This helps to provide an integrated 360° view of a campaign.
Measurement models
A measurement model is a way of measuring your organisation, website, product, service, or campaign performance by identifying the key factors that matter most. It provides a framework that defines and organises metrics and dimensions used to analyse data, ensuring they are relevant to your business goals.
A strategic measurement model demonstrating the flow from organisational and product strategy, through a strategically aligned model, to the identification of key metrics and data sources used by decision-makers.
For example, if you're an e-commerce business, your measurement model might include metrics like website traffic, conversion rate, and average order value. These metrics would help you understand how well your website is performing and how effective your marketing campaigns are. For a content site, it may be about content engagement.
Benefits of a measurement model include:
Clarity and focus: It helps you focus on what matters and is worth measuring, providing a clear direction for data collection and analysis efforts.
Alignment with goals: By aligning your measurement model with your organisational and customer objectives, you can ensure that the data you collect and analyse is directly tied to your desired outcomes.
Improved decision-making: A well-defined measurement model enables you to make informed decisions based on data-driven insights, leading to better strategies and outcomes.
Communication and collaboration: It facilitates effective communication and collaboration among teams by providing a common language and understanding of how success is measured.
Continuous improvement: Regularly reviewing and refining your measurement model allows you to adapt to changing business needs and improve your measurement practices over time.
In summary, a measurement model is not just a framework for measuring performance but an essential tool for gaining valuable insights, making informed decisions, and driving value.
Web analytics
Web analytics is the process of collecting, measuring, analysing, and reporting on website data to understand user behaviour and improve the overall user experience. It involves tracking website traffic, user interactions, and other relevant metrics to gain insights into how users interact with a website.
Web analytics can help you to:
Understand user behaviour and preferences: Web analytics can help you understand how users find your website, what pages they visit, how long they stay on each page, and what actions they take. This information can help you improve the user experience and make your website more effective.
Identify areas for improvement: Web analytics can help you identify areas of your website that need improvement. For example, you may find that certain pages have a high bounce rate or that users are not converting into customers. This information can help you make changes to your website to improve its performance.
Track the effectiveness of marketing campaigns: Web analytics can help you track the effectiveness of your marketing campaigns. You can see which campaigns are driving the most traffic to your website and which campaigns are resulting in the most conversions. This information can help you optimise your marketing campaigns and get the most out of your marketing budget.
Make data-driven decisions: Web analytics can help you make data-driven decisions about your website. You can use web analytics to track key metrics and then use this information to make decisions about how to improve your website and your marketing campaigns.
If you are not currently using web analytics, I highly recommend that you start today. Web analytics is a powerful tool that can help you improve your website and your business.Google Analytics 4 (GA4) showing the paths users take through the website.
Data visualisation and dashboards
Data visualisation is the process of presenting data in a way that makes it easier to understand and interpret. This can be done through the use of charts, graphs, maps, and other visual elements. Dashboards are a type of data visualisation tool that displays metrics, key performance indicators (KPIs) and other important data in a single, easy-to-read format.
The benefits of data visualization and dashboards are numerous. They can help you to:
Identify trends and patterns in your data
Make informed decisions
Communicate complex data to others
Improve your productivity
Save time
Improve your website traffic and conversions
If you're looking for a way to improve your understanding of data and make better use of it, then data visualization and dashboards are a great option. They can help you to see your data in a new light and make more informed decisions.Looker Studio dashboard example from Google
Data pipelines
Although there are specialist software and platforms for creating and executing data pipelines, such as Apache Airflow, Elixir is an excellent choice for building data processing pipelines, such as ETL workflows. In particular, this is due to its inherent scalability, fault tolerance, and concurrency features.
Some notable libraries and tools from Elixir’s ecosystem include:
Broadway - a concurrent, multi-stage tool for building data ingestion and data processing pipelines
Ecto - tools for mapping, validating and changing data as well as interacting with databases
Explorer - a fast dataframe library with support for CSV, Parquet, NDJSON, and Arrow IPC formats, with external databases integration via ADBC and direct connection to file storages such as S3
Nx - high performance numerical computing, such as for machine learning
Req - a HTTP client which is excellent for interacting with internet-based APIs and services
Oban - job management
Quantum - time based scheduling
FLAME - quickly scale up workloads in a lambda-like fashion.
Additionally, Elixir's functional programming paradigm promotes immutability and composability, enabling developers to build pipelines that are easy to understand and maintain.
Implementation
Context Digital is experienced in developing measurement models, setting up and deploying Google Tag Manager implementations, customising Google Analytics setups and creating useful dashboards and reports with Looker Studio.
