Data visualisation: Unlock the story behind your data

Make data accessible to a large audience, and detect patterns, trends, and outliers in large data sets, to make faster data-driven decisions more accurately.
16 December 2021
data visualisation
Pallavi Kheria

Head of Data Strategy and Customer Analytics, UK

Namitha Padiyar

Product Engineering Manager, Analytics

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Data visualisation makes data accessible to a large audience by making it easier to comprehend multiple KPIs simultaneously, as well as detect patterns, trends, and outliers in large data sets. This process helps organisations make data-driven decisions faster and more accurately. Bringing data to life is the last mile in the data-to-insights journey.

What is data visualisation?

Data visualisation is the act of graphically representing information and data through the use of elements like charts, graphs, and maps, and delivered via digital infographics, dashboards, and other interactive tools. The goal of visualisation is to get easily digestible data to the people who need it, with all the data in one place, ready to be consumed. The process of creating data visualisations typically takes 6-8 weeks depending on the type of deliverable, number of data sources, number of views, complexity, and other factors.

The Benefits of Data Visualisation

When done properly, data visualisations:

  • Save time: all of the data is in one easily accessible place
  • Improve engagement: people want an easy way to use and interact with data, instead of struggling with spreadsheets
  • Make complex information easy to digest: visualisations can help organise multiple data points into layers that allow users to begin at a higher level and then go deeper if needed
  • Empower users to make data-driven decisions

Different users have different needs

Unlike other parts of the data engineering process, visualisations go to a wide audience within an organisation. Good visualisations must address the needs for all users, and recognise that some users may not be (or do not need to be) as data savvy as others. Here’s a quick overview of each audience and what they typically want.

Senior leadership (high-level overview)

  • Intuitive and consistent visualisations
  • Ability to quickly see the story in the data
  • Summarised views and executive reports, such as a quick overview of key metrics, data about what’s driving trends, and cross-metric comparisons across brands

Research and marketing managers (understanding what happened and why)

  • Variety of charts and analysis
  • Pre-defined reports that are simple to generate
  • Profiling and comparison of data for any market and segment
  • Easy filtering and deep dives
  • Pre-defined analytics templates for different objectives

Power users (answers to more detailed and complex questions)

  • Option to extract large data sets in a flexible manner with just a few clicks
  • Ability to switch bases, change percentage type, and create custom filters on the fly
  • Advanced analyses such as correspondence maps, simulations, and optimisations
  • A scalable platform for future needs, including new metrics and data sources
  • Automated report generation to distribute to wider audiences

The risk of not doing data visualisation properly

Poorly built data visualisations are cumbersome to use, visually unappealing, and often show the user inaccurate data (for example, survey data without proper weights). If people don’t have good visualisations that show the data – and the story behind the data – they may struggle to make accurate, timely, data-led decisions.

But perhaps the biggest risk is that people simply won’t use data since visualisations aren’t visually appealing and easy to understand, even when there is good data behind them – which means you end up wasting much of the time and money you put into gathering, enriching, and visualising your data.

Best practices: Combining three key capabilities

Leading data visualisation providers have expertise in all three of these critical areas:

1. They have the required understanding of the business and business users, including:

  • Your industry across different clients
  • Different types of marketing data sets
  • Variety of end user personas, including their needs, challenges, and objectives

2. They have advanced technology capabilities, including:

  • Ability to create visualisations with automated reports (e.g. one click to download a spreadsheet with multiple tabs)
  • Flexibility to provide visualisations in your preferred technical environment using your infrastructure (including off-the-shelf platforms and custom technologies)
  • Experience in harmonisation and integration of complex data sources, formats, sizes, and types
  • Ability to render visualisations on mobile devices

3. They understand design thinking for storytelling, including:

  • The design thinking process (define, prototype, implement)
  • How to extract the most relevant data and metrics from large databases
  • The need for new stories, customised stories, pre-built stories, and analytical frameworks built around your needs
  • How to build empathetic designs and use the most effective visual design and storytelling techniques, including using the business user’s language (to help employees take ownership), and structuring data, visuals, navigation flows, and analytical frameworks around how your users and organisations make decisions

The Kantar difference

At Kantar, we create data visualisations that help marketing teams make better, smarter, faster decisions – in part because members of our team have been on the client side, so we understand what you need from your marketing data visualisations. Kantar’s specialists have a thorough understanding of the complexity and nuances of marketing data sets, and routinely handle every step of the data insights process – including data engineering with Olympus, our platform with built-in artificial intelligence and machine learning.  

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