Data on its own can be pretty useless until you give it the right shape – one that provides you with a 360-view of all the scattered entries you have. Spreadsheets and pie charts no longer do that trick. As data grows bigger, you need more sophisticated tools to uncover concealed stories buried deep inside your numbers.
Data visualisation can help your business digest large volumes of information at scale, identify new trends and patterns, and most importantly – reveal questions that would otherwise be overlooked.
Adhoc data visualisation
Depending on your goals, our team will choose the most suitable datasets for visualisation. Then we’ll transform them into elegant visual reports to share with your teams.
Ongoing data visualisation
Have our team on retainer to deliver fresh insights and visual reports to your company on a regular basis. Set up specific goals and reporting needs, and our data scientists will continually weed out actionable insights. Or challenge us with pressing questions, and we’ll deliver detailed answers within a variety of report templates and formats.
There are stories only your brand can tell and they are often hidden inside your data. We can resurface them and transform them into original research, creative marketing assets and data journalism stories. This is highly effective for extending your brand reach by creating an exciting buzz around your brand.
Data visualisation is the graphical representation of data to help you find meaning in it. Human beings are visually receptive and our brains are more attuned to seeing patterns in shapes than lists of numbers. Data visualisation allows us to understand the meaning behind the numbers and get valuable information faster. This is crucial as businesses handle growing quantities of data.
Data visualisation allows marketing teams to get greater value from large amounts of data. By working with an agency that specialises in data visualisation, you can make full use of big data to discover actionable insights that drive marketing success and business growth.
3D data visualisation incorporates the graphical sense of depth, breadth and height to representations of data. In some cases, 3D visualisations can provide greater contextual insights, such as mapping out comparative sales volumes across the nation over a period of time. In other cases, three-dimensional representations can make it harder to read insights so it’s important to understand where 3D rendering is beneficial and when it’s detrimental.
The most important data visualisation technique is capturing the right data, to begin with. Then, it’s a question of understanding how to showcase this data in the most effective way for your target audience (marketers, shareholders, customers, etc.). If your aim is to showcase insights, such as campaign performance to stakeholders, you may simply create static visualisations to communicate your key points. However, for analytical purposes, the challenge is creating interactive visualisations that allow users to compare, segment and work with the data in meaningful ways to extract real insights.
Big data visualisation specifies the process of representing large or multiple datasets. For example, the default website reporting in Search Console is one source of analytics insights but, once you pull this data into another platform and combine it with data from Google Analytics, Google Ads, public datasets (eg: ONS, the Met Office, etc.) you’re working with big data.