What is data visualisation?
Data visualisation refers to the graphical or pictorial representation of data. It is not a new concept, as you can see in this Ted Talk from 2012. The beauty of data visualisation is that it helps us to make sense of information and find patterns in data.
Big data has been a keyword in online business for the last few years. However, these vast mounds of data have no use except to fill up valuable memory space, unless we can use it to discover more about how our business functions, the environment in which it operates and, of course, our existing and potential customers.
Data visualisation plays to the strengths of the human mind. Rather than trawling through spreadsheets of complex data, a chart or graph portraying the relevant variables is much easier for us to process. Suddenly, we can see areas that need improvement, obvious trends and outliers as well as predictions, pretty much instantaneously.
Data visualisation vs. data analytics
Data analytics is a very different beast to data visualisation. Analytics is the process of collecting the data and deciding what’s essential to the task at hand, whereas visualisation involves converting the analysed data into a digestible format.
Data analytics benefits a business by identifying underlying models and trends and helps to predict what the company requires to thrive. However, data analytics is also a fantastic resource that can be transformed into data visualisation. Google Analytics is a great tool to integrate with a data visualisation software package.
The core difference is that data visualisation emphasises the findings and displays them in customisable ways in order to get the most out of data analytics. Whereas analytics is all about gathering information, visualisation helps us to grasp complex concepts that arise out of this information, as well as communicating them efficiently.
Data analytics is broken down into three distinct parts:
- Descriptive analytics: focuses on past events as well as root causes
- Predictive analytics: used to make predictions about future events by using systems such as data mining, statistics and machine learning
- Prescriptive analytics: a combination of the first two components. It involves combining the information from both descriptive and predictive analytics to make savvy business decisions and drive profits.
Data visualisation is separated into:
- Static visualisations: this is a single-view snapshot that represents data in forms such as graphs and charts
- Interactive visualisations: chances are if you’ve been on the internet over the last three years you’ve come across an interactive chart. Here is an excellent example used to track tennis champion Roger Federer’s career. Not only is it very gripping, but it gives us much more information and context about the user than a regular chart would.
How does data visualisation software work?
Data visualisation software provides efficient and effective results when done right. What you need as a Shopify store owner is a package that can integrate with multiple platforms to display data reports. You need a panoramic view of what your business is doing, where it’s headed and whether it’s genuinely meeting targets.
From time to time, every business needs a wake up call - it can be far too easy to disregard negative figures and declining sales volumes. However, having a graph will outright show you that your sales are tanking, and fast, making it much harder to ignore the harsh reality.
Using a software that automates these graphs also means less time wasted creating them. It’s like having a switch that empowers you to turn your business strategy from reactive to proactive.
Why use data visualisation?
You can use data visualisation to improve your site’s SEO. What many online stores don’t master is a balanced link-distribution. Using data visualisation, you can instantly see which pages are under or over linked. You want balance across all your pages, excluding those that you deem most important. This might be a site’s landing page, which should score higher by setting up more natural links to it across your site.
Accuracy in CRM
Shopify store owners want to secure their customer profile. It’s all too easy to think of your customer profile as more of a marble statue rather than a reflection of your target market. People change - using data visualisation will show you when you are failing to connect with your market. Once that happens, you can begin taking actionable steps towards changing course and reconnecting with your target demographic.
Creating and implementing KPIs
Data visualisation prevents unrealistic targets. You’re not going to set a goal that looks like a big, fat outlier on a graph. It adds a sturdy realism to your business plans. Although you only need data analytics for KPI analysis, it’s a real shame to stop here. By setting up a data visualisation tool, you can instantly present this data, which gives you a much clearer picture on:
- Your store’s progress: are you behind or ahead of predictions?
- The distance from your goals: how far are you currently ahead or behind?
What forms can my data take?
I’ll keep this short and sweet by giving a few simple examples. You can also check out this sophisticated KPI dashboard that is possible with data visualisation here.
- Bar charts
- Pie charts
- Line graphs
- Bubble/radar chart.
What do you need to consider when selecting a data platform?
How many data sources are you drawing from? What is the size of the datasets?
Which of your team members will need to have the ability to create reports?
Some platforms can be fairly costly, depending on how many data connectors you require.
Maximise the integration of your store’s operations to get the best result out of your package. Here are a few common essentials for Shopify stores, however, your combination will be unique to your company:
- Google Adwords
- Google AdSense
What data visualisation tools do we recommend for Shopify?
A great way of thinking about Databox is as a package that places your team on the same page, but also pulls all your data onto that page. Its datawalls are second to none and give you that crystal clear overview of your company, also allowing for customisation if you’re tracking particular goals which you set within the software package.
Another great feature of Databox is its security. You can choose which data you want to share and give access to specific IP addresses and users. Check out their integrations here (this includes Shopify!) and see how streamlined your analysis process can become.
The key feature of Grow is the speed at which it operates. It tracks in real-time and provides warnings to prevent those end of month report surprises. There’s a lot of value to be gleaned from the historical snapshots which its competitors tend to neglect!
Another area where Grow stands out is that it's fully customisable- you can ask Grow to give you data representation at every possible angle. This makes the most of the asset that is your data. Again, Grow integrates with Shopify and over 150 other platforms, so your store’s direction is fuelled by intelligent, well-informed business decisions.
Ready to get started?
Need help choosing a data visualisation tool to integrate with your Shopify store? Get in touch with us - we're Shopify experts who can help you take your online store to the next level.