Data analytics is more than just a collection of graphs on a computer. By utilising the extraordinary power of big data, analytics platforms are able to turn actions into insights, helping businesses cut costs, increase efficiencies and improve the power of their digital marketing campaigns.
But what are the elements of a good analytics dashboard, and what should marketers consider when designing one?
A good dashboard isn’t just a dashboard
Success for a marketing intelligence dashboard comes from the insights it uncovers, but getting to that point takes some work. When I’m talking with clients about their data, first we start with getting clear on what they are solving for – why have they turned to digital marketing? What problem are they trying to solve?
It’s easy to get distracted in analytics by answering just one or two simple questions, like what channels generate the most leads. But that’s only one problem out of what is likely to be many. A good dashboard must be able to answer a variety of questions that dig deep into the results and support the business’ overall objectives. Starting at those business basics – what do we do, and why – can help you get to that point.
A good dashboard is able to answer a variety of questions that dig deep into the results and support the business’ overall objectives.
To put it in context: Say an organisation turns to marketing to increase the value of existing customers and attract new ones. Already, knowing this is our objective lets us start to build a dash that supports those outcomes. Then, we can drill down into channels, then into campaigns or any other layer we need to view. We’re not just thinking about surface-level problems, we’re going deeper and looking for insights that support our purpose.
- Read more: How to spring clean your customer data
How to choose from all the various BI solutions
Business intelligence (BI) is a multi-billion dollar industry, with lots of players on the market. So how do you choose between them?
The major players – SAS, Microsoft Power BI, Tableau, Datorama, Google Data Studio, Domo, and so on – may appear to perform similar functions at face value, so comparing feature for feature can be tricky. What’s often more important for digital marketers, especially those new to BI, is finding a platform that works specifically for their needs.
Marketers should look for a platform that is designed to visualise the data that they most rely upon. A tool that is pre-built for marketing data, such as from Facebook or Google Ads, will likely be far easier to use than a more agnostic BI system, which may require extensive setup to bring it into the marketing context.
Some questions to ask:
- How quickly can you access the data most useful to you?
- How easy is it to plug in the marketing tools you use?
- How simple is the process of visualising the insights from these tools and, more importantly, compare them against each other (see below for more on this)?
Common dashboarding challenges, and how to overcome them
Meaningful insights don’t come easy; unfortunately, data doesn’t always magically fall into place, even with the best BI platform. That creates a few key challenges that must (and can!) be overcome early on in the setup process if marketers are to get the most out of their dashboard.
1. Data that doesn’t work together
Different tools gather data differently, often using a different language. This can make comparing their insights tricky, as it may not be clear which insights from one platform relate to or impact the insights from another.
Data harmonisation. Harmonising data is about translating each of the different ‘languages’ I mentioned into a single view. While different tools talk differently, the reality is at some point they are going to mean the same thing – impressions, clicks, conversions, leads generated and so on. By taking the time to sync up platforms by identifying these overlapping areas, we can bring together data from all our tools into a dashboard that is quick and easy to use.
- Example: Using similar naming conventions across platforms is one way to help harmonise different advertising tools. For instance, naming each and every campaign with the same template (objective – audience group – advertising medium – creative name) lets you quickly compare how different platforms stack up against each other. With this template, you would be able to filter by objectives, audience groups, advertising mediums (e.g. video ads, search ads) and the creative used in each campaign and collect this information into a unified view, where you can determine, say, which mediums are the most cost effective for a particular audience.
2. Data that sits in different silos
Merging data from disparate silos has to be one of the most common challenges of marketing analytics. If Facebook sits in this database but Google Ads sits over here, email results are over there, and none of it talks to the sales data, all of this extraordinary information can’t really be used. Not effectively, anyway.
Marketers must collect all of their data across systems into a single database – a central truth. This is where choosing the right BI platforms comes in again, as the right tool will be able to plug into all of these different silos and collect the required information to be analysed and produced as a visualised report.
3. Insights you can’t trust
Data accuracy is vital to acting on insights, but there’s a common theme among marketers that they feel like they can’t trust their reports. There are so many technical variables involved in establishing a good dashboard, it may seem like the numbers simply aren’t true – especially if they are quite different to expectations.
A simple solution here is to audit the dashboard to ensure it has been set up correctly. This can be done quickly by comparing the metrics that appear on the dash with the metrics that appear when viewed in their native platform (i.e. Facebook). If they match, then the dashboard passes the accuracy test. If not, something may not have been plugged in properly and requires a second look.
Education plays a crucial role here, too; given some of the biggest sources of marketing data apply their own, different attribution algorithms, it can be hard to compare oranges to oranges. As such, I lean towards trusting empirical sources of data such as from e-commerce or CRM. If these data sources aren’t available to you, you might expect to look for trends from the reporting rather than absolute numbers.
Harmonising data will also help here, as the process of setting up and utilising techniques such as naming conventions can control the data that makes its way to the dashboard, and therefore improve its usefulness.
4. A lack of actionable insights
Setting up a dashboard is one thing – reading it is another. Even with simple visualisations and easy filtering, analysing data is not always easy. After all, an entire industry has been built around this skillset, and not everyone is going to be qualified. This investigative complexity can at times make generating actionable insights beyond that surface level we talked about earlier a little intimidating.
Here we come again to finding a solution designed around your digital marketing. A platform built with marketers in mind will make it as simple as possible to generate deep insights about the tools and processes relied upon by their teams.
Even better, look for a platform that actively helps find these insights, either through support teams, auto-generated tips and tricks, or even better, an AI helper. For example, Salesforce’s Einstein AI can be used within Datorama to parse through old campaigns and use cases of high- and low-performing metrics to find ways to optimise future activities. This can be done at the click of a few buttons, as the bot has been set up to make its use easy even for newer users.
Bringing it all together
You get out what you put into data analytics. By taking the time to align your dashboard to core marketing objectives, collecting and harmonising disparate data sources, and then auditing the platform to ensure accuracy, you can start to dig through the information and produce real, actionable insights.