If you’re looking to make fast, impactful optimization decisions that drive business growth, your ability to effectively collect, analyze, and visualize data is becoming more and more important.
But powerful data analytics dashboards that provide meaningful, actionable insights don’t happen by accident.
There are a lot of different aspects to consider to ensure your data is accurate, consistent, and visualized in a way that meets your decision-making needs.
In this guide, we’ll discuss the key areas you’ll need to be aware of to generate powerful data analytics and marketing insights.
Whether you're a seasoned marketer looking to optimize your cross-channel strategy, or a beginner seeking to understand the best practices for data analytics and data visualization, this guide has something for you.
One of the first key steps in getting started with a data integration platform is deciding which data you want to consolidate into your Single Source of Truth.
Examples of traditional structured data might initially come to mind - which is easily measurable data such as impressions, clicks, costs, sales, revenue, and CPA.
This structured data can easily be extracted, transformed, and standardized for accurate analysis within your SSoT.
But this approach would miss the opportunity presented by big data.
Big data analytics goes a step beyond the analysis of structured data and involves the consolidation of semi-structured and unstructured data as well - unlocking the hidden insights that exist within your business emails, videos, social media comments and customer reviews.
Big data analytics also introduces the potential for analysis using machine learning and AI tools with the predictive analytics capabilities they bring.
Unlocking the power of your big data insights can provide a range of benefits, including a better understanding of customers, the ability to optimize marketing campaigns more effectively, and the capability to predict future trends.
If you’ve been using the phrases “data analytics” and “data insights” interchangeably - you’re not on your own.
But although these two terms are closely related, they actually have distinct meanings.
Data analytics relates to the process of analyzing your business data to help uncover key information, patterns, correlations, and trends.
Data insights, on the other hand, relate to the conclusions you’re able to draw from the analyzed data - which ultimately help to guide your decision-making.
For example, your data analytics might show that there has been an increase in website visits from a particular state in the USA.
If you investigated this further and found that there was no increase in organic traffic in that state, and no increase in paid search traffic either. You discover that the traffic uplift has all come from social media - specifically a shared post in a local group on Facebook. This is a data insight that you’re able to take action from, such as looking at the potential for similar opportunities in other states.
But for your data to answer the questions you’re asking of it and turn your analytics into valuable insights, you need to make sure your data is consistent, accurate, and standardized.
Data visualization is a key tool for marketers looking to gain valuable insights from data.
It helps turn complex marketing data into visual charts and graphs, enabling you to identify trends, patterns, and outliers more quickly.
Effective data visualization can also make it easier for anyone in your business to understand your data - leading to increased collaboration, improved engagement, and a better business-wide understanding of marketing performance.
However, creating impactful visualizations requires more than just loading data into a chart. It needs careful thought.
To truly unlock the power of data visualization, it’s important to avoid the common mistakes that can undermine the accuracy and value of your visualizations - including common issues such as:
Overloading a visualization with too much information can confuse the viewer and obscure the key insights you're trying to convey.
Choosing the wrong type of chart can misrepresent the data, making it difficult for your audience to understand the intended message.
If your visuals don't align with the knowledge level and interests of your target audience, they may miss the insights or find the information irrelevant.
Distorting or mislabeling data can lead to inaccurate interpretations and potentially damage trust in your analysis.
Poor use of color can make visuals hard to read, leading to misinterpretation and confusion among your audience.
Using incorrect or inconsistent data for your visualizations can lead to misleading conclusions and poor decision-making.
Once you have an understanding of the common mistakes to avoid - you can start implementing specific techniques to enhance the analysis and insights from your marketing data.
This process starts with a thorough understanding of your audience and their level of expertise so you can tailor your visualizations based on their needs.
The next step is to choose the most effective chart type based on the questions you want your dashboards and visualizations to answer, and making sure your scales and axes are clear for ease of understanding.
Another important technique is prioritizing simplicity —focusing on key metrics and KPIs only and making sure the flow of your dashboard is logical and tells a story.
Find out more about visualization techniques in our detailed guide.
The right data visualizations can make your data more engaging, lead to faster, more effective analysis, improve collaboration, and make the lives of your marketing team much easier.
But even the most visually appealing, well-designed dashboard will fail to deliver accurate insights if it's powered by incomplete, inconsistent, or erroneous data.
It’s important to take a thorough, methodical approach to preparing your data for an efficient dashboard.
The process starts by defining clear objectives and identifying the right metrics for your target audience to make decisions.
For example, a branding focused social media dashboard might want to focus on metrics like impressions and post likes, whereas a performance marketing dashboard will be more likely to include CTR and ROI metrics.
Having identified the key metrics you want to be pulling through into your dashboards, it’s important to ensure the quality, consistency, and freshness of the data you’re going to use to power them.
This is where a data integration platform can be instrumental in helping prepare your data for visualization through:
Automatically extracting, transforming, and standardizing data from your different marketing sources.
Ensuring the accuracy of your data through anomaly detection.
Maintaining consistency in data formats and metrics across channels.
Scaling your data integration processes as your business grows and evolves.
We’ve already established that data visualization and marketing dashboards are essential for turning data into actionable insights.
However, many businesses fall into common traps that undermine the value and impact of their dashboards.
By understanding these traps and implementing best practices, you can create dashboards that are clear, concise, and compelling - delivering the insights your team needs to make smarter, faster decisions.
If you’re following our best practice tips so far and taking note of the common marketing dashboard mistakes - you’ll already know how important it is to tailor your reports and dashboards to include the metrics that are most useful to the audience.
But with so many different marketing metrics to choose from, it can still be challenging to understand which KPIs are going to be most valuable to measure and analyze.
Certain stakeholders might favor engagement metrics and video view time, whereas others will only be interested in the ‘harder’ metrics like sales and revenue.
To help you navigate this task, we’ve put together a detailed guide on the most important marketing metrics to consider when you’re preparing your marketing reports.
It’s important to understand that not all marketing analytics platforms are created equal.
Each solution has its own advantages and drawbacks, and it’s important to choose the solution that best meets the specific needs of your business.
One of the most important factors to consider is the platform's visualization and reporting capabilities, as you want to make sure the options available are suitable for your business needs.
It’s also advisable to check on the scalability of the platform. You don’t want to be choosing a data analytics platform that is suitable for your business today, but isn’t able to process the larger amounts of data you might be generating in 12 or 24 months' time.
Collaboration and sharing functionality is another common factor that many businesses look for. This allows a visualization or report that you build to be easily shared with other stakeholders across the business. Some platforms even allow comments and discussions on reports to further aid transparency and engagement.
Depending on your internal technical knowledge, you might also want to factor in the level of customer support available to help you get the most out of the platform.
When it comes to the visualization and reporting features in a marketing analytics tool - how do you know which solution is going to be right for your needs?
To provide a quick top-level overview, marketing analytics tools can be divided into two main categories: Business intelligence (BI) platforms and data visualization platforms.
Business intelligence tools are best for presenting business data in a tabular format, although many established BI tools now also incorporate impressive data visualization features.
Data visualization tools, on the other hand, excel at presenting data visually and are ideal for businesses that want to prioritize visual storytelling with their data.
The right choice of platform will likely depend on your specific data analysis needs - whether you're looking for deep analytical capabilities, impressive visual dashboards, or the ability to integrate your analysis into custom applications and business tools.
There are dozens of different analytics platforms available, but four of the most popular include:
A business intelligence platform by Microsoft that enables users to create interactive visualizations, reports, and dashboards. One of the key benefits is its integration with other Microsoft products. |
A leading data visualization platform that allows users to create impressive interactive data dashboards using a drag-and-drop interface. It is great at processing and visualizing large, complex data sets. |
A business intelligence platform owned by Google that provides an intuitive interface for users to create interactive dashboards. The collaboration features are impressive, and it integrates well with the Google Workspace ecosystem.
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While not technically a data analytics platform, Snowflake enables businesses to build custom analytics applications and leverage machine learning and AI for deeper insights from their data. |
The launch of Chat GPT in November 2022 has really brought the topic of AI and machine learning into mainstream marketing.
If you’re like many businesses, you’ve probably already been experimenting with generative AI and exploring ways to use AI to improve, enhance, and streamline your day-to-day marketing operations.
However, it’s also important to note that AI is significantly shaping the world of data analytics
By understanding patterns in historical data, AI can identify any anomalies in data that might reduce the quality or accuracy of your Single Source of Truth.
The ability for AI to process vast amounts of data quickly also paves the way for faster access to insights, which is essential for gaining a competitive edge.
Machine learning can additionally unlock hidden insights that exist in your unstructured data, providing deeper insights into customer sentiment and opinions to help shape your marketing strategies.
But from a marketing growth perspective, perhaps the most exciting aspect of AI in data analytics is the ability for predictive analytics and ‘what if’ analysis - helping marketers understand the probability of outcomes with different market variables.
This type of analysis promises to be a bit of a game changer in how marketing teams approach analysis, and plan for the future to achieve business growth.
In today's marketing landscape, data analytics and insights are essential for making informed decisions and driving business growth.
However, many marketing teams face challenges that can undermine the quality of their insights - such as being overwhelmed with data, operating in data silos, or working with inaccurate or inconsistent data.
No matter how good your analytics tool is, if you don’t have the right foundation of consistent, high-quality data - your insights are going to be flawed.
As a data integration platform specifically designed for marketers, Adverity can help you:
Our platform streamlines the data integration process, giving you the confidence and peace of mind that the most accurate and up-to-date data will always power your marketing dashboards and reports.
Ready to see what Adverity can do for you? Book a demo today.