Whatever ecommerce niche you work in, different types of dashboards may help you simplify evaluating the performance of your online marketing initiatives. These can be both independent platforms and supplementary services. For example, Facebook offers online businesses the opportunity to connect online and offline marketing channels for their ecommerce projects in the In-Store menu.
In order to develop and further promote your website, you need a good analytics system. For some companies, this means having a simple counter which allows monitoring the number of website visitors over a certain period of time. Other companies need an all-encompassing set of tools that can track the efficiency of each cent invested in various types of marketing.
With respect to successful business development, implementing comprehensive analytics is the most reasonable and correct approach. “Cutting off” inefficient user acquisition channels and focusing your money on the effective ones provides a solid base for steady improvement in the company’s revenue and, consequently, the bottom line.
In this post, we compare the capabilities of Google Data Studio and Microsoft Power BI, the two popular integrated analytics systems. Keep reading to learn more about the differences between these two dashboard systems and see which system fits better for your business.
A dashboard is any type of user interface used to visualise data in a compact, easy-to-understand way. In fact, you use dashboards each time you look at your smartwatch, treadmill display, or your car’s speedometer. Dashboards have emerged as a synthesis between powerful mathematical analytics tools and graphical visualisation of the results.
Dashboards enable companies’ management to track the key performance indicators, trends, dependencies and other metrics in a convenient, compact form, as well as interactively modifies different parameters. In addition to graphics data visualisation, the main objectives achieved with the help of dashboards are tracking a particular indicator over time or evaluating it against other indicators.
A comprehensive analytics system involving dashboards also involves a number of dedicated tools and approaches to measuring website’s performance. Thereby, a company is able to track the entire customer journey across all interactions, starting with a website visit through any customer acquisition channel up to the target action, such as completing a purchase. End-to-end analytics enables businesses to measure the real value of their advertising investments and other traffic growth methods, as well as identify the most cost-efficient ways to promote a website with regard to the revenue they help generate.
Visually, an end-to-end analytics system could be presented in the following way:
Website visitors interact with a website in many ways. These can be filling out feedback forms, placing orders, communicating with the company’s manager via online chat or a regular phone call. All these interactions are tracked by the means of analytics, configured in a way that enables further end-to-end reporting.
Creating an end-to-end analytics system involves the following steps:
Each traffic source is analysed individually, which makes it possible to identify the best-performing channels and stop investing in the channels that fail to meet the goals you’ve set.
Any online business needs to regularly measure the efficiency of their digital marketing efforts. And it is almost impossible to do without the detailed efficiency analysis of each advertising channel and other traffic sources.
End-to-end analytics allows solving a number of business challenges:
End-to-end analytics can benefit, first of all, online stores of any scale that are using more than two marketing channels for customer acquisition. Having analytics tools properly configured and integrated with the website will also benefit service providers, including those engaged in information marketing and those organising seminars, coaching and training sessions.
End-to-end analytics will be less useful to web resources which use only one channel to promote themselves, as well as to industries dominated with offline advertising.
If the transaction cycle has at least 3-4 steps, a business will also need to integrate a CRM system providing information on all ongoing interactions with a customer.
There are commonly used free tools, such as Google Analytics, you can use to build end-to-end analytics for your business. However, these services alone wouldn’t allow you to record website visitors’ personal data so far, which limits your ability to get an “end-to-end”, 360-degree view of your marketing performance. To get a more objective and reliable data dashboard, you will need to simultaneously aggregate (i.e. combine) data from a number of different systems, including the advertising platforms and channels.
That’s exactly why there are services, such as Google Data Studio and Microsoft Power BI, developed specifically for these purposes. Below, we’ll take a closer look at the two services.
Both services are direct competitors, each with their own advantages and disadvantages.
Google Data Studio collects and visualises data from such services as Google Analytics (website analytics), Google Adwords (search and display ads statistics), Google Sheets (data tables), YouTube Analytics (video analytics), Attribution 360 (ad performance analytics) and Google BigQuery (big data).
Here’s how this works, schematically:
The main advantage of Google Data Studio is that this is free. The only thing needed to start using the service is to click the link and follow the step-by-step instructions.
Microsoft Power BI dashboard is an online platform that allows businesses to perform the whole complex of tasks on the aggregation of various types of data received from third-party sources. There are two options for using the service: an online service and a desktop version. The former can be used to perform monitoring, collecting and updating data, while the latter can serve as a constructor for creating reports in accordance with the specific business needs.
Both solutions for aggregating analytics data are easy to implement and use. It’s pretty obvious that each of the two was initially designed to work with heir “parenting” companies’ tools — Google and Microsoft products, respectively.
Google Data Studio dashboard has a number of ready-to-use data connectors, which makes it indispensable when it comes to integrations with AdWords and Google’s analytics systems. However, in terms of connectivity to various databases and CRM systems, the product is clearly inferior to its Microsoft counterpart, which has advanced technical capabilities, including the ability to integrate with various cloud-based solutions. The integration with the Azure products alone is already significant progress for large commercial companies. Another additional advantage would be Power BI’s greater flexibility of settings and the ability to display data from two or more independent sources in one visualisation object (a table, chart, or graph). Although recently Google Data Studio has made this possible, the labour costs are still far higher than for Microsoft Power BI.
In terms of speed of operation, simplicity and quick integrations, the Google product has a clear advantage over its peers. The need to create your own connector for Microsoft Power BI is a drawback since you’ll need a web analytics expert.
From the perspective of comprehensive analytics, the efficiency of a system largely depends on many parameters. Check if your ecommerce data is collected correctly, you’re tracking relevant metrics, you’ve set the right goals and monitor the right events and objects. The quality of your analysis also depends on your ability to measure any given characteristic, such as conversions, with the maximum accuracy possible.
Check out the table below comparing the two services.
As you can see, Google Data Studio is the best fit for small- and medium-scale ecommerce companies. Large-scale enterprises will benefit from Microsoft Power BI and its extensive technical capabilities for data aggregation that are superior to its Google counterpart.
Regardless of which service you choose, the objectivity and reliability of the information presented will mainly depend on the quality of settings in your data analytics tools, the correctness of data handling the accuracy of data processing, and to a lesser extent from the service itself.
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