Sometimes it feels like there are way too many buzzwords and industry terms to keep up with. As the software industry continues to grow and advance, more new concepts and trends are added to the fray. And the problem compounding all of this is that many of them sound incredibly similar.
Case in point: think about how many types of “analytics” are out there. There’s data analytics, diagnostic analytics, predictive analytics, descriptive analytics, prescriptive analytics (don’t even get us started on the fact that those three rhyme), web analytics and business analytics, just to name a few. Aside from simply knowing the names, do you know exactly what each is, and what differentiates them all?
We’ve already covered predictive, descriptive and prescriptive analytics before, so today we’ll pit web analytics vs business analytics to discover the differences between them. Now the next time you’re discussing analytics, you’ll know exactly what you’re talking about (when it comes to these two, at least).
Both web analytics and business analytics help businesses optimize their data-driven decision-making. But the biggest difference between the two lies in which data-driven decisions are made, based on the analysis. Web analytics — which analyzes your website data — aims to improve your web presence. Mainly, this means increasing your overall web traffic, including the number of visitors, total visits and page views.
Additionally, web analytics helps optimize your website’s performance. After all, what’s the point of a highly-trafficked website if it doesn’t help the bottom line? To maximize the effectiveness of your website, you need to make sure that it helps increase your customer base by finding new leads. For example, making sure that your calls to action (CTAs) are effective is one key strategy. Web analytics can deliver data, such as conversion rates, that you can use to improve your CTAs, so you’re generating as many leads as possible.
While web analytics focuses on improving your website, business analytics help improve your entire business. There’s almost no limit to what you can use business analytics for. Using Big Data, it helps you dive into the data related to your business processes, your customers, your employees and more.
Similarly to business intelligence (BI), business analytics helps you predict future outcomes and performance. It helps by creating reports and predictive models from your data, which reveal valuable insights. These reports are great for finding trends, while predictive models help you prepare for the future.
As you probably know, data is the most important component of analytics. Without it, you can’t perform any analysis. This makes up one of the biggest differences between web analytics and business analytics: the type of data analyzed.
Web analytics, as we mentioned earlier, analyzes data from your website, including data related to your users, your site visitors, site visits, page views and other web metrics. This means that the data it analyzes is very focused and narrow, related exclusively to your website. After developing key performance indicators (KPIs), such as the number of monthly site visitors or CTA conversion rates, you can use web analytics to discover whether or not you achieved those KPIs.
Business analytics, on the other hand, analyzes all of the data that you have. Any kind of data, from how many hours each employee works to your monthly product sales to inventory information, falls under business analytics. Boosting more than just your marketing, business analytics helps turn your entire company into an efficient, data-driven business.
Business analytics also involves more robust, in-depth analysis. Using techniques like statistical analysis and quantitative analysis provide insights into why you experienced a particular result. For example, it could find a correlation between excessive time off being taken by warehouse employees and a higher amount of late shipments (we know this is a very basic analysis, but you get the idea). You can then use that information to implement changes and conduct A/B tests if necessary. Finally, using predictive modeling, you can forecast future results that you can use while planning for the future.
Last but not least, we come to the final difference between web analytics and business analytics: the type of software used. Web analytics involves more simple analysis than business analytics. Therefore, the software you use for it doesn’t need to be particularly robust. Typically, the main features of web analytics tools include data collection and reporting. Google Analytics, the most popular web analytics tool, doesn’t create sophisticated predictive models (at least not yet), but you don’t need it to. You just need to be able to see the data on your web traffic, page views, page referrals, etc and view the trends in a report.
If you want predictive modeling of your web analytics data, however, you can use business analytics software. The data analysis performed by business analytics is much more detailed and sophisticated, so it needs more robust software than web analytics. Good predictive analytics aren’t easy, you know.
Business analytics software needs to be able to do so much more than collect, store and report on data. It needs to be able to create predictive models, while continually updating those models as it collects more and more data. Plus, it needs to be able to aid in data mining, so you can extract every possible insight from your data. Tools like SAS Business Analytics, Dundas BI and the SAP Business Analytics Suite help you do just that.
Once they’re broken down, the different types of analytics aren’t all that difficult to understand. To recap, web analytics involves the collection and analysis of your website data, with the goal of improving its performance. Business analytics involves the collection and deep analysis of any type of data that your business collects. And while both types of analytics contribute to a better data-driven decision-making process, they each require their own unique type of software.
Now get out there and start discussing analytics with confidence!