Avoid these data visualization errors

One of the best ways to present complex business data and reports is visualization. Good data visualization can significantly help users to take in a vast amount of information in a short period of time. But of course, not everyone is a data visualization expert, which is why much of the visual content we see nowadays is often ineffective and jam-packed with information. If you’re looking to create great data visualization that appeals to readers, make sure to avoid these data visualization pitfalls.

Inconsistent visualizations

It’s important to be consistent when presenting your data, otherwise users will have to stop and figure out how to read each new picture before they can comprehend what it says, wasting time and defeating the purpose of data visualization. Luckily, there are some best practices you can follow. For instance, try choosing colors that go well together. Use only 2-3 colors at most throughout your visualization – any more and you’ll find that your pictures might be hard to read. Also, use the same iconography and typography in each picture so your audience can quickly understand the information.

Displaying too much data

Overly complicated data visualizations are sure to turn off most audiences because they can’t figure out where and what to focus on. Your customers, colleagues, and employers want specific, relevant answers. The quicker you can deliver those answers, the better. Irrelevant data gives your presentation a cluttered look, making finding relevant information more difficult for readers. The solution? Find a compromise between showing too much data and not showing enough overall. Use good judgement.

Oversimplifying data

The purpose of data visualization is to present data in a way that’s easy to understand. While it’s all too easy to simplify data, if you go too far and leave out crucial parts, your audiences won’t be able to see or grasp the main point of the presentation. Instead of trying to oversimplify data, it’s better to include all important criteria and organize them into a structure so audiences can easily understand what’s being presented to them.

Choosing the wrong visualization

This is one of the most common mistakes made in data visualization. There are many different types of data out there, and each of those types require different analytics and tools to use. For example, if you want to present a sales growth comparison in the last 5 years, it’s better to use bar charts that can clearly show the difference at a glance. If you want to show a relationship between two metrics, on the other hand, you should use a scatter chart to show results.

The best way to avoid all these errors is to focus on your goals first. It’s likely that you’ll have to make changes along the way, which is actually a good thing, because it will make your presentation more accurate and effective.

Want to learn more about other business intelligence tools to implement in your company? Give us a call today.

Published with permission from TechAdvisory.org. Source.

Common BI mistakes businesses make

Clued-up companies rely on business intelligence (BI) in order to make informed decisions regarding their future. Yet even though businesses invest in BI, they often make mistakes resulting from a lack of knowledge about how best to implement it, and can end up losing more than they can afford. Here is a round-up of common BI mistakes encountered by businesses, and how you can avoid them.

Mistake #1: Not defining business problems

One of the biggest mistakes in BI implementation is jumping to conclusions too soon without first identifying what your business wants to accomplish. When it comes to integrating BI into business operations, there’s no such thing as a one-size-fits-all solution. Looking for a single BI tool to solve all analytics problems is one of the main reasons many BI projects fail.

You need to clearly define the business problem you’re trying to solve, and understand the specific tools required to solve those problems. Only then will you be able to select and purchase the BI tool that best suits your needs.

Mistake #2: Not getting buy-in from end users

Even the best BI tools are ineffective if they’re not properly utilized. Forcing your employees to use newly purchased BI technology without informing them or hearing their thoughts beforehand is a big mistake.

Instead of telling employees they have to use something, first focus on highlighting the benefits of the new BI system. Help employees understand why they’ll want to use it, and convince them by showing them what they stand to gain from the new BI technology.

Mistake #3: Rushing implementation

A rushed deployment of new technology is often times not a successful one. When it comes to deploying BI solutions, patience is key. If you hurry into BI implementation too quickly, your end users may not have enough time to develop the skills required to use the software effectively.

Take an incremental approach to implementing BI solutions. Make a list identifying business problems and, rather than expecting to solve every business problem all at once, try to prioritize specific outcomes you want to achieve. When you have solved the first issue, move on to the next one and so on until you have incrementally solved all the problems on the list.

Mistake #4: Insufficient training

New BI systems are complex structures that require a lot of training in order for users to make the most of them. If users lack the skills necessary to operate the software, then bottlenecks can occur. The product may be left dormant for long periods of time as users wait for experienced IT staff to resolve teething problems.

Spend wisely on providing ongoing training, so that users really understand how to use the system. Consider hosting weekly lunch sessions where a different aspect of the BI system is discussed. You could also provide online training videos that enable users to learn more about the new system at their own pace.

Mistake #5: Not making use of information and reports

BI tools are designed to analyze raw data and turn it into valuable information that can be used in business decision making. But some organizations fail to exploit the information fully – it is not shared, not analyzed, and not acted on. BI software can generate reports on various data points, identify risks, and predict trends. It’s important to leverage the information gathered and to apply it to your business’s objectives and goals.

Business intelligence software is a highly useful tool that, when used properly, can drive your business forward. Avoid these mistakes in order to make the most of your BI solutions. If you’re looking to implement BI tools to your company, contact our experienced consultants today and see how we can help.

Published with permission from TechAdvisory.org. Source.

A metric more important than website traffic

Are you getting a large amount of traffic to your site but not seeing a corresponding match in product or service sales? This is a head-scratching dilemma that many small business owners will face at one time or another. The reason behind it can be summed up in one word: engagement. A high amount of visitors doesn’t necessarily translate into engaged customers. Here’s how you can use Google Analytics to change that.

How do you measure engagement?

Just because a page receives a large amount of traffic, doesn’t mean it has quality content on it that visitors value. Half of the visitors to your most trafficked blog post or service page can easily bounce within seconds. So to figure out which pages your customers like, you need to measure engagement. And the easiest way to do that is by looking at the amount of time a visitor spends on a page.

Generally speaking, if a visitor is on a page for five minutes or more, they’re likely reading, watching or listening to some form of content you posted. Of course there’s the off chance that maybe he or she took an extended bathroom break after landing on your page or forgot to close it and continued surfing the web in another window. But if a consistent number of visitors are spending several minutes on a given page, you can feel confident that most of them are engaging with the content.

Why does engagement matter?

Simple. The more your visitors engage with your content, the more likely they’ll visit your website again or – even better – become a loyal customer.

You can measure engagement by following these four steps in Google Analytics:

1. Track engagement over a long period of time

We’re not just talking a month or two, but more like years. This will show you which pages are performing best in the long run. To do this, open Google Analytics. Then in the top right corner of the screen, input your date range and then click Apply.

2. Measure all pages

You need to look at time spent on all your pages to see what’s performing best. In the navigation bar to the left of your screen, click on the following in the order below:

  1. Behavior
  2. Site Content
  3. All Pages

3. Compare the average time visitors spend on a page

Under the main graph that displays visitor numbers to your site, you’ll see a search box with the word “advanced” next to it. To the right of that, you’ll see five buttons. Click on the second button from the right – the Comparison button. To be sure you’re clicking on the correct one, hover your mouse over it and the word “comparison” will pop up.

Slightly below the comparison button and to the left, choose Average time on page as your secondary metric.

4. Mind the Green bars

After you’ve followed the above steps, green bars will appear to the right of some of the pages displayed. The higher the bar, the greater amount of time a visitor is spending on a page.

With this data at your disposal, now you can understand what content your customers find valuable – and then focus on creating more of it.

Want to know more about how to gain valuable insights from your business data? Give us a call today.

Published with permission from TechAdvisory.org. Source.