Monthly Archives: February 2015

Deciding How to Represent Website Data – Part 2: Segmenting Aggregate Data

Web analytics guru Avinash Kaushik famously wrote that all data in aggregate is “crap”. Time on site. All visits. Total revenue. None of it tells a good story. As Avinash says, the only way to get insight from data is to segment it into parts.
For example, it is mildly useful to know a website receives 15,000 Sessions (visits) per month. That aggregate metric gives you a rough idea of the scale, however, not much else. If you knew that over 50% of those Sessions came from Organic Search, then you’d start to get some insight into what makes the website tick. Clearly, content marketing and SEO are an important part of the story for such a website.
Breaking down Sessions by Acquisition Channel (e.g., Organic Search, Referral, Social, etc) is an example of how we can start segmenting aggregate data – Avinash’s recommended path to enlightenment.
But once you are enlightened, how do you communicate those insights to others? Using the right data visualization helps.
In Part 1 of our series on representing website data, we looked at different ways to visualize time-series web analytics data. In this, the second part of a three-part series, we look at aggregate data for fixed periods of time – how to segment it and how to best represent the segmented data to communicate your insights.

Blog Image Representing Data

 

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Combining YouTube Analytics with Google Analytics for Better Video Marketing

If video makes up any part of your marketing strategy, whether for your own company or for that of a client, it’s very likely you’re using YouTube. And if you’re using YouTube, you’re likely to be promoting your video content in a number of different ways – marketing it directly on the video platform, embedding videos onto your site and even using Google AdWords for video to specifically promote your videos to those in your target demographics.
Google Analytics provides metrics on the traffic that clicked through to your website from YouTube, but what about those other users? What about people who may have engaged with your content on YouTube, but didn’t visit your site?
YouTube Analytics can provide data on those people, helping you see beyond the information you get in Google Analytics. Even if you’re not seeing many people coming from YouTube directly to your website, they still may be engaging with content on your YouTube channel or watching embedded videos on your site.
YouTube offers powerful analytics for each video you publish, showing detailed information including viewer demographics, how long they watched a video, and where they watched it.
In this post well show how to tap into your YouTube Analytics and use that data together with Google Analytics to get a more complete picture of your audience.

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Deciding How to Represent Website Data – Part 1: Bar Graphs, Line Charts, Tables

Some people have really strong opinions about charts – or more specifically, about data visualization. Pie charts seem to get folks particularly riled up. In fact, Steve Fenton declared there are many, many reasons to despise pie charts. On the other hand, Bruce Gabrielle maintains those who cry for the death of pie charts are flat out wrong. He argues pie charts deserve your respect.
While I’m not going to weigh in on the great pie-chart debate, I do believe selecting the right data visualization tool for the job is important when creating digital marketing reports.
It is important because, for your analytics insights to have an impact, they must first be understood. Whether your audience is a client, your boss, or your internal marketing department, selecting the right chart will help you communicate the data more effectively.
This is the first post in a three-part series where we will break out common analytics reporting situations and identify the best approaches to representing the data (yes, sometimes it may even be a pie chart).
Part I of this series looks at how to visualize time series data. Part II examines segmenting data for a single time period. Part III looks at how to best present data to compare performance across time periods.

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Combining Google Analytics with Facebook Insights for Better Marketing

You may already know that Facebook Insights can provide you with demographic data about the people who like and engage with your page. But did you know you can use Google Analytics to compare that data with insights about the people who actually click through to your website?
Did you just get really excited? Us, too.
Informing Google Analytics with Facebook Insights allows you to refine messaging and ad targeting to more strategically reach the people who are most likely to engage with your brand. So, what data can you see about your audience in Facebook Insights, and how can you connect this data to the people who come to your website? We’ll walk you through it below.

Blog Image Combine Facebook Insights with Google Analytics

 

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Building an Ecommerce Report in Megalytic

You need to produce a report showing your website’s Ecommerce performance. As long as you have Ecommerce tracking set up in Google Analytics, you’ll have transaction and product data showing up in your account. But, how do you use that data to pull a report together, the kind of report that tracks not only the revenue earned on the website but where that revenue is coming from?
You could cut and paste from Google Analytics. Or, you could export data from Google Analytics to Excel, build your own charts and tables, and pull everything together into a report in MS Word. But, that’s a lot of tedious work. And then, you’ll just have to do it all over again next month.
Luckily, Megalytic allows you to put together Ecommerce reports quickly and easily using widgets specifically designed for Ecommerce reporting. And once the report is created, you can easily keep it up to date each month with just a few clicks.
Go ahead, breathe that sigh of relief.
In this post, we explore the Ecommerce widgets in Megalytic and show how you can use them to construct a report.

Ecommerce Reports with Megalytic

 

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