I like using spark lines data viz when it makes sense! It’s a great way to visualize trends in the data without taking too much space. Now, I knew how to add sparklines in Excel but recently, I wanted to use that on Google sheet and I had to figure it out so here are my notes:
1. Google has an inbuilt function called “SPARKLINE” to do this.
2. Sample usage: =SPARKLINE(B2:G2) — by default you can put line chart in your cells.
4. One of the best practices that I advocate when you spark-line to “compare” trends is to make sure that you have the consistent axis definition. So the sample usage for that could like this:
you want to create a funnel chart of how your new users move from their landing page to your desired destination. Ideally it’s goes something like this:
Stage 1) lands on your home/landing page
Stage 2) goes to a product page
stage 3) goes to a checkout page
stage 4) sees a thank you page
Now, if you want to analyze the conversion among these stages for a “new” user then you will need create custom reports in google analytics. You will basically need to create a report for each specific page that you want to analyze. So how to set one up?
Solution:
1) Navigate to Google analytics profile
2) On the top of the go to “customization” section and click on create a new custom report
3) here’s how you can set up a custom report that will use you new users by a specific page (notice the page filter?).
Conclusion:
In this post, I outlined the steps that you need to take to setup a custom report in google analytics that shows you new users by specific pages.
WordPress recently did a good series on how to analyze the data that’s available to you via WordPress Blog Stats tool. This series is great if you’ve a WordPress.com blog PLUS it’s a good read for any one in the data analytics role to learn how to write-up content like this.
Along with WordPress Stats, I also use data from the Google Webmaster Tools. It’s a great way to see Keywords, Top posts & pages from a search engine point of view. It’s always good to have a healthy number of people searching for your content on search engines like Google.
I hope you take a look at how Data Analytics can help your Blog Grow. The series that WordPress ran focused on their platform but if you run your blog on other platform, this should give you a good sense of how to analyze the blog statistics.
I’ve been using Google Alerts for more than a year now and I thought I’ll talk about how it helps me keep track of who is talking about XYZ on the web. here XYZ could be a brand, your full name, your competitor’s name, your company name among other things.
So why should you care?
Well, whether you know it or not, someone out there is talking about your brand, about YOU or about your company. you can’t control that – but what you can do is to “Monitor” it. Keep an eye out on what people are talking about YOU or your brand on the internet. That way, you get to stay current w/ the conversations about things that matter to you.
And If you’re a blogger then you can set up an alert for when your blog gets found (a.k.a indexed) by Google – nice! right?
In this post, I’ll share how I learned to track an email campaign via Google Analytics.
First up, what do I mean by email campaign?
let’s say you email 1000 newsletter subscribers a link (URL) along w/ a summary – How do you track the traffic that is generated via this email campaign? Well – that’s where Google analytics can help you track your email campaigns. One metric would be how may people clicked on that link and visited your site.
Why should I care?
“If you can’t measure it, you can’t manage it” – Peter Drucker
If you do not measure what’s working or what’s not working, then you can’t improve – can you? Let’s take a hypothetical example. supposing it’s cost you $25 dollars to email 1000 people. How do you calculate the ROI on it? Well – track it! And the tool you can consider using is Google Analytics.
Now, Here are the steps to track an email campaign via Google Analytics:
Here’s the visual:
Here are the steps:
1. First Step is to create an URL.
Why do you need this? Basically this URL would have “meta data” that helps Google Analytics identify this link belongs to one of the campaigns.
I like exploring data sets to find interesting patterns from them. To that end, I was exploring a data-set: List of companies by revenue and I added a column to calculate Revenue/Employee to explore the dataset:
I was going through the list of largest IT companies in the world. And I thought, it would be great to see it visually! so here it goes:
[created using Power View in Excel 2013)
Configuration of Scatter Plot:
Some of observations:
– Foxconn has low revenue/employee ratio (I guess, it’s because they must be employing a lot of workers for their electronic manufacturing plant at low cost)
– Samsung is ranked number 1 and Apple is ranked 2. But apple has better revenue/employee ratio. Also Apple’s market cap (represented by Size of bubble) is greater then that of Samsung
– there’s a cluster that comprises of MS. Google, Amazon.. etc Also one more cluster of HP, Panasonic and IBM
Data Collection limit: You should not send more than 10 million hits per month. If you exceed this limit, there is no assurance that the excess hits will be processed. Data Freshness limit: Sending more than 200,000 visits per day to Google Analytics will result in your reports being refreshed only once per day
And to take it further, I wanted to know how many website in USA get greater than 10 million hits per month, turns out only 108 websites in US get that much traffic. Source: http://www.quantcast.com/top-sites/US?jump-to=108
so from data collection limit standpoint, only these 100 odd sites would exceed the limitations of Google Analytics.
To put things in Perspective: MySpace.com does not exceed Data Collection Google Analytics Limit:
Conclusion
Just knowing about the Data Collection Limit was not interesting but I combined data from other data sources – it seemed very interesting to me! Anyhoo – In this post, I shared:
> Limitations of Google Analytics
> Answered How many websites in USA exceed the limitations of Google Analytics?
[UPDATE Feb 10th 2013] I made a mistake in correlating data from Quantcast and Google Analytics. Lesson learned:double-check for units when comparing data from two different sources
Florin Dumitrescu pointed out that while Quantcast uses People/Month and Google uses hits/month. They may NOT be always the same. Sorry about this.
@paras_doshi interesting post, but quantcast seem to measure the number of people/month, while the Analytics limitations are for hits/month
Once in a while I go back to basics to revisit some of the fundamental technology concepts that I’ve learned over past few years. Today, I want to revisit Data Mining and Knowledge Discovery Process:
Here are the steps:
1) Raw Data
2) Data Pre processing (cleaning, sampling, transformation, integration etc)
3) Modeling (Building a Data Mining Model)
4) Testing the Model a.k.a assessing the Model
5) Knowledge Discovery
Here is the visualization:
Additional Note:
In the world of Data Mining and Knowledge discovery, we’re looking for a specific type of intelligence from the data which is Patterns. This is important because patterns tend to repeat and so if we find patterns from our data, we can predict/forecast that such things can happen in future.
Conclusion:
In this blog post, we saw the Knowledge Discovery and Data Mining process.
The success of companies like Google, Facebook, Amazon, and Netflix, not to mention Wall Street firms and industries from manufacturing to retail and healthcare, is increasingly driven by better tools for extracting meaning from very large quantities of data,” says Tim O’Reilly
Resource: Presentations from the Sentiment Analysis Symposium http://bit.ly/VtPH3B
If I switched to the newest “holiday” theme on WordPress, this is how it would look: http://on.fb.me/UEuyFr
Nice! Code School now has R programming language! I have been playing with R for a while now and definitely want to learn more – here’s the link to learn R: http://bit.ly/VEAnkZ
Interesting tool from Google to optimize and analyze web page speeds: http://bit.ly/HTubNC
Performed #sentiment #Analysis on #starbucks twitter data using #R ! It was fun! http://on.fb.me/Z3qLo8
In 2002: The Data Warehousing Institute estimates that data quality problems cost U.S. businesses more than $600 billion a year. And of course, over the past 10 years, this number would be bigger. http://bit.ly/TPT9r3
