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.
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?
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?).
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:
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
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:
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.
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
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