Four Tenets for effective Metrics Design


The goal of this blog post is to provide four tenets for effective metrics design.

Four Tenets for effective Metrics Design

What is a tenet?

Tenet is a principle honored by a group of a people.

Why is effective metrics design important?

Metrics help with business decision-making. Picking the right metric increases the odds of decision making through data vs gut/intuition which can be a difference between success & failure.

Four Tenets for effective metrics design:

  1. We will prioritize quality over quantity of metrics: Prioritizing quality over quantity is important because if there are multiple metrics that teams are tracking then it’s hard for decision-makers to swarm on areas that are most important. Also having multiple metrics decreases the odds of each metric meeting the bar for quality. Now if you have few metrics that are well thought out and meets the other tenets that are listed in the post, it will increase the odds of having a solid data driven culture. I am not being prescriptive with what’s a good number of metrics you should have but you should definitely experiment and figure that out — however, I can give you a range: Anything less than 3 key metrics might be too less and more than 15 is a sign that need to trim down the list.
  2. We will design metrics that are behavior changing (aka actionable): A litmus test for this that ask your business decision-markers to articulate what they will do if the metric 1) goes up N% (let’s say 5%) 2) stays flat 3) goes down N% — they should have a clear answer for at least two out of three scenario’s above and if they can’t map a behavior change or action then this metric is not as important as you think. This is a sign that you can cut this metric from your “must-have” metrics list. This doesn’t mean that you don’t track it but it gives you a framework to prioritize other metrics over this or iterate your metric design till you can define this metric such that it is behavior changing.
  3. We will design metrics that are easy to understand: If your metrics are hard to understand then it’s harder to take actions from it and so it’s a pre-requisite for making your metrics that are behavior changing. Also, other than increasing your odd for the metrics being actionable, you are also making the metric appeal to a wider audience in your teams instead of just focusing on key business decision makers. Having a wide group of people understand your metrics is key to having a solid data driven culture.
  4. We will design metrics that are easy to compare: Metrics that are easy to compare across time-periods, customer segments & other business constructs help make it easy to understand and actionable. For e.g. If I tell you that we have 1000 paying customer last week and this week, that doesn’t give you enough signal whether it’s good or bad. But if I share that last week our conversion rate was 2.3% and this week our conversion rate is 2.1% then you know that something needs to be fixed on your conversion funnel given a 20 bps drop. Note that the ratios/rate are so easy to compare so one tactical tip that I have for you is that to make your metrics easy to compare, see if a ratio/rate makes sense in your case. Also, if your metrics are easy to compare then that increases the odds of it being behavior changing just like what i showed you through the example.


In this blog post, you learned about effective metric design.

What are your tips for picking good metrics? Would love to hear your thoughts!

Completed Marketing Analytics Course from Coursera:


I just successfully completed the Marketing Analytics course from coursera. The certificate was issued by coursera and university of virginia — it was great to brush up some of my existing skills and then build upon it by learning some new techniques/frameworks.

The course covered:

  1. Marketing Resource Allocation
  2. Metrics for Measuring Brand Assets
  3. Customer Lifetime Value
  4. Regression Basics
  5. Marketing Experiments

If you haven’t checked out courses on coursera yet then I would recommend to check those out! There’s a ton out there for data professionals!

Coursera Marketing Analytics Certificate


Titanic Data


Here’s a link to download the Titanic data — — it’s really useful in analytics and data science projects. You can:

  1. Build a predictive model. Example:
  2. I also use this data set to create interactive dashboards on tools like Qlik and Tableau to understand their features.


If you liked this, you may also like other data sets that I have here:

How to add custom User-ID to your Universal Analytics (Google) implementation?


There are three different implementations that you could have with Google Analytics:

  1. Classic Google Analytics
  2. Universal analytics
  3. Universal analytics with Google Tag manager.

If you fall under “2. Universal analytics” then this post is for you since I’ll walk you through steps that you need to take see UserID’s on your google analytics report.

First why do you want UserID on your GA reports? 

1) Data blending is powerful. If you can combine your transactional datasets with web traffic data then you can extract some powerful insights! To be able to join your transactions data with web traffic data, you need some field that is common across those datasets. UserID might be one of the most useful fields that you could use for data blending.

2) Also having UserID in your reports let’s you perform some user behavior analysis at individual level and that could be pretty powerful too!

Now, How?

There are three steps:

  1. Identify the User ID
  2. Create a Custom Dimension on Google Analytics
  3. Modify your tracking code to send data for the custom dimension

Step 1. Identify the User ID

The first step is to identify the ID that you are going to send to Google analytics. Remember that you can’t send PII (personally identifiable information) so you can’t send something like an email id but you can send other ID’s that may be used in your database.

Step 2: Create a custom dimension on Google Analytics

Go to google analytics admin section > Select your account & property > Go to Custom dimensions

Custom dimensions google analytics

Now, create a new custom dimension. Give it a name, scope it and make sure it’s marked active.

Custom dimension universal analytics User ID

Step 3: Modify your tracking code to send data for the custom dimension

Notice that once you create the dimension, it will also show the example code (on the right side in the picture above). Send this to your web developer!

Just a note on this: The custom dimensions for which you are passing value using the tracking code are referenced as dimensionxx and you don’t use the Name like “Custom User ID” — if it’s the first custom dimension that you will refer to it as dimension1 in the code.

Next steps: Let me know if you have any further questions and if you are interested in seeing the steps for classic GA and Universal analytics w/ Google Tag manager then here’s a blog for you:

I hope this was helpful!

What percentage of users are authenticated? (Google Universal Analytics)


You’re using Google’s Universal Analytics — That’s great! They key to make sure that you get the most out of it is to make sure that you incentivize your users to log-in aka authenticate. First step in doing that is to figure out percentage of users that are authenticated…Here’s how you can see that report:

1. Login to Google Analytics

2. Select your view > Go to “Reporting” section

3. Navigate to Audience > Behavior > User-ID coverage

Google Analytics User ID Universal

4. On this report, you can see authenticated vs unauthenticated sessions:

Percentage of authenticated users google analytics Universal


In this post, we talked about how to run a report that shows you percentage of authenticated users. (In google’s Universal analytics)

How to analyze “new users” metric by specific pages in Google Analytics?



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?).

New users by specific pages funnel visualization google analytics


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.

Achievement Unlocked! Passed Google Analytics certification Exam.


I recently completed the Google Analytics certification exam!

Here’s the Google Analytics Individual Qualification (GAIQ) certificate:

Google Analytics Certification Exam

New Digital Marketing Analytics Report shows social media is not the best source of acquiring customers:


It’s great to see Insights that data can uncover. I saw a nice insight in a report I read about Analyzing customer acquisition channels for e-commerce sites and in this blog post, I am sharing it with you. So what are the top customer acquisition channels for Commerce sites? The Top channels are Organic Search, Emails & Paid Search.Here’s the report: E-Commerce Customer Acquisition Snapshot

It was not surprising to me to see Organic Search and Emails being among the Top customer acquisition channels but what surprised me was  relatively poor performance of social media in acquiring customers. Here’s the chart showing performance of various online channels for acquiring customers:

ecommerce analytics percentage of customer acquired vs. channel

Data Source:

Note #1: The post is NOT about devaluing the benefits of social media and it comes to down to understanding the goals of having a social media presence in the first place. While computing the ROI of social media, there are other factors like increased brand awareness, customer loyalty to be considered. But I posted this data because it’s a great way to show how data can uncover insights and sometimes it may surprise you

Note #2: The percentage of customers acquired does not add up to 100% for a year because the data does not include things like direct traffic. The author of the report confirmed it over an email w/ me.

That’s about it for this post. Your comments are very welcome!

Google Analytics: How to Track an email campaign?


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:

google analytics track email campaign

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.

How do we create it? Use this web service: to create an URL:

This is how an URL that I created looks:

google URL builder google analytics

2. Create an advanced segment in Google Analytics:

> Open Google Analytics.

> Select your site

> you should be in the audience overview report

> From here, click on advanced segment and click on new custom segment

google analytics advance segments> Here I’ve configured it like shown in the image below. Note the name of the campaign is same as the name of the campaign in STEP 1.

email campaign track google analytics> Save segment

> next time you visit, you’ll see this custom segment – select it and you’ll see only from the campaign that you want to track:

google analytics custom segments traffic

That’s about it for this post. your comments are very welcome!

How many websites in USA exceed the data collection limitations of Google Analytics?


Little bit of background:

– I was researching on the limitations of Google Analytics

– After reading the Limitations, I wanted to know – How many websites in USA exceed the limitations of Google Analytics?

So Here’s the Short Answer:

Only 108 sites exceed this limitation

(as of today)

And Here’s the long answer:

Limitations of Google Analytics. Here’s the URL:

And I am quoting from the above URL:

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.

so from data collection limit standpoint, only these 100 odd sites would exceed the limitations of Google Analytics.

To put things in Perspective: does not exceed Data Collection Google Analytics Limit:

my space can use google analytics


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.