Posts Tagged ‘mobile analytics’

Sep 19

We used to hear “mobile is the future.” Then, we started to hear the phrase, “Mobile Now.” Finally, “Mobile First” is the reality. While this is great for consumers, as we have access to great apps and services literally at our finger tips, marketers are now challenged to keep up with new user-experiences, new platforms, mobile development, and yes, you guessed it, new mobile analytics! But, hey, no one said life in the fast lane was easy ;) And, when you need mobile insights in a jiffy, you’re naturally going to look at real-time reporting. Don’t get ahead of yourself though – it might not be what you expect.

Mobile Analytics vs. Standard Desktop Analytics

Just as mobile user-experience and mobile marketing have pushed beyond the familiar features and functionality of the traditional web, so does mobile analytics. General analysis concepts such as segmentation, acquisition, behavior, conversion etc. still very much apply to mobile analytics. But there are foundational mobile concepts that marketers should adopt and do so quickly.

Don’t waste any time before getting comfortable with these:

  • Tracking activity in a mobile app, in Google Analytics for example, requires a mobile SDK (and yes, you can use the Google Tag Manager for mobile).
  • Screens. Don’t get caught saying pageviews. Pages are for browsers.
  • Events and more Events for all your user interactions. No browser, no hyperlinks. Explicitly define every Event.
  • Crash and Exception reports. You won’t need these? Yeah, right.
  • Metrics like Installs (App installs) and IAP (In App Purchases).
  • Mixed Web and Mobile data for similar user interactions - like when a user logs in at to shop and later uses their Amazon iPhone app to make a purchase. It’s a multi-screen world, folks. Let’s track it.

These aspects will be the subject of another post, but I’ll share a taste of what is going in Mobile Analytics.

Google Analytics recently made a User Interface change and updated some metrics to work across desktop and mobile. Visitors are now Users and Visits are now Sessions. A needed switch as we begin to use the internet in browserless ways.

Real Time Reports

What about reporting? Take a look at Real-Time reports. In GA for web, Real Time reports show you data about your users as they traverse the site (after a few seconds of delay). How does Real-Time Reports work for Apps? Slightly differently. We’ve isolated the data in the following examples to highlight the differences.

In the Overview Report, you see how many active users there are, how many screen views the app is getting “Per Minute” and “Per Second”. The metrics work in the following ways:

Scenario one:

  • The app is started; the user navigates through number of screens and icons, links. Events are generated in GA.
  • After waiting, nothing shows up in the “Per second” window.
  • You escalate to your developers, they check the code and the GA View configuration and it’s all solid.
  • You run the test again. You watch closely. In two minutes, activities appear in the “Per minute” window showing activities that happened two minutes earlier (see first snapshot below). Huh? What happened?
  • This is as Real-Time as you are going to get. Not good? Sorry :( It’s by design. Stay with me as we learn why.

Data Dispatch
In Mobile Analytics and in our specific GA example, there is a concept called data dispatching, as defined by Google “As your app collects GA data, that data is added to a queue and periodically dispatched to Google Analytics. Periodic dispatch can occur either when your app is running in the foreground or the background.” Dispatching is used to reduce overhead, increase battery life, etc.

In the iOS, the default dispatch is 2 minutes (and you can adjust it to your liking).

For Android, the default dispatch is 30 minutes (and can be adjusted as well).

Other analytics platforms such as Flurry have similar concepts.

real time sdk google analytics screenshot 2

Scenario two:

  • The app was started; a number of screens and events were clicked on.
  • The app was killed—all within less than 2 minutes. The activities showed up right away in the Per Second window.
  • After a minute or 2, the activities showed up in the Per Minute window as shown below.
  • Why did the activity show up within less then 2 minutes in the Per Seconds and (pretty much less then 2 minutes) in the Per Minute window?

real time sdk google analytics screenshot 2

The way Data Dispatch works is that there is a set delay in which the activity is transmitted. However, if the app is terminated before that time frame, data will be submitted immediately. Thus, in this scenario, because the app was terminated before the 2 minute mark, the data was submitted and (after some processing time) showed up in the Per Second window. In the minute window, of course, after the processing time and minute intervals, then you’ll the real time activity.

real time sdk google analytics screenshot 3

An active user is triggered when you start the app, as seen below. The snapshot was taken within 1 min of starting the app. Just remember only 5 minutes of inactivity will drop the user from the Active User report even though their activity will be present in the Per Minute report.

real time sdk google analytics screenshot 4


So be careful – the present world of mobile Google Analytics Real-Time reports is different from what you might expect from desktop Real-Time. What you see isn’t necessarily exactly live, but rest assured that the same hits that have appeared in standard (non-Real-Time) Google Analytics reports are still making their way to GA to appear in the reports (and in some new reports, too) in only a few hours.

Share with us your thoughts and comments!

Feb 27

Googel Analytics Real TimeWhen working with high volume sites, slicing and dicing the data can be challenging, and looking for insights is very much like Tom Hank’s famous quote from the movie Saving Private Ryan – it’s like “finding a needle in a stack of needles”!

At E-Nor, we’re proud to work with some of the most recognizable brands in the world. Our clients expect sophisticated measurement and deep insights, more than “ancient” basic metrics like “total visits” or “site wide conversion rates” :) .

So what do you do? One thing I’ve learned over the years (the hard way at times!) is that as a consultant, and the same applies to marketers and practitioners, you should focus on what matters most to the business. Find creative ways to measure/report/analyze and find “gems” that truly impact the business. Along the way, that will make you look like a hero (and will ensure long-term employment!).

In this post, I’ll cover the challenges and solutions for understanding user behavior and cohort analysis across multiple platforms. The business we’re using as example is a large media organization where you “Sign Up” to access content. You then have the option to upgrade and buy a “Premium Subscription” as well as access to buy exclusive products and services. And in case you are just getting used to this type of analysis, a typical cohort analysis will show you the behavior of a “class” of visitors, typically segmented by an action on a specific date or date range.

We’ll cover:

  1. The Cross-Platform Challenge
  2. The Measurement Approach
  3. Integrated Reporting & Insights

1- The Challenge – Web, Mobile and Offline

In this multiple device, multiple platform world, understanding user behavior and measuring “what matters” require planning (and a bit of process) way before jumping into tagging and JavaScript. Especially as we start shifting our thinking from measuring visits and conversion rates, to visitors and customer lifetime value. I won’t get into the technical instrumentation of cohort analysis (just Google it, you’ll find many posts on the basic “how-to”). I’ll focus on the user-centric approach and marketing insights.

“Out of the Box” Cohort  - Mixpanel Analytics
Some analytics tools have cohort analysis built in their standard reports. For example, you could be using the Mixpanel platform (and assuming you’ve planned and implemented your events properly), you’ll get very meaningful cohort reports that can shed some light on user behavior over time. Say you have a content site where a subscription to access is required, you’d want to know if your users are coming back and consuming that great content you produce, if a cohort of users whom you acquired in a specific time period, are likely to be more loyal than others.

A standard Mixpanel cohort report will look like the snapshot below:

cohort mixpanel screenshot

The first column shows the date at which the “Sign Up” occurred. The “People” column shows how many people signed up on that day (e.g. 10,324 on Feb 5th, 2013) and the percentages represent the percent of people who come back after x-amount of days (where x is 1 to 12 in this chart). So for the Feb 5th cohorts, 1.84% of them came back and consumed more content two days after signing up.

In addition and without a lot of digging, you can clearly see that the segment of visitors who signed up on February 8th are super engaged in the first seven days, and they are coming back for more every other day. On the other hand, those who signed up on February 6th, behave completely different. They are interested initially and then their interest taper off.

Campaign Segmentation in Mixpanel
You are hungry for more insights, what do you do? Jump over to Mixpanel’s Segmentation reports (you can segment on the fly by region, referral and even Google Analytics utm parameters) and dig deeper to find the source of those who signed up on the 8th. You’ll notice here that the campaign that peaked on the 8th (in green) is likely to be a very good driver of such an engaged audience.

That’s good to know, but you are still not yet satisfied. The data above is from the web channel only. You are missing other acquisition channels.

In line with our cross-platform and the 360-degree customer view approach, let’s take this analysis to the next level for a large media site. Visitors register to access and share content, and with a paid “Premium Subscription” option then have access to discounted/exclusive products and services. You’d want to track user behavior across all potential channels on which a prospect might convert. A prospect can buy a Premium Subscription:

  • On the website
  • On their mobile app
  • Dial the 800 number and sign up “offline”

2- Solution Design – Analytics & Measuring Across Platforms

This large media site uses Google Analytics Premium and also has Flurry Analytics for their mobile app. But no matter what analytics platform you are using, this multiple-way conversion presents quite a challenge to cohort analysis in any one analytics product. Time to stitch and tie!

To have the 360-degree view of the customer, and stitch all the disparate data from the web, mobile and offline, there is a technical implementation aspect and a little bit of process. So yes, work is required, but the anticipated results are definitely worth all this pre-requisite hard work.

The highlights of what is needed include:

  • Web data — extract data from Google Analytics Premium
  • Mobile data — download your events data from Flurry
  • Offline — export your purchase data from your backend

And here are the details:

Web Analytics: Google Analytics Premium unsampled reports with the following metrics/dimensions:

  • Revenue
  • Date of transaction
  • Cohort date – The date the Premium Subscription took place, and is stored in a visitor-level Custom Variable 1
  • Unique customer ID, (of course, no personally identifying information), stored in visitor-level Custom Variable 2 (we will use this for the advanced user-centric tip at the end of the post)

Note: As previously stated, this is not a technical post, but here is how you’d set up Custom Variables. You’ll also need the help of your IT/dev team to coordinate the passing/managing of the unique ID in the backend system.

In Google Analytics, run an eCommerce -> Sales Report, and choose your Cohort date (CV1) as a secondary dimension, you’ll have something like this:

The table above shows the dates/revenue after the Premium Subscription date (e.g. CV1 = 20130109, January 9, 2013) during which a transaction took place, along with the revenue associated with these transactions. Now, say you want to see how the January 9th cohorts did compared to the January 12th cohorts. , Simply create an advanced segment for each of the Cohort dates and the graph will look as follows:


Here are the findings:

  • The January 9th cohorts brought in 2.84% of the revenue
  • The January 12th cohorts brought in 1.94% of the revenue
  • There were no more sales from either cohorts after January 21st

Once the “Cohort date” data has been collected, you can also plot it in Excel or Tableau in a traditional cohort chart. We will cover this later in the post.

Before we move on to more analysis, insights and actions, we still need to complete the picture. Remember, our subscribers can upgrade to a Premium Subscription using the mobile app as well. So let’s take a look at the mobile data next.

Mobile Analytics Data – Flurry Analytics come to the rescue
This client is an early adopter of mobile and has leveraged the powerful capabilities of Flurry Analytics since day one. The client has done their homework and planned out their user actions (aka Events) and did not just settle to track screens and buttons, but is also tracking outcomes like In-App Purchases (IAPs).

Similar to what we gathered from Google Analytics, in Flurry Analytics we want the following information:

  • An event when the Premium Subscription purchase takes place, date stamped for our cohort analysis (e.g. 20130109)
  • Revenue associated with purchases
  • Unique user ID (and again no PII please!). The user ID will show in your Flurry Event Log (we will use this for the advanced user-centric tip at the end of the post)

flurry event

As you see in the image above, your “time stamped” mobile app eCommerce data is now available.

We can create a segment in Flurry under Manage –> Segments and choose the Premium Purchase Date as the custom event/parameter for the segment, and then export this data (download as CSV or leverage the Flurry API). If you are downloading the CSV, your parameters (revenue, etc.) will be available in one cell in Excel, and you can easily parse the parameters you want to include in the report.

Offline – Backend Data
Well, we are almost there! Since the client’s system allows for offline Premium Subscription upgrades as well, we need this offline data integrated too. These elements are required from your backend:

  • Premium Subscription date
  • Date of purchase
  • Revenue
  • Unique customer ID

And finally, we download the offline data in a CSV file, and we are ready to rock and roll!

Note: if you are forward thinking and like to get your hand into the latest and greatest, then Universal Analytics (from Google Analytics) will be an option here. With Universal Analytics you will be able to import the offline user interactions into Google Analytics and map it to existing data.

3- Integrated Reporting – Customer 360-View, Tableau Dashboarding & Insights

If you’re using a data warehouse or a database one approach would be to present all this data in Tableau using its optimized connectors available for many data environments. If you haven’t made the investment into your infrastructure yet, or you don’t have the IT resources to leverage these connectors in Tableau, you could extract your data into CSVs from Google Analytics Premium, Flurry and your backend system and upload it into Tableau.

Now that you have your data ready from the three data sources (web, mobile and offline), it’s time to tie it all together, visualize, analyze and find some awesome actionable insights. Your common element for this analysis is going to be the Premium Subscription Date.


Aha! The cross-platform full picture is ready for you. You see the value of those who signed up on the 9th of January (in terms of sales and revenue), and you start understanding where they came from, what offer resonated with them among other factors.

Advanced Tip# 1 – Google Analytics Tableau Integration
If your business is a pure online play, and your subscribers can only buy on the website, I have a very nice surprise for you (kept this till the end to reward the loyal readers :) ). With Tableau version 8, there is a native integration between Tableau and Google Analytics (in beta but works well), meaning you can pull your dimensions and metrics directly from GA and into Tableau. You bypass the need to download files, reformat and upload. I’ll share the tips on doing so in a post by our Tableau geek extraordinaire Shiraz in the next few days. (Please note if you have a large site with high volume and you are getting sampled reports, this method will not work for you. For now, you’ll have to download the unsampled reports and then upload into Tableau).

Advanced Tip# 2 – User Centric Analytics
In-line with our emphasis on concepts such as user-centric analysis (and Universal Analytics), and in capturing data from different sources, I emphasized the need to include a unique user ID when customers buy the Premium Subscription. Once you have this common user ID (aka key) you can run all sort of sophisticated analyses in your Tableau or a BI tool of your choice. Examples include:

  • Customer Lifetime Value (LTV)
  • Recency & frequency across platforms (web, mobile, offline)
  • Segment high ticket item customers
  • Map demographics data (available in Flurry and/or your backend system) with web data
  • Plus more and more scenarios that I’ll leave for future posts

So there you have it, how to create a cohort analysis across mobile, web and offline platforms. I hope you found this post useful and I look forward to hearing your comments and input!

Feb 01

49er-mobileSuperbowl Sunday! GO NINERS!!!! Is mobile phone traffic on your site going to be the same during the game? During commercials? During halftime? In this post, we’ll show you how to figure that out!

Mobile is taking over! The ability to access the Internet from everywhere is so convenient – when you’re at the supermarket, gas station, even when you’re driving (don’t do that). Sometimes, I’m too lazy even open my laptop at home, it’s simpler to just pull out my mobile phone in front of my TV and connect.

And mobile use is only growing:

  • In 2013, more people use mobile than PC’s (Gartner 2011)
  • 50% of U.S. cell phone users have smartphones
  • 47% of consumers look up local information (for example, stores they want to visit)
  • 46% look up prices on a store’s mobile site
  • Etc.

(Statistics from

Marketers who don’t start accounting for this trend will surely be left behind. The design and structure of your site, how your visitors use it, how visitors buy, etc. – is completely different on mobile devices vs. desktop – even vs. tablets. A mobile visitor is on the go, the screen is significantly smaller than a PC and tablet, it’s touch screen, etc. As a marketer, you need to be able to do dive deep and figure out exactly what’s going on to get insights unique to each.

Ideally, the following insights is what you want to see. You can see in this case that mobile phone and tablet behavior is different – tablet visitors are much more engaged, spend more time on the site, and view an average of one more page than phones:

Mobile Traffic Only Report - Google Analytics

“Mobile” (including Tablet)

It’s tricky. Google Analytics lumps tablets into the “mobile category”. But what if your design is responsive, and you have a different design for your mobile phone site vs. your tablet site? What if that’s impacting your traffic differently? You’ll need to separate the data.

Advanced Segment: Mobile Phones Only

Google already has a default segment to analyze ONLY “Tablet” traffic. But where’s the “Mobile Phone only” default segment? We love Google, but hint hint, cmon guys…

Have no fear – our resident analyst genius, @charlesfarina created a simple advanced segment to do this. Here’s how:

Step 1. Create a New Custom Advanced Segment
At the dashboard, choose Advanced Segment and click on “New Custom Segment”
Create advanced segment in google analytics

Step 2. Name Your Custom Segment
Name it something useful like “Phones”

Step 3. Include Mobile Traffic
Get all of mobile traffic, including Tablets and Mobile by selecting “Include” > “Mobile (including Tablet)” > containing “Yes”.

Step 4. Get rid of Tablet traffic
In order to separate mobile phones from tablets – you want [Mobile (which is mobile + tablets)] – [Tablet]
Add an “and” statement and “Exclude” > “Tablet” > containing “Yes”. This will get rid of tablet traffic.

Your advanced segment should look like this:
Mobile Phones Only Advanced Segment - Google Analytics

You are ready to slice and dice only mobile phone traffic!
Just in case, here’s a quick link for the segment (so you can just save it to your profile automatically).

Sep 24

E-Nor is expanding! We are pleased to announce the opening of our newest office in Tampa, Florida. Starting this week, our new location will service the analytics and marketing optimization needs of E-Nor’s clients in the Tampa Bay area and Southeastern United States region. Operations will be led by Principal Partner, Bilal Saleh. We recently sat down for a Q&A session with Bilal, and wanted to share this exciting news with our customers, friends and community.

Q: Tell us a little bit about your background.

A: Well, I’ve been fortunate enough to have had the chance to work on cutting-edge technologies with the brightest engineering minds in the industry. I am also fortunate to have worked with visionary marketers pushing disruptive services and business models.

My career began as a software engineer developing chip-level communication protocols for one of the early voice response systems in the industry. I then progressed through various leadership roles including engineering management, business unit head, and then general manager. I established a business unit responsible for engineering, marketing and selling a service delivery platform for developing, deploying and managing mobile applications, which was a major shift in my career. That’s when I started my MBA at Kellogg. At that time, I handled B2B and C2C marketing, business intelligence, data-driven product positioning and pricing, and the mobile applications eco system. I also created business models for service providers and app developers to monetize mobile applications and content, and handled sales funnel management – lead generation, tracking, and nurturing in an extremely complex and competitive telecom environment.

Q: You have been granted three US patents, that’s quite impressive, what did it take?

A: Being a part of a team solving problems at the industry level and shaping the global standards puts you in a unique position that really gravitates you towards innovation. I remember my first patent: I was working late with a colleague, drafting a proposal for one of the T1P1 standards groups and we came up with a simple solution to a complex problem without adding complexity to the network. After brainstorming the solution on the whiteboard, we both looked at each other and said, “This is a patentable idea!” We stayed up all night and drafted the patent application which was granted in less than a year.

Going through the patent filing process is exciting. We had to sell the idea to an internal committee consisting of some of the brightest engineering minds, marketers and, of course, patent lawyers. That was a humbling experience for me.

Q: You have traveled the globe consulting and advising some of the most well-known brands.  This is a clear benefit to E-Nor’s customers, share a little of your global experience?

A: Remember, when you are a young and enthusiastic software developer, your world evolves around solving technical problems. When you leave the lab and start talking to customers and listening to their pain points, you quickly realize that technology is just one piece of the puzzle and you start to understand the big picture. Your mindset changes and you start seeing technology as an enabler used by business leaders to achieve economical value for their shareholders.

The fact that I worked with some top global brands/tier-1 service providers to solve business problems using technology, and was exposed to a mix of culturally- and technologically-diverse customers was a big plus. That exposure not only enriched and shaped my view of the role of technology in achieving business goals, but also helped me understand and appreciate my customers’ pain points and focused my energy on developing business solutions. This shift in thinking and mindset forced me to be even more analytical and data-driven, not only from an engineering perspective, but also from a marketing and business intelligence perspective, where deriving insight from all the data one has is a critical factor for success. I think this particular aspect of my experience will enable me to understand our customers’ business objectives and pain points, and to develop practical solutions that achieve measurable results.

Q: What is your vision for the Florida office?

A: E-Nor is a trusted consultant throughout California and beyond. I hope to be able to leverage the company’s expertise and brand, and expand it to the business community in the Tampa Bay area and the whole Southeast. I plan to grow our healthcare and tourism segments, oh, and beat the California office in YoY growth!

Q: As one of the pioneers in the mobile industry, where do you see mobile going?

A: There are a number of studies projecting that the mobile device will become the number one device for accessing the web. Putting this in perspective, and in the context of global brands that are not confined to any specific geographies, you can quickly realize that the volume and variety of data these devices will generate is mind boggling. Being a veteran of the mobile industry and having helped global service providers in developing their mobile applications strategies and business models gives me the ability to look at mobile data in a more meaningful way. For instance, understanding how the location of a consumer influences his/her browsing behavior and purchasing decisions gives a deeper insight into his/her needs and intents. Browsing on a small screen and using touch instead of clicks also influences a user’s web interaction behavior. Understanding these subtleties in user behavior and their impacts on buying decisions will be a fascinating and exciting problem for marketers to solve. We need to be able to decipher “big data” and make sense out of what consumers are looking for.

Q: You have adopted the E-Nor analytics framework and are helping businesses in Florida leverage data to make better business decisions. What are the major marketing and analytics needs you encounter when working with businesses?

A: Businesses need to be discovering how much valuable and insightful data they have at their disposal and figure out to how to leverage it to make more educated decisions. They should replace the guesswork with a data-driven understanding of their customer’s behavior, which ultimately leads to better marketing and business decisions. Business leaders should also develop an understanding of what they are doing well or not so well , i.e. why they are spending too much money on marketing but not realizing great returns. Basically. just help them know what they do not know when it comes to digital analytics!

Q: On the personal side, Feras said that you do two hours of cardio every morning… is that true?! :)

A: Well, that must have come from Feras, he is raising the bar! I think he is referring to my challenge to my 20-year-old nephew 10 years ago, to do two hours of cardio and burn 20 calories a minute. I do not recall who won the challenge! ;)

Seriously though, starting my day at the gym gives me the energy and the focus I need throughout the day. My 30-minute cardio is the best time to organize my thoughts and plan my day.

Thank you Bilal for this interview, and welcome on board!! For more information on E-Nor’s Southeastern U.S. market, contact Bilal Saleh at (408) 988-0003 ext. 210 or Bilal(at)E-Nor(dot)com.

Jan 10

I have recently guest-authored a series of posts on mobile analytics strategy on the Google Analytics blog. Each of the three posts highlights simple yet key steps for marketers to track their mobile traffic and improve their returns.

For those of you on the go, here’s a quick glance at the material I covered.  Try to make time to read each post in-depth, even if you have to read it on your smart phone!


1 – Look for Mobile Trends

In the first post, I detail how to monitor and analyze mobile traffic using key performance indicators. This is best done by customizing your GA settings to receive mobile traffic reports, custom alerts, and for the enthusiast, using the Google Analytics data export API.

2 – Give Your Reports More Dollar Power

So you’re mobile trends are positive, do you just throw the data to your boss? No. You always want to give your reports more dollar power. The second post centers on the power of presentation. If you’re CEO can easily connect the dots, two bottoms will be covered — your company’s and yours! :)

3 – Act on Your ROI

The average analytics guy will stop at step 2, but the third post encourages you to do more. Additional segmentation and leveraging  AdWords’ reports will allow you the much needed visibility into campaign performance to maximize your results.


And There’s More!

For tor the technically inclined, and to get a more comprehensive perspective on your mobile presence, there is more you can do. Check out the code site page on mobile to:

  • Track native iPhone or Android applications
  • Track activities on websites from low-end mobile devices

And be on the lookout for  niche analytics solutions specifically built for mobile.

Remember, it’s never too late to start maximizing your company’s mobile investment and implementation. Be sure to check out each post for more details and practical tips.

For more analytics tips and insights, follow @ferasa on twitter.  Happy analyzing!