“I…i…i…i… I’m soooo in love with you… whatever you waaaant to dooo… it’s alright with meeeee…!” – lyrics from the “Reverend of Soul” himself – Al Green.
It’s Valentine’s Day, love is in the air! So, we thought we’d shoot cupid’s arrow through this next post about data and measurement. Give it some “love”, so to speak.
If you’re heavy into Google Analytics, you might be “infatuated” with quantitative data - “views”, “visits”, “bounces”, etc. – and…ahem…”RAW” numbers. That’s only one “better half” though. That is, it’ll tell you “what” is happening on your site. However, what about the other half – “why”??? One way to answer that question is by “marrying” your quantitative analytics data with qualitative, “voice-of-customer” survey data.
“Why… why do people break up? Then turn around and make up… I just can’t seeeeeeee….”
Let’s take a statistic of love. Unfortunately, it looks like approximately 50% of marriages fail [Cupid, what the hec are you shooting at?] The Reverend of Soul, Al Green stated in his immortal lyrics, that he could see “what” was happening, but for the life of him, just couldn’t see “why” people break up!!!
This Valentine’s Day, let’s pretend to try to solve this urgent matter of the heart. WHY is this happening?! Is the aforementioned statistic enough for you to take action? Doesn’t look like it.
Those of you who’ve been through a tough time in your relationship know it’s not black and white – there could be a plethora of reasons:
You might have grown apart
Stresses like money could have strained the relationship
Communication could be missing
As any counselor would tell you, they wouldn’t just diagnose “what” is going on in a couple’s troubled relationship, then right away present solutions. In order to solve the issues, they would go into several deep counseling sessions so they can get to the nitty gritty of “why” this is happening.
Similarly, diagnosing “what” the issues are with your website is only part of the process. Voice-Of-Customer qualitative surveys could potentially give you insight into “why”, insight that may not be readily apparent from quantitative data.
“Let’s Stay Together” – Putting Voice-Of-Customer Together with Quantitative Data
You have several ad campaigns leading visitors to a landing page asking them to register for your event. As the example figure below indicates, your analytics may be telling you that your landing page is getting all the traffic you’re paying for, from Facebook/Google Adwords campaigns, etc. You’re spending good money, and your micro conversion, say an agenda for your event, is getting all the downloads you want. But according to your data, the bounce rate is really high and no one is registering for your conference. Why?!
We recently ran into a similar situation with a project our consultants were assessing, and tried to figure out the issue:
Was there not enough sales information? We listed all the bullet points…
Did clients not trust the organization/service? We listed impressive certifications and testimonials…
Was the registration call-to-action button not clear enough? It’s big and yellow, and it looks like people are clicking on it according to our data…Just not completing registration
At this point, even if you had all the unsampled data in the world from Google Analytics Premium, you’d still be stuck. There’s always an option of implementing A/B testing, but that would take time and coding. Plus, what do you start testing? You can make educated guesses, but you’re pretty much taking shots in the dark (like cupid).
So even before we explored A/B testing, we tried implementing Qualaroo – an awesome, quick, non-invasive survey that quietly pops up based on criteria you set (ex. 30 seconds on the page, after 2 pages have been visited, etc.). You can ask any question – open-ended, multiple-choice, etc. And after each survey is complete, get reports in the native interface or download reports into .xls for deeper crunching.
So we asked – “Second thoughts about registering? Why?”
Sample responses were as follows:
As you can see from the responses (after ensuring we had enough replies for an acceptable confidence level/ statistical significance…), it was pretty much unanimous – pricing was the issue!
It would have been extremely hard to conclude that with just the quantitative data. We may have stumbled upon this after some A/B testing, however, after marrying the qualitative, it pointed us towards a pretty reliable direction in a quick and efficient manner. Even if we wanted to verify using A/B testing, we now have an idea of where to start. They lowered the pricing and registrations started rolling in!
So when you’re having dinner by candlelight tonight, gazing into your lover’s eyes… slowly move in close, and whisper ever so gently… “My quantitative is incomplete without your qualitative…” <3
We have been hard at work over the past few months doing what we can to share analytics tips, best practices and the latest from the trenches relevant to the measurement industry and those on their road to becoming analysis ninjas . We have had the pleasure of connecting with some influential media outlets and thought it would be beneficial to share some of our recent published pieces with our blog followers. Feel free to click through these links to review the entire piece.
Take a Moment to Get Feras’s M.O.
E-Nor’s Co-Founder and Principal Consultant, Feras Alhlou was recently featured on MO.com, a website highlighting entrepreneurs from all industries and all around the world. This online publication examines what makes entrepreneurs tick and shares with readers their habits, strategies and business philosophies. Feras’s feature begins with a quote that encapsulates his drive to make E-Nor successful, “Delivering and measuring results, then sharing those results with our clients, along with demonstrating the positive impact on their bottom line was (and still is) very satisfying to me.”
The competition was fierce, but CampaignAlyzer, a web-based solution that acts as a central repository platform where organizations can store their marketing campaign values in one database, caught the love of the audience and social world! The application streamlines campaign tagging into a process that is efficient, timely, accurate, adaptive, value-added and business critical.
Cost Data Import- Ever wanted to measure return on investment from multiple digital channels? Import data from multiple channels and review them in a custom report for cost analysis of traffic sources. See how all your digital marketing channels are performing compared to each other, so you can make better decisions about your marketing programs. E-Nor was featured on the Google Analytics Blog as a partner who implemented the cost data import successfully for a client (OEMPCWorld).
Timely Analytics for the Holiday
The PR team at E-Nor always tries to keep content timely and current, which is why we released an article just this week on Data Analytics for a Profitable Holiday Season through Independent Retailer’s online publication. This article provides valuable information to retail store owners and marketing managers on what and how to measure digital data just in time for Black Friday and Cyber Monday. We shared tips, suggestions and resources to ensure you have a profitable holiday season.
Talk About Analytics
Feras spoke on a number of different occasions this fall, one of which was at the Conversion Conference last month in Fort Lauderdale, Florida. As a speaker at the event, Feras touched on the topic of Big Data’s Perfect Storm: Actionable Customer Insights from the Cloud. Here, conference attendees learned about the “magic powers” of Big Data and data integration to provide the 360 view of customers and stitching data from multiple sources (campaign costs, CRM, web analytics data) to produce insights on reducing lead acquisition costs and overall cost per qualified lead.
E-Nor was featured on PUNCH Media & Marketing Made Easy radio show 1220 a.m. KDOW, The Wall Street Business Network, where Feras spoke on the topic of Web Analytics & Marketing Optimization. Listeners gained knowledge on measuring online marketing activities with email marketing campaigns, website offers and social media measurement. (Archived episodes aired October 6, 2012.)
Smart analyst, smart analyst, what do you see? I see more segmentations made just for me!
Marketer, marketer, what do you see? I see detailed reports and valuable insights made available for me!
Business owner, business owner, what do you see? I see more money for me!
Online shopper, online shopper, what do you see? I see an amazing website customized and optimized for me!
Say you have an online store where you sell clothes for men, women, and children. Wouldn’t it be nice to have more visibility into the shopping experience based on site visitors’ age, gender, and products of interest?
In this post, I would like to walk through our implementation strategy and technical details.
As visitors enter the store website, they will be tagged with different labels based on some personal unidentifiable information (gender and age), and based on the pages they visit (products and store departments):
Tom is a new visitor. He registered on the site, viewed a product (women’s pajamas), added the item to the shopping cart and then completed the purchase.
At the end of the session, Tom’s visit will be labeled as the following:
Sara is a returning visitor who in a previous visit registered to the site. She viewed a few products (men’s and women’s apparel), and then left the site.
At the end of the session, Sara’s visit will be labeled as the following:
1. Customizing the tracking code:
At the visitor level we will use custom variables to segment visits based on their entries in a form. Let’s use the values that visitors voluntarily enter in the “gender” and “age” fields in the following form. These custom variables will remain attached to the visitors for future visits starting from the visit in which they filled the registration form (until they clear their cookies).
Setting the value of “gender” and “age”:
Add custom code that takes the gender and age values from the registration form.
Pass the two variables (gender-variable, age-variable) to the registration confirmation page
In the registration confirmation page, add the following code inside the GATC right before* the pageview GIF request _trackPageview()
At the session level we will use custom variables to distinguish visitors’ behavior across sessions based on their conversion. In this way, we can segment visits by those who complete e-commerce transactions versus those who just browse products on the site.
A visitor will be tagged as a “buyer” if he or she completes a transaction. If they do not buy anything, the visitor will be tagged as “justlooking”.
Setting the value of “visitor-type” to “buyer”:
In the transaction confirmation page (thank you page) add the following code inside the GATC right before the pageview GIF request _trackPageview()
Setting the default value of “visitor-type” to “justlooking”:
All visitors will be tagged by default as “justlooking” once they enter the site by setting the value of the custom variable “visitor-type” to “justlooking” at the session-level.
Add the below code* to all landing pages right after the GATC.
* High-level description of the code:
extracts the “_utmb” string from the cookies set by Google Analytics
extracts the “pageview count” value from the _utmb cookie
if the session’s “pageview count” is equal to 1 (landing page), set the value of “visitor-type” to “justlooking”
var utmb = get_utm_value(document.cookie, ‘__utmb=’, ‘;’);
var utmc = get_utm_value(document.cookie, ‘__utmc=’, ‘;’);
var pageview_count = get_utm_value2(utmb, utmc);
pageTracker._setCustomVar(3, “visitor-type”, “justlooking”, 2);
//This function extracts the “_utmb” and “_utmc” string from the cookies set by Google Analytics
//This function was originally written by the Google Analytics team (urchin.js)
if (!l || l==”" || !n || n==”" || !s || s==”") return “-”;
var i, i2, i3, c=”-”;
if (i > -1)
if (i2 < 0)
//This function extracts the “pageview count” value from the _utmb cookie
var i, j, k;
At the page level we will use custom variables to determine which product categories and store departments are visited. We will set a custom variable at the page level for each product, where the product category and the department for that product is set as a custom variable.
Setting the value of “store-department” and “product-category”:
In each product page, add the following code inside the GATC right before the pageview GIF request _trackPageview()
Integrating lead information from one system such as Google Adwords into a CRM like Salesforce is definitely not a new topic, especially since the Salesforce-Google Adwords integration has been announced for a while now.
I want to highlight the steps required for a seamless integration, as well as a few additional pro-active steps you want to take to keep your Google Analytics data clean. The same concept would apply to other analytics tools you might be running. As Avinash always reminds us, data accuracy is always one of the biggest challenges in web analytics.
Here are my steps:
Create Adwords and Salesforce accounts.
Link Google AdWords with Salesforce.
Exclude SalesForce parameters from Google Analytics.
Set up AdWords lead tracking.
1) Create Adwords and Salesforce accounts
You need to have a Google AdWords account and a Salesforce account before you can integrate them.
In Salesforce, click the Google AdWords Setup tab.
Enter your AdWords customer ID and login e-mail.
3) Exclude SalesForce Parameters from Google Analytics
When Salesforce performs its integration with AdWords, it appends parameters (_kk and _kt) to all destination URLs in your AdWords account. We suggest that you strip these query parameters out of URL to insure no duplicate entries in your Top Content report.
To strip the query parameters, please follow these steps:
Exclude the following query parameters: _kk and _kt
*A note for AdWords managers. Keep in mind that when Salesforce appends the destination URLs with its _kk parameters, this is actually “editing” your AdWords ads and the stats associated with these ads will now reset, according to how Google AdWords works.
4) Set up AdWords Lead Tracking
Back in SalesForce, click on the Google AdWords Setup tab.
Hello world! I’ve always wanted to say that I’m new to the blogosphere – I’ve posted on this blog before, but it’s been an eternity. I’m hoping to be much more consistent going forward. This post and the upcoming posts you’ll see from me will be focused on communicating what I’m learning about Web Analytics. I’ve been in Creative Marketing now for several years – I have a strong background in Web Usability and Marketing Consulting. You could say I’ve always been analyzing, just not with the tools/concepts in Web Analytics. Although our company is a Google Authorized Analytics Consultant (GAAC), I’ve only been involved in a limited capacity in Analytics. That’s changing now I attended an event held by the SVAMA 10 days ago and figured my notes about the event would be the best way to get the ball rolling. Being new to Web Analytics, it’s a challenging subject to start writing about, but I figured there’s no better way to learn than to write about what I’m learning. This helps reinforce what I’m learning in my own mind, and also opens the door to feedback from readers. As I learn new concepts and techniques each week, I’ll blog about them. I’m pretty excited about it, and hope this is useful and beneficial.
It’s 1:00 AM as I’m writing this and it’s been a super long day at work. My 9 month old baby has been having tummy trouble the last few days so I’m feeling a little sleep deprived. In any case, I’ve had my coffee and everyone’s asleep, so it’s quiet and I can focus on writing I have this new found love of woodworking and wanted to spend time in the garage but if I started cutting wood with my electric saw at this hour (no man is complete without an electric saw), I’d wake up the neighbors. Besides it’s too late to finish that workbench I started building this weekend…I’ll get back to that next weekend I suppose.
To Web Analytics and beyond…
I recently attended a session held by the SVAMA at the Googleplex, with guest speaker and Analytics Evangelist, Avinash Kaushik. Before I start off, I want to say that Google food IS all it’s cracked up to be… my colleagues and I thoroughly enjoyed breakfast
Avinash is author of the book: “Web Analytics: An Hour a Day.” He’s a wonderfully articulate, inspiring speaker. As a newbie to analytics, I learned more from this session than what I had previously heard or read about. We have several Analytics geeks here at the office and I hate getting left out of the conversation when they start talking in their ego-maniacal uber cool geek-speak. Well, after this session, I can at least keep up with them, even if it hurts a little.
The title of the session was Actionable Web Analytics. Avinash began by talking about data and how there is an overwhelming abundance of data available to companies. There’s so many tools out there that result in data overload. He posed the question: Does all this data provide us the insight needed for a successful site?
He emphasized 6 points which I’ve listed below.
1) Actionability is an Attitude
The concept of actionability helps identify underlying issues on websites really fast. Without much knowledge about the site or the subject matter, you can easily find Actionable Insights by looking at key metrics.
Bounce rate (To quote Avinash “I came, I puked, I left”) is a great way to measure how effective a page is performing. Generally speaking, the lower the bounce rate, the better. This has to be taken with a grain of salt though, since some pages might be designed to have a high bounce rate (ie. blogs, contact us pages, etc.)
Another point emphasized was about site home pages. Too much emphasis is placed on the home page. I’ve participated in hundreds of web site design cycles, and I can wholeheartedly agree that far too much emphasis is placed on the home page. The concept of a home page assumes that the user will always walk through the front door into your home. That simply isn’t the case. We don’t live in a world where users have to enter your site through the front door. The search engine holds the keys and the blueprints to your site. Whatever the search engine determines is the home page, essentially becomes the home page of your site. If your user searches for a keyword that results in the search engine displaying your “About Us” page as a result, than that’s effectively the home page for that user, for that visit. So basically every page is a home page.
Armed with the above knowledge, you could now look at the top entry points of your site and easily determine what is working well and what isn’t. This metric gives you information about your users (ie. what they are looking for) and also tells you what they are doing on your site, so you can focus on optimizing pages that need it.
2) Give your Data Context
Avinash had this neat little acronym he called PALM – People Against Lonely Metrics. I laughed, but then realized what it really means. Data needs context. Without context, the data is meaningless and definitely not actionable. Data is relative and needs comparison to have meaning. A report showing a month’s data isn’t as insightful and actionable as a report showing a comparison of the current month to the last month and to previous months. This latter approach facilitates actionability whereas the previous approach would simply show a view of the data inside a bubble. In highlighting metrics, focus on goal conversion and outcomes – these are what’s important to your client, the rest is just extra information. Use tools such as compete.com or Fireclick to compare results to your competitors.
3) Say No to Data Pukes
This section really opened my eyes because it cemented in my mind what Analytics is about. It’s not about throwing a bunch of data and numbers to your customers. Showing them top 10 pages or top 10 keywords is useful in the beginning stages but this list becomes stagnant very quickly. How often does it really change? All the little tweaks being done on the site – the ones that really matter – typically won’t result in a significant change in the “top 10″. What’s important to highlight is what’s changing on the site, such as the top 10 rising pages, or the top 10 falling pages. Again this gives data some context and is actionable.
4) Segment Like Crazy
I come from the Usability world, so when Avinash mentioned his next point about Personas, it connected several dots for me. Personas! Personas! Personas! it’s all about personas! In order to understand your users, you have to know who they are where they are coming from and what they are doing on your site. In analytics, data can be segmented by visitor source to identify where traffic originated from (ie. Organic search engine traffic, Paid campaigns, direct, referring sites, etc). Visitor paths, etc. can identify what your users are doing on your site and give you insights on what you can do to make their experience more beneficial.
5) Ask Your Customers
Surveys are a great little tool, revealing tidbits of information that is very valuable. Ask your customers “Why are you here?” and “Were you able to find what you were looking for?” Two simple questions – but they provide feedback that will help you transform any site from a mundane to a rich experience, identifying what Avinash referred to as “segments of discontent” – another actionable insight.
6) Automating Actionability
Avinash has these creative little acronyms to illustrate his points – HiPPO is another gem of an acronym. He said that websites are typically designed by HiPPO’s - HiPPO stands for Highest Paid Person’s Opinion. This brought back so many memories for me because I’ve facilitated so many creative designs and this is so true. The only way to really tell which banner works best or which font style works best or which color works best, is to let your users decide. Huh? but how can they participate in the creative review cycle? Easy… By doing A/B testing or multivariate testing, your users literally tell you what works and what doesn’t work. Actionable Insights….
If there’s one thing I got out of this presentation by Avinash, it was that Analytics is Qualitative. What???? Qualitative???? I almost wanted to press the rewind button to make sure I heard that right. Wouldn’t it be great if life was a Tivo? Qualitative? Analytics is all about numbers right? It’s about the data, right?
This was the biggest revelation of the day for me. All this time I was under the impression that Analytics was all about numbers and data. It was purely quantitative in my mind. In reality it’s just the opposite. The numbers are only indicators of what is essentially qualitative data. If you focus on the numbers, you’ll get lost. If you focus on what the numbers represent (ie. user behavior), therein lies the heart of analytics. Once I got this point down (and it took a while to sink in), it changed my perspective on what analytics really is and how it all fits together.
The last thing that he mentioned that I really liked was that companies should spend 10% on the tool, and 90% on the people. Again this ties back into analytics being a qualitative discipline – it’s not just number crunching, we’re talking about user behavior.
Well time to go catch some zzzzzz’s now. Look for more entries from me as I continue my learning curve in Analytics. Looking forward to hearing feedback, and feel free to send me any tips about woodworking as well