Working in the Silicon Valley is an awesome ongoing adventure. The spirit of entrepreneurship, creativity, hard work, and fun is always there. Even large companies like Google have the “20 percent time” program, where Googlers are allowed to use 20 percent of their work week to pursue any special project they like, which Google claims many of their innovative products to have originate from.
Here at E-Nor, such innovative spirit is integrated in our culture and company’s DNA. We try to think about data and analytics beyond the 8 (official) working hours Such spirit can be found in a project of one of our lead analysts and long time blogger, Allaedin Ezzedin, in a little fairy tale called “Alice in Marketing Wonderland”.
For your digital marketing amusement, if you’re a child of Analytics ready for a wondrous journey through a world of marketing fantasy, watch the video below!
Sometimes, the urls (and titles) of your pages are not conducive to web analytics reporting. For example, your ecommerce site’s payment, shipping, and order confirmation page may all have the same url for some reason – http://www.domain.com/checkout.aspx. To web analytics, all these funnel pages are reported as one page. You are now stuck, you can’t create ecommerce funnels and measuring shopping cart funnel abandonment is impossible. And there is a more subtle and serious issue as well, in your report, you may find hits (events, ecommerce, social, etc) associated with this url, but you won’t know what part of the order process these hits belong to.
Here’s the actual flow we want to track and understand:
If you have a shipping calculator on your shipping page, a card type drop-down on the payment page, social buttons on all pages, you want to track each of these events on each page. However, it will show like this:
All the urls are the same! How do you know if these events happened on the shipping page, payment page or order confirmation page? You might be able to tell from the event names, but in some cases you may not be 100% sure, and this is definitely not clean and ideal.
While fixing the actual real urls and title tags (assigning unique urls and titles per page) would make things very organized, your content management system may not support this, or you might prefer not to spend that time or money on developers.
Luckily, there is a secret, undocumented method that allows you to actually set the page url and title of a visited page in Google Analytics. More importantly, it will actually associate the hits with these new, more meaningful page urls and titles. Your reports will be easier to read and will provide insights that may not have been available before.
The Issue With Virtual Pages
The traditional solution to this would be to use the _trackPageview method and trigger virtual pages for each “step” (i.e. /virtual-page/shipping.html, etc.).
The drawback here though is still, the actual events will not be associated with these virtual pages you’ve created. They will always be connected to the “real” page, which would be /checkout.aspx (as you can see in the screenshot above). You’re still lacking potentially valuable insights.
SECRET HACK! Setting the URL and TITLE in Google Analytics – _set method
With this new _set method, you can manually set the url and title of the page to whatever convenient name you want.
In the case of the ecommerce example mentioned earlier, for each page you’d like to rename, you can pass the preferred url and title so that it’s separated and meaningful in Google Analytics and associated WITH THE HITS:
We got a couple Google Analytics service calls this morning from some concerned patrons freaking out about traffic in their real-time report that was coming from an international space station (one of them was a government call!).
WTH? International spies? Aliens?
Well, we looked at a couple of other client profiles, and we saw the same exact traffic… and it actually isn’t counted in the real-time counter.
41 visits all day consistently… 4/1… April fools… pssssshhhhh….
Looks like we’ve been dupped by Google Analytics April Fools 2013. Very funny :/
No matter what the latest marketing channel or marketing buzzword is, email marketing is here to stay and you’d better be paying close attention to it. We’ve covered some basic email marketing strategies in the following parts:part 1, part 2 and part 3. But once you’ve got a solid email marketing program, you’ve gotta be measuring how it did! This post is about email marketing analytics, and in line with our “user-centric” approach to measurement, I’ll share tips with you on how to report not only on traditional email metrics, but also how to see a 360 view of your customers and prospects.
The beauty of the user-centric approach is that your data will be specific to your customer base. You’re not just looking at “open rates” or “click-through rates” in just email marketing, but you’re measuring the entire user experience. This way, you can better decide what works and what doesn’t work based on the interaction with the user. Tracking helps you to constantly improve your email, web and mobile content and approach based on your customer’s overall behavior.
First let’s cover the basics. Most email marketing platforms, such as Exact Target, Responsys, iContact, MailChimp, Constant Contact, VerticalResponse, etc. all have integrated tracking. In fact, you don’t even need to set anything up – they’ll have a report ready for you as soon as the email campaign has been sent. In the report, you get pretty decent metrics.
Here is a sample of what you would see from an email-marketing provider:
Open Rate – the number of people who opened your email as well as the total number of times your email was opened.
Action: If you have a low open rate, let creative juices flow and come up with more compelling subject lines. Test sending at different times of the day, different days of the week, etc.
Click Rate – the number of people who clicked a link in your email as well as the total number of times links were clicked in your email.
Action: More than likely, the purpose of your email is to get the reader to take action. More often than not, that’s to click on something and go somewhere on your website. If this metric is low, maybe the quality of your content is not where it needs to be. Maybe the offer is not that compelling. Also, make sure your links and “Calls-to-Actions” are visible; the goal is to get more interaction with customers.
Bounces – the number of people who didn’t get your email e.g. their email account could not be reached.
Action: To avoid bounces, make sure you collected the list of contacts yourself by having a sign up list on your site, or having them opt-in to receiving special offers from you once they make a purchase.
Unsubscribes - the number of people who removed their email from your list, using the subscription management link (email platform will always include this on emails sent through their system) at the bottom of the email.
Action: To avoid unsubscribes, make sure the information you are presenting to your customers is relevant to them. When initially creating your list, having subscribers opt-in would most likely decrease this too, since they’ve chosen to hear from you. Most likely if you added someone without their permission, they may not want to be bothered and unsubscribe. Also, maybe you’re sending too many emails? That can be annoying and cause someone to unsubscribe.
Forwards - the number of people who forward the email using “Forward to Friend” at the bottom of the email. The email platforms can (should) not capture data of people clicking the actual forward link in their email client.
Action: You’re doing something right if this is high, if your customers are forwarding to their friends! Keep it up!
Complaints – the number of times a contact reports your message as spam in their email clients.
Action: Similar to unsubscribes, to avoid complaints, make sure you are not spamming your customers, don’t send multiple emails a day and make sure you are sending information that is relevant to them. A great way to ensure people don’t unsubscribe is segmenting your contacts into lists of content that is relevant to them, this way they are only receiving content that they signed up for.
Now if you have been reading our blog and follow our Reporting Framework, you know that you should be trending your KPIs, and you could do that easily in Excel and come up with something like this:
WOW! What happened to our open rates and click-through’s in Feb!! We can see some issues, so now we can take action!
Post Click – Tracking in Google Analytics
Hopefully, you can tell this is all great information for the email blast itself, but what happens after your email subscribers clicked on the link in your email and landed on your website? This is where Google Analytics comes in.
The email platform will allow you to track the amount of clicks and opens for your blast. But what web analytics platforms such as Google Analytics will do, if you have it set up on your website and have properly tagged your emails, by connecting the two, you get insights on what happens after they’ve clicked the links in your email. See how engaged your email visitor is with your site.
Tagging and Segmentation
Adding a simple tag to the links on the email blast will allow you find out:
…if they convert
…fill out a form
…watch a video
…and much more.
This is obviously quite useful, especially if you have eCommerce set up in Google Analytics you can track revenue per email campaign.
Tagging properly to segment your visitors in Google Analytics can be useful when trying to figure out what works best for particular audiences. For example, let’s say you’re having a sale and want to see if “20% off” would capture more attention than “Free Shipping”. The first thing would be to segment your list. Segmenting will allow you to send the same email blast to different sets of people or you can even send two different emails based on your audience to see which performs better. The first email will have a subject line of “20% off your purchase today!” and the second email will be “Buy now & get free shipping.”
Now that you’ve created two blasts, you can add utm tags. A utm tag allows you to make each link unique by adding fields that will appear in Google Analytics reports. To generate this unique link, use E-Nor’s URL builder or another awesome tool for tagging is Campaignalyzer.
When using the URL builder, there are three required fields:
Campaign Source is where your traffic is coming from. For example, if you paste the link on “Facebook”, and want to track the visits from there, you can use that as your source. In the case of email tagging, you can use it to identify your segment type. For example, use “leads” for a email blast to your leads list. You can use “prospects”, “customers”, “male”, “female”, etc.
Campaign Medium is a marketing medium, or in other words, the “channel” you are using. In this case, it should always be “email” when linking from an email blast.
Campaign Name as it says, names your campaign. For example, you can use “April Newsletter” when linking from an email blast for the monthly newsletter in April. You can use the month and year, or even more specifically use the actual day that you are sending it on. You can also use the name of the product you are promoting in the content. If you are sending out newsletters on a regular basis (daily, weekly, monthly, etc.), we would suggest using the date for the campaign name, because it will make things easier when you are looking at reports. Also, if you are testing to see what type of email is getting more conversions, then you will want to use the campaign name to differentiate the emails.
Tip: Always test that your tagged urls appear in the browser and in Google Analytics! You never know what can happen…
Now that you’ve tagged your email, the data will be found under medium as email traffic for your deep dive analysis.
You can also trend data over time and see if there are seasonal impacts to your user’s behavior. You can see how many people continued ‘shopping’ on your site and even if they ended up purchasing/converting or not. If you are doing A/B testing on which email to send out to all your customers, you can analyze between both sets of data and then make a decision about which offer resulted in more revenue or micro conversions.
The above reports are all dandy, but we are still looking at metrics in isolation. Analysis and optimization is all about context. What if you like to view the entire experience in one report, you want to see the number of list subscribers, the open rate of a specific campaign and the associated revenue in one report? Sure, you could do it in Excel, but that’ll be a lot of work.
What we recommend is automatically pulling data out of Google Analytics into Tableau and then be ready for some serious slicing and dicing (for now, you still have to pull the email providers data from a csv file and into Tableau). Again, if you follow our articles, here we are featured on the Google blog explaining how to do that).
Here’s what you’ll see, a nice dashboard in Tableau showing key campaign metrics nicely trended for four email newsletters (NL_1, NL_2, NL_3, NL_4):
Clicks (of those Opens, how many clicked and visited your site)
Number of transactions
(you can also plot Open Rate, Subscriber/list Growth Rate, Time on Site, email visits from Mobile, etc.)
Analysis note: it’s obvious that the Newsletter 4 (NL_4 in red) just tanked in every aspect so address it immediately. It’s also worth noting that while the Newsletter 3 (NL_3 in green) had less transactions than the Newsletter 2 (NL_2 in orange), the revenue number for NL_3 is slightly higher. This indicates that your average order value is higher and whatever you did to upsell or promote higher ticket items worked!!
Mobile Analytics & Engagement
Don’t forget to assess your users mobile experience and expect that more people are using the mobile phones and tablet to access email, browse and shop. Go to your mobile reports and segment by “medium” and select the “ecommerce conversion rate” metric. You’ll quickly see that your mobile users convert at half the rate than your desktop users!! A quick “lost opportunity” analysis will convince your manager to invest into a responsive design for your site or maybe a mobile site.
This will be the subject of a more detailed blog post, but since Universal Analytics is the future, start thinking of what metrics you want to pull into Universal Analytics from your email marketing efforts. Passing a “user id” (ensure it’s don’t include personally identifying information) is a good start. Work with your email providers to pass the “user id” with the click/visit and then once once the visitor clicks the email link and they are on your site, grab the “user id” and store it in a Custom Dimension. You can then report and export your reports (with user ids) into your BI tool.
Filter out auto-respond emails, confirmation emails.
Scenario: A user arrives at your site via an organic search. The user performs some action which results in him receiving a system generated email containing a link back to the site (for example, an account activation email). If the user clicks on the link to go back to the site, it’s very likely the medium of the original visit will be overwritten to Referral, particularly if the user is using a web-based email client. (In the case of Microsoft Outlook, this would be considered a Direct visit, but the medium wouldn’t be overwritten since returning Direct visits don’t override the original medium.) The “no override” parameter shown below prevents this problem from manifesting. The parameter utm_nooverride=1 can be added to all system generated e-mails, such as registration and password reminder e-mails. For example, a password reset link such as:
Can be updated to
Attribution & Multi-Channel Funnels (MCF) for your email marketing program:
Keep in mind that we all browse many sites before we buy or submit a request for more information. And we are likely to revisit the same site many times before we do so. To see all these touchpoints and how your email channels contributes and assists conversions, make sure you review the MCF reports in in Google Analytics. Here is a snapshot at the Top Conversion Paths along with the number of conversions and conversion values for each path. It takes some of us 5 emails to convert!!
Here you have it! Any other email marketing analytics tips you like to share?
The average time spent by visitors on your website is four minutes. Is this good? Or is this something to be worried about? You begin to evaluate the time spent per visit and asked yourself questions such as:
Is this enough time to complete an e-commerce transaction?
Are visitors reading enough quality content in that four minutes that will motivate them to subscribe to the email list?
Are visitors getting enough information for interest in the Contact Our Sales Team form?
And while all of these concerns may be valid, it comes down to a simple plan of evaluation and determining exactly what information you want to gather in order to reach a given outcome. Time-onsite metrics can often be very misleading when the data is viewed in aggregate, and no segmentation is applied. And the metrics are even more misleading when used to make site optimization decisions. What is missing from the standard conversion reports is a metric I believe is very important for analysts to have in order to accurately optimize the conversion funnel based on visitor’s behavior and need. This metric is “Conversion Duration” which I define as, “the time is takes a user to complete a purchase or a Goal from a defined starting event.”
I am currently aware of two e-commerce reports that are available today in Google Analytics (GA) to time track a purchase. In my humble opinion these two amazing reports (Days to Transaction and Visits to Transaction) still lack three main features:
They are limited to the e-commerce transactions and cannot be applied to track conversion time of any other micro or macro conversions (i.e. form submission, email subscription, enrollment application, etc.)
They are not applied at the session level, so we can’t tell how much time (in seconds or in minutes) a particular Goal takes to be done during the same visit.
They are applied for the last campaign only which make these metrics less robust and tell a very partial story.
So now, the question is, how do I calculate this metric?
First Things First – Determine your Goals
Whether the purpose of your website is lead generation, e-commerce, content or media, you must first define goals in your analytics tool. Do this in order to track conversions and also to track the time users take to make an action.
A Goal conversion can be a variety of things, depending on what your desired outcomes are. It could be an event registration, whitepaper download, form submission, video completion, or a product purchase. In your analytics tool you’ll be able to see the conversion rates and number of completions for each Goal you have set up. (Read more here about Google Analytics Goals.)
While tracking the number of Goal conversions is the basic metric for measuring how well your site fulfills your business objectives, other metrics need to be associated with the conversion rate to deeply understand the customer behavior both before and after the conversion.
Define your Starting Point
In order to accurately track the time is takes visitors to make it through a given process that you set for them, we need to define the starting point. This can be entering first page of a six-page application form, or when they reach the Add-to-Cart page for an e-commerce funnel, or even the Contact Us page. Regardless of the Goal that you are trying to track, make sure the starting point is an event that all visitors are required to go through in order to complete the conversion.
Develop Metric Calculations
Now after defining the starting and final conversion points, we need to set a timer between the two points. This Conversion Duration metric is calculated using the following simple equation:
Conversion Duration = (t2 – t1)
t1 = The timestamp of the first success event (i.e. landing page, add-to-cart, about-us page, etc.)
t2 = The timestamp of the second success event (i.e. form submission, thank you page, transaction confirmation page, application confirmation page, etc.)
How to Track the Conversion Duration in Google Analytics
While there are various ways to report the calculated metric to GA, in this post we will use the relatively new feature, User Timings, to pass the period of time spent in the conversion. With the new introduced feature you can track and visualize user defined custom timings about websites. I will provide you with the code needed to capture the conversion duration.
The easiest way to implement this is to create a timestamp at the starting point and create another timestamp at the completion of the Goal. Then, we calculate the difference between both timestamps and pass it to GA.
Here’s the process:
Create a timestamp at the defined starting point.
t1 = new Date().getTime();
Save the timestamp in the cookies or in the backend.
Create a timestamp at the end of the conversion.
t2 = new Date().getTime();
Calculate the time duration from start to the Goal completion. (In GA the time difference between the two timestamps is in milliseconds)
Once this data is collected, the report will consist of the Conversion Duration metrics as well as the number of Conversions, as seen below.
Go to Content > Site Speed > User Timings to see your data.
So there’s our recommended process for developing the metrics and calculate tracking using Conversion Duration in Google Analytics. This will provide you with the steps to reach your business goals when it comes to determining the passing period of time in site conversions.
We would love to hear your feedback on how you’re planning to utilize this method to work for you! Please share your thoughts with us and the analytics community
Previously, Google Analytics had only 2 roles (“Admin” and “User”), which are very limited. They announced today that they’ll be expanding the flexibility of access – which is good news for anyone that has multiple hands in their Google Analytics accoqunt cookie jar (you have multiple accounts/properties/profiles but want to give…
…different employees different access/security roles to specific properties/profiles.)
…particular clients/agencies view or admin access to specific properties/profiles, etc.)
Google Analytics Accounts – this is the general account you set up for analytics. It would be on an organization basis. Example, an analytics account for E-Nor, Sony, Proctor and Gamble, etc. This is the large bucket and you get an assigned ‘UA’ number.
Properties – Under the account, you can have multiple “properties” – website 1, website 2, mobile app, etc.
Profiles – Within each property, you can have multiple profiles. Maybe for your website, you want a profile that only shows E-Commerce data. Another example, say you’ve filtered out all your company traffic from your profiles so you only see data from “visitors”, not your developers doing work on your site. You also have a backup profile (always have an unfiltered control back up profile!!!). Etc.
Users – In order to give someone access to a Google Analytics account/property/profile, they must have a Google Account.
The “Old Ways” and its Limitations
As it works now, the user permissions are pretty limited. You can only have admin access at the account level (all properties/profiles under the sun). Nothing in between.
If you have multiple properties (say website and mobile app), and you want to give a specific user/client admin access to only a portion of that (say, yet you want say the website development team to only have access to the website property/profiles), this wasn’t possible.
User “View Only” Access per Profile
Also, you could only give users “view only” access per profile. If you wanted to give users “view only” access to all profiles within a property, you’d have to manually select each profile under that property and give them access.
Enhancements and Improvements
User Permissions at Every Level!
Analytics users have been requesting more granular user permissions. Today, we got the answer from the Google Analytics Blog. They’re expanding these options and will allow you to basically set access at every tier. Set users to have view/admin specific to properties, profiles, and/or the entire account. No more worrying about a user having too much admin access. No more having to manually select profiles per property – you can set access to whole properties.
We now have the ability to give different access specific to each tier.
For example, while a user can now have permission to say view the entire property, you can also limit their admin access within that property (per profile). Example, give the website developers access to view the entire web property, but only edit the E-Commerce profile.
The only trick is admin access inherits permissions from its parents. Meaning, if you have full account admin access, it wouldn’t make sense then to only have “view” access to specific properties/profiles under that account – you have full access.
New User-Role: Manage Users
We know that today Google Analytics has 2 roles of access – “admin” access (which gives users permission to edit Google Analytics accounts/properties/profiles) and “view only” access.
They’ve now added a third role called “Manage Users”, which allows that that user to add and delete other users as well as assign them permissions. This is different from “edit” and “view” permissions.
Pretty cool! Give certain employees/agencies specific access so they don’t mess up other profiles! (NOTE: Your account may not yet have this feature, but Google is working on migrating all accounts to have this within the upcoming weeks, so keep checking for it).
A couple of weeks ago, I wrote a post about marrying qualitative and quantitative data, giving recommendations on how to conceptually combine both types of data for more useful insights. For the savvy marketers and the analysis ninjas out there, you want a tighter integration, and of course, more segmentation on the qualitative data. Visitors told you “No, I didn’t accomplish what I came to the site for” and “that pricing was too high”. Now, maybe you want to know…
…where these “No’s” and “Yes’s” are coming from
…what content they are consuming
…what campaigns are driving these segments so you optimize at the source
Google Analytics – Quantitative Data Tool of Choice
It’s no secret that Google Analytics is our web analytics platform of choice. It’s a “monster” when it comes to providing web usage stats. It’s the gold standard. And as far as pricing, the cost benefit is unbeatable – it’s free (and if you want more data and enterprise analytics consulting, Google Analytics Premium is there for you). When planned and implemented right, you can get a wealth of qualitative data on your website – what pages are visited, where they come from, what keyword they searched for, how long they stayed, who converted – etc etc etc.
Qualaroo – Non-Invasive Voice Of Customer Survey
As far as qualitative data, Qualaroo can be your best friend. As an internet surfer, I’m sure your feelings are consistent with the rest of the world – forms and surveys are kind of annoying. They’re long, tedious, and often a waste of time. What we like about Qualaroo is how non-invasive it is. A small question will pop up and a visitor has the option of quickly answering it, or quietly dismissing it. We feel this increases the likelihood of it being answered.
We also love its configuration flexibility. “Nudge” the question after 30 seconds. After a visitor has visited 2 pages. Publish the survey from a certain date, shut it off after a certain date. Display only on certain pages. Etc. Note: to integrate Qualaroo data in Google Analytics, you need to sign up for Qualaroo’s enterprise edition.
Google Analytics and Qualaroo Integration
With the ability to integrate Qualaroo data into GA, you now have a very powerful surveying, measurement tool. You can see “what’s” happening on your site by looking at the Google Analytics metrics. Then, with Qualaroo integrated into Google Analytics, you get a deeper understanding about “why”. Google Analytics itself will tie the connections between your qualitative data and quantitative data, between your “what” and “why”.
ROI by Channel
Here’s a simple example. Your company sells a SaaS product targeting CMOs and Marketing Managers at medium and large companies. You have your paid search campaigns running on AdWords and Bing and you want to expand into new paid social ad campaigns. You have ads on the following social networks:
Your landing page is converting, but it’s not converting like it should be, and you’re looking to really cut down your ad spend and optimize ROI. Your quantitative numbers tell you the following:
Your spend is about equal (budget was set by yourself).
There actually is a lot of traffic from Facebook and Twitter and LinkedIn.
However, it looks like you are getting very few conversions.
“Why is that?”
“Should you continue spending on these channels?
If you shut down these campaigns, what opportunity are you missing?”
Thus, we add the following survey:
Your goal is to understand what’s happening and why your visitors can’t find what they are looking for and thus not converting. With Qualaroo Enterprise version enabled, some cool Qualaroo event user interaction can be reported in GA (an event is fired based on user interaction with the survey). The image below shows the number of events when responders answer “No, we didn’t accomplish what we came here to do”. Here is what we see in GA (go to Content –> Events –> Top Events –> and then click on the Qualaroo Enterprise Event Category):
Your first reaction is , so many people (and a high percentage of the total responses) can’t find what they are looking for, no wonder they are not converting. Time to dig deeper and segment.
As we know, once you have the event captured in GA, you can make it a goal or segment on it in whichever way you like. In our case, we want to understand where the No’s are coming from. Let’s take this specific event and segment the report by channel (apply secondary dimension to the Top Events Report) and voila! You have the channels responsible for driving the unengaged visitors.
In the snapshot above, you see LinkedIn is a potential culprit here. We love LinkedIn and we’d expect it to generate high value leads, what’s going on here? Our paid ad LinkedIn campaign appears to be bringing visitors who are not interested in the SaaS product. After verifying the statistical significance (and correlating the number of “no” events with the traffic volume from the respective source) and looking at some of the survey responses, so of the answers to tell us why you didn’t find what you came here for were very revealing, here is a sample of these answers, once you read them, you’ll know exactly why the campaign is not converting.
”I can’t find the technical product description”
“your product appears to be solid, but I am interested in customization features and API import/export capabilities”
“how technical does the system admin need to be, I can’t tell from the info provided”
“I am a system admin and I need to know your system up-time and technical support you provide, can’t find this information”
Most of the answers/comments were of a technical nature, and appears to come from IT folks and your LinkedIn ad campaign (including the landing page) is all designed around speaking to the CMOs!
These insights are very actionable. Two immediate actions are now taken to adjust our targeting options, and really optimize our ROI (by maybe putting our budget towards these better channels).
Cost savings: Enhance the LinkedIn targeting to marketing managers
New opportunities: create a new campaign/new landing page with information requested for the IT folks.
ROI by Keywords
Now, say you’re spending on Google AdWords. You really want to know if specific campaigns or keywords are driving the traffic and unengaged visitors.
Again, we take the specific event and segment the report by keyword (apply secondary dimension to the Top Events Report) and voila! You have the culprit keywords.
Is this super insightful or what?! (keywords blurred to keep our clients identity anonymous…)
Stop bidding on these keywords or direct traffic from these keywords to a lower price-point product and see your sales go up like you’ve never seen before!
Here you have it, if you feel like you are hitting a wall and not sure what to do to improve your conversion rate, go back to the basics and “listen to your customers”!
How have you used voice of customer tools to improve your site and campaign performance? Very interested to hear your stories.
“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
When Google Analytics makes changes to their platform, it’s usually a good thing, and helps users navigate through the dashboard easier, offers a more powerful data experience and overall is seen as beneficial to the user.
Google Analytics did just that this time around, as they rolled out some improved features earlier this month. We at E-Nor dove right into the changes and have been loving them.
The first change you notice when logged into Google Analytics is there are less tabs at the top of the screen. Just the simple Reporting, Customization, Admin and Help tabs are now available here. This area had been freshened up a bit, and some of the reports here have been moved to the left sidebar. We’ve noticed this definitely makes more sense, and offers up a more unified placement for the tools. Plus, the top orange navigation bar floats as the user scrolls down the page. Pretty cool!
Create Your Own Custom Dashboard
We all have our own preferences, right? So too is the case when working with Google Analytics, and the gurus at Google have figured that out! The platform now offers new enhanced personalized dashboards. Users can choose from a variety of layouts, giving them a handful of options available. This feature expands the way the dashboard is laid out, and how users can see their data.
1. Advanced Segments
Anyone who works regularly in Google Analytic is aware of the Advanced Segments feature. Well, thanks to this most recent round of changes, this tool has been added to the dashboard. (Yay!) Users can find this button in the upper left section of the dashboard near the Audience Overview header.
2. New Widgets
The Geo Maps and Bars widgets are both new additions to the Google Analytics dashboards. You will also find the Geo Maps have been added for custom reports. These are available on the improved dashboard, and provide yet another set of data gathering tools that help users. The Geo Maps widget allows users to color code data by country, state and so on. The Bars widget give more advanced graphic data abilities.
Examples of Widgets
So if you haven’t already noticed the improvements to the Google Analytics interface, now is a good time to jump in and check them out.
We at E-Nor have found these new and/or revised features and tools highly beneficial, and love the fact that they allow us to continue to provide top-notch analytic services to our clients. We hope you enjoy the changes too!
There are so many screens, features, tools, filters, searches, etc. For the heavy data cruncher, it’s always nice to have a set of shortcuts for quick execution of common tasks. In case you couldn’t find it on the Google Analytics Blog, we laid them out for you.
Here are a list of keyboard shortcuts in Google Analytics:
Date Range Shortcuts
Set date range to TODAY
Set date range to YESTERDAY
Set date range to LAST WEEK
Set date range to LAST MONTH
Toggle date comparison mode (to the previous period of whatever you are looking at. Example, if you’re looking at 6 days, this will compare it to the 6 days before it)
Toggle date comparison mode (to the previous year of the period you are looking at)
Open keyboard shortcut help
Search help center
open account panel
shift + a
Go to account list
shift + d
Go to the default dashboard of the current profile
Some of them not working? If you’re a genius like me, it’s probably because you pressed one of the keys on accident and it took you to the search box. Make sure you are out of the search box when you try these.