1 02, 2016

How to find Bot traffic and segment it out in Google Analytics

By | 2017-07-20T09:23:04+00:00 February 1st, 2016|Categories: Google Analytics|Tags: , |

Recently, I had a client come to me with this question (and mind you, we don’t manage Google Analytics for them. They were consulting with us on this problem):

“My traffic for Q1 has grown 86% YOY but they are not buying on my site. Is there something wrong?” 

My first thought: 86% – Whoa! – that’s some serious growth! My second thought: No way that can be real traffic growth (knowing this client doesn’t do much SEO for their site). So, I wondered if this issue is bot related. I jump into the data and start digging around…

Here are the steps I took to figure out the problem and fix it.

1st – Figure out where the increase in Traffic came from

To do this, I pulled session data by medium for Q1 YOY and right away I see a huge increase in traffic related to one medium….Direct. To be exact it was an increase of 376%, almost 134,000 visits! Now I’m definitely thinking my assumption about it being bot traffic is right.

google analytics

 

2nd – Find the Bot Traffic

Now that we know the increase is related to direct, I start looking at ways to figure out if its bot traffic. I move on to look at Browser traffic. Right away I see Chrome had a significant increase in sessions and new users.

Chrome - Google

So now I know I need to look deeper into Chrome and click to see the browser versions.

browser bot

Low and behold, the very first browser version 39.0.2171.95 shows an increase in session by 2,528% and new users by 3,690%. At this point I was totally getting all giddy and excited. You know that feeling you get on Christmas morning when you’ve just woke up and you can’t wait to see what presents you got but you have to wait just a little while longer on the rest of the family to wake up. Well that was me. I was so excited and anxious, knowing I was so close to getting the answer and fixing the problem but wasn’t there quite yet! (Insert childish grin here.)

Ok – so back on track now. We know the issue is coming from Chrome and specifically version 39.0.2171.95. And we know this is the issue because sessions drastically increase, bounce rate is 99.85%, time on site is 00:00:01 and there is no revenue. (I mean come on, I know the site needs improvements but it’s not that bad!) And remember this is for all traffic, no filter has been applied yet. Now I want to see if any of the traffic coming from this browser is good traffic or not. So I add a secondary dimension for medium. I can see that there is some good traffic tied to other mediums but majority of the bad traffic is direct.

So now I turn on an advanced segment for direct traffic and turn off all sessions. After doing that, I change the secondary dimension from medium to landing page to see if I can narrow down a page that is being hit.

browser bot chrome

As luck would have it (and as I had assumed), the homepage showed a huge increase in sessions. So given all the information, I now had I could safely make the assumption: It was a bot causing the increase in sessions to the site and the problem was coming from Chrome and the homepage was involved. Using all that info, I can now set up an advanced segment to filter out the bot traffic.

 3rd – Set up an Advanced Segment to Filter out Bot Traffic

To set up the advance segment, click the + sign then click on Conditions in the left navigation. Now fill in the field using this information:

advanced segment for bot traffic

But because I’m super nice, here is a direct link to open and save the advanced segment in your Google analytics account: http://bit.ly/1nD00GH (Keep in mind you’ll need to tweak some of the fields based on your sites data such as landing page.)

You’re welcome ;)

 4th – Review the Data

Now that the advance segment has been saved, I turn off the direct traffic advanced segment and add back the all sessions segment. Once that is done loading, I return to the all traffic>source medium report and switch the primary dimension to medium. I now can see that only direct traffic shows a change in sessions and the behavior stats look a lot better. I also double check no other mediums were affected by the advance segment and make sure sessions numbers match for exclude and all sessions…which they do. So we’re good to go.

As a disclaimer – looking at the browser report I could see it looked like some bot traffic might still be coming through by the number was so low that it wouldn’t be a problem so I decided to leave the advanced segment as is instead of adding anything to it.

 

 

20 01, 2016

How to Set up a Custom Report for eComm Conversion Rate per User

By | 2016-04-18T09:48:04+00:00 January 20th, 2016|Categories: Google Analytics|Tags: , |

I love analytics and all the information that can be extracted from the data. I happen to work with quite a few ecommerce clients and we are always looking for ways to improve online revenue. Each month we comb through the data and most of the time are always concentrating on revenue and eCommerce conversion rate. While this metric is great, I feel like it doesn’t provide enough insight into the users of the site.

As a reminder – eCommerce Conversion Rate = sessions / transactions

Sessions are generated by Users. 1 user can have multiple sessions. However you can’t have 1 session with multiple users. So I wanted to see what the ecommerce rate looked like based on Users of the site and not just sessions. In order to extract this information, I had to set up a few things in Google Analytics.

 

Steps for Setting up eCommerce Conversion Rate per User

1st Set up a Calculated Metric

  1. Go to the admin section of your account then open up your default view.
  2. Click on Calculated Metrics
    • Click to add a new calculated metric
    • Fill in the form:
        • Name = eComm Conv Rate Per User
        • Formatting Type = percent
        • Formula = {{Transactions}} / {{Users}}
        • Click Save

      calculated metric in GA

2nd Set up a New Custom Report

  1. Now go to the Customization Tab. (Top Navigation beside Admin)
  2. Click to add a New Custom Report.
  3. Now you need to fill in this form and choose your metrics.
    1. Title: eComm Rate per User
    2. Name: You can name this whatever you want to call the tab. I used the title over.
    3. Metric Groups: Choose Sessions, users, ecommerce conversion rate, and then ecomm conv rate per user (the metric you set up).
    4. Add a dimension: I choose to add medium, but you can choose any dimension you want to see Source/medium, campaign, source, etc.
    5. Next, choose the views you want this report to be available for and click Save.

 

custom report

Now your new custom report will generate and you can compared the metrics.

Here’s an example:

ecomm_conv_rate_metric Pretty cool huh?! Now try setting it up yourself.

 

8 09, 2015

Google Analytics Goal Conversion and eCommerce Transaction Counting

By | 2017-07-20T09:14:59+00:00 September 8th, 2015|Categories: Google Analytics|Tags: , , |

Did you know that goal conversions and eCommerce transactions are counted differently in Google Analytics?

Goal Conversions

Each Google Analytics goal conversion will count a maximum of one time per user per session. While the All Pages report may show three pageviews of the goal URL by the same user, there will only be one goal completion counted. Similarly, a user could trigger the same event multiple times in a session. If that event is also configured as a goal, that session will only show that goal converting one time for that user. This is important to know, especially if you reconcile email submissions against your goal total in Google Analytics.

eCommerce Transactions

Unlike goal completions, a user can register multiple transactions in Google Analytics during the same session. This is intended to account for instances when a user decides to complete more than one purchase without leaving the website in between purchases, keeping your revenue information as accurate as possible.

Duplicate eCommerce Transactions

While it is great that every eCommerce transaction will count in Google Analytics, this truth extends to unintended duplicate transactions. Here are examples of how an unintended duplicate transaction can occur:

  • The user refreshes the purchase confirmation page.
  • The user exits the browser on a mobile device, opens the browser later, and the browserautomatically reloads the purchase confirmation page.
  • The user bookmarks the purchase confirmation page and visits the page one or more times untilthe purchased products are received.
  • The user emails the purchase confirmation page link, and the page is accessed through thelink.

In each of these cases, another transaction, with all the same product and transaction information, registers in Google Analytics. There is no setting in Google Analytics to prevent duplicate eCommerce transactions.

An easy way to check for duplicate transactions over a given date range is to import this custom report from the Google Analytics Solutions Gallery. The report will display all transaction IDs with more than one count.

In order to prevent duplicate transactions from occurring, you need to: a) not allow the confirmation page to load more than once, or b) make a server-side update that only allows the Google Analytics eCommerce tracking code to load once. Need help with this type of fix? Beacon is one of the longest active Google Analytics Consultants in the market.

19 08, 2015

Why Should I Put UTM Tags on 301 Redirects?

By | 2017-08-08T08:21:42+00:00 August 19th, 2015|Categories: Google Analytics|Tags: , |

So you probably just did a search for something like ‘Why Should I Put UTM Tags on 301 Redirects?’ Awesome, you’re being proactive and realized that you’re missing out on data and attribution. This is a practice I’ve been using for about a year now, there are many applications for tagging redirect URLs with UTMs and I’ll address a few of them here. The Cliffs Notes version though is this: UTMs on the resolving URL of a 301 redirect give you better attribution in Google Analytics, and help you identify 301 redirects that are no longer need and could be slowing down your site.

If you’re a web developer, webmaster, or digital marketer, chances are pretty good that you’ve been involved in 301 redirects at one point or another. Whether it’s another domain you’ve purchased, a dead page, or products being removed from your eCommerce site, there are plenty of reasons to implement a 301. Users still get where they wanted to go, search engines don’t ding you for dead URLs, it’s a perfect solution to page removals right? Well, that is until you look at data in Google Analytics. The problem with 301 redirects is all the traffic coming from a 301 appears as ‘direct’ traffic in Google Analytics. ‘So what?’ you may ask yourself. There are a couple of use-cases where you definitely want to know what 301 redirects are sending traffic to your site.

301

Use-Case 1: Offline URL Presentation

Ways in which you might be doing this:

  1. Domain redirects – i.e. yoursite.co redirects to yoursite.com – you might use the .co version in your collateral
  2. Vanity URLs – i.e. yoursite.com/promo redirects to yoursite.com/annual-fall-sale – it’s much easier for people to type /promo and you handle the rest

Kudos to the marketers for using vanity URLs, or purchasing other domain variations for these uses. HOWEVER, 99.99% of the time I see either one of these implementations, they’ve made one crucial error. Not. Using. Tracking. Parameters. If you’re just doing basic 301 redirects for these cases, you’re missing a huge opportunity to analyze how much traffic was driven, and how the users engaged with your site once they landed there. The solution to this problem is ridiculously simple; UTM parameters. If you’re not familiar with these parameters, check out Google’s URL builder for some assistance. You’ll need to identify a source, medium, and name (name is actually optional, but Google makes it required), then append it to the end of your destination URL. This way your redirect doesn’t strip anything out, and your landing page has the parameters built in, feeding important data straight to your Google Analytics account. For medium, always enter ‘301’, and for source, I like to do the referring URL. Here’s what mine would look like for the examples provided:

  1. yoursite.co >> yoursite.com?utm_source=yoursite.co&utm_medium=301
  2. yoursite.com/promo >> yoursite.com/annual-fall-sale?utm_source=yoursite.com/promo&utm_medium=301

Here’s an example in action: ga-fusion.com is the domain we use for our GAFUSION product, but you’ll notice when you click on that link, it takes you to beacontechnologies.com/technology/products/gafusion?utm_source=ga-fusion&utm_medium=301.

Use-Case 2: Removed Pages

Why might you remove pages?

  1. You run an eCommerce site and stopped selling a particular product
  2. You have some old, non-relevant pages that you just don’t want people to see anymore
  3. Two pages exist that have same/similar content (it’s easy for this to happen on large sites)

It’s obvious that if a page is removed, something needs to be done about it. You don’t want to provide a poor user experience, and if you’re concerned about SEO management, you want to make sure you let search engine bots know what happened to that page. The main difference in this use-case for UTM parameters isn’t necessarily for tracking and analysis purposes. With these types of 301 redirects, UTM parameters will be helpful in determining which 301s you can eventually remove. It’s no secret that too many redirects will slow your site down, but how can you tell which ones are adding value and which ones to nix? UTM Parameters, that’s how. Using the same methodology above, append your parameters to the destination URL, still using ‘301’ as the medium and the referring (dead) URL as the source. The difference is, we’re not going to use this to understand behavior of these users, we’re going to use this to see which 301 redirects are no longer needed. Login to Google Analytics, and go to Acquisition > All Traffic > Channels then click on ‘Source/Medium’ as your primary dimension, then apply an in-line filter for ‘301’. Choosing ‘Landing Page’ as your secondary dimension will provide you with a list of all the 301 redirects that are sending traffic to your site. Once enough time has passed that your comfortable saying ‘OK these redirects have contributed nothing in time period XYZ’, you can remove that 301 redirect. This will help you manage your list and not have unnecessary redirects slowing down your page load times.

***Edited to Add a Third Use

Use-Case 3: URL Shorteners

While this technically doesn’t fall into the category of an internally implemented 301 redirect, I’m still going to address this one.  It occurred to me while sharing this article on social media sites that I left out one crucial use-case, shortlinks! Everyone loves a good URL shortener, Bit.ly, Goo.gl, Ow.ly, and so on. They make links much more presentable, especially for Twitter where character count matters. But once you shorten that URL, you lose all of the source/medium information that Google Analytics would normally pick up on automatically. So how do you solve this? Easy, add your UTM parameters to the URL before you drop it in your shortener. If you’re not doing this, all of your short links are feeding zero useful data into Google Analytics and your analysts will scream in agony at all the ‘direct’ traffic.

Have any other use-cases where you would apply UTM parameters to 301 redirects? Let me know in the comments!

14 07, 2015

Case Study: Medical School Uses Google’s Async Code to Provide Accurate and Flexible Tracking

By | 2017-06-16T12:44:43+00:00 July 14th, 2015|Categories: Case Studies|Tags: , |

Updating Website to Asynchronous Tracking Code from Traditional Tracking Code Follows Best Practices, Improves Site Performance, and Allows for Greater Flexibility in Code Installation.

Challenge: Client was re-launching website in a new format which offered an opportunity to update the site’s existing traditional Google Analytics snippet to the asynchronous tracking snippet. In addition to staying on the cutting edge with Google’s best practices, this was done to improve site speed and also produce more accurate results. This would also provide Beacon some added flexibility in where the snippet could be placed and still perform at optimal levels.

  • Client Facts:
  • For Profit Medical & Veterinary School
  • Valued at $115M in 2008
  • Faculty size greater than 200
  • 2000+ Student body hails from 24 countries six continents
  • Goals:
  • Update website with Asynchronous tracking code for GA for optimal flexibility of code
  • Improve site performance in both speed and accuracy with installation
  • Installation Notes:
  • Tracking code moved into header file for consistency and easier maintenance
  • Virtual Pageviews and Events were updated in order to track users who accomplished a predetermined step or goal completion
  • Results:
  • Client’s tracking script adhered to Google’s best practices and works at the optimum load time and accuracy levels available through GA

 

Business Solution: Previously the Google Analytics tracking code for the client’s website was located before the closing <body> tag towards the end of the page. This was considered an ideal location for this JavaScript snippet because it gave the page an opportunity to load prior to firing. However, due to the structure of the client’s website, this involved the code being included in a number of template files in order to be consistently rendered across every page. Any update to the code required changes to all of these files which increased the potential for errors.

Google’s updates to the asynchronous tracking code offered a greater flexibility than the traditional snippet. When the client re-launched its site to a new Drupal format, this provided a great opportunity to upgrade to the new code which could be placed in a universal header file and still function with a greater accuracy than the previous version. From this point forward, any changes made to the code could be made just once and would be applied site-wide.

Changes to the actual code involved adjusting to the new format. The traditional code used the pageTracker function for its tracking operations. The new async. code is built around the gaq.push function. Once these changes were made to the primary tracking snippet, the final task was to go through the site’s pages and ensure than any virtual pageviews or event tracking were updated to the new codes as well. These represent instances where specialized tracking code snippets are inserted at the point of action to display specific events in Google Analytics. Any instance where this was previously tracked under the traditional snippet was replaced. Beacon was able to conduct a global find and replace to work more efficiently to minimize client hours used.

Results: The adjustments to the asynchronous snippet were made without issue. The client also appreciated that the upgraded tracking code would lead to quicker load times and better accuracy for their Google Analytics data. The new site invested heavily in a number of flash elements, so load time for all installed scripts was critical to ensure a high quality user experience. In terms of accuracy, the client services students hailing from all over the world. Having the most accurate data on segments from each region helps to determine marketing strategy and financing for various countries around the world.

20 01, 2015

How to Check Goal Conversions are Set Up Correctly in GA

By | 2017-05-31T11:46:10+00:00 January 20th, 2015|Categories: Google Analytics|Tags: , , |

I absolutely love that Google Analytics has the Real-Time Reporting section that allows you to see many different options in “real time.” Now, when you are testing out new goals you’ve set up, to make sure they show up correctly in GA, you don’t have to wait a few hours to see the data. It will populate in real time while you’re on the site clicking, which is very convenient – don’t you think?! I use this feature every time I set up a new goal to test it works correctly.

Here’s how you can use it too.

Step 1

Set up a new goal in GA. As my example, I’m using a Goal I set up to track Live Chat sessions on a client’s site.

Example Goal Set up

Step 2

Real Time in GA

Once the goal is saved, go back to the reporting tab and click on “Real-Time” then Conversions.

Now go to the website and go through the steps needed to complete the goal.

(This is where having two screens comes in handy. If you have two screens, keep GA open in one screen and complete the goal steps on the other screen so you can see when your Goal completion pops up.)

 

Step 3

Once you take the steps to complete your goal, then look at GA and see if it showed up under the conversions section. Using my example, you can see that my Chat Goal is working correctly.

real Time Goal completion

If you don’t see your goal completion show up, then you need to go back and make sure you set the goal up correctly. You might have chosen the wrong Match type for URL destinations or wrong category names if you did event type goals. You can even double check the goal is configured properly by clicking “verify this goal” before you click the blue button to “create” the new goal.

That’s it. It’s literally as simple as 1-2-3!

Question for you

How do you currently double check your goals are set up correctly in GA?

 

30 04, 2014

How to Track Offline Activity with Google Analytics

By | 2018-05-01T08:25:12+00:00 April 30th, 2014|Categories: Digital Marketing, Google Analytics|Tags: , , , , |

What’s the biggest challenge you face as a web marketer? I’ll bet dollars to donuts it has something to do with the accurate assessment of ROI.

Customer life-cycles often have multiple components to them – both online and offline. They may start with a phone call and end the buying cycle with a purchase at a bricks and mortar location. Unfortunately, folks don’t have chips embedded in them, scanned automatically upon purchase and referencing them by Google Analytics User ID (Don’t worry. If there is anything we know about Google, this cannot be far behind).

We’d been conditioned to believe that regardless of how great a job we’ve done with organic SEO, email campaigns and print promotions, an answer for how to track offline conversions with Google Analytics would remain allusive. Then along came Universal Analytics, Google’s answer to the deficits inherent in current multi-channel attribution models.

Is Universal Analytics the answer?

dta-ripple-snippetOn the surface, Universal Analytics may appear to address this issue by leveraging an API to record offline transactions and attribute them back to a unique user ID. Problem is, the user has to carry that ID wherever they go. If they use multiple browsers or devices, the entire premise behind this method of accurate visitor tracking becomes compromised. Finding an original touch point may be akin to finding a diamond ring in a box of Cracker Jack. Good luck.

The development of GA Fusion is a true game changer. Through use of a centralized database that connects offline conversions to your online marketing efforts, this “middleware” maps offline transactions back to GA visitor sessions. Using Google Analytics as the reporting platform, GA Fusion provides superior ROI models, attribution models, time to purchase date, etc.

And did I mention that GA Fusion works with the Async code you probably already use? That’s right. If you don’t want to update to Google’s Universal Analytics, you don’t have to. GA Fusion empowers you to make that decision for yourself.

Now you know how to track offline conversions with Google Analytics effectively and accurately. If you’re not ready to upgrade to Universal Analytics or just prefer the asynchronous tracking method, Beacon can add the functionality of GA Fusion to your analytics without any interruption of data flow to your GA account.

Contact Beacon today to step though a demo and find out how a seamless transition to GA Fusion can provide you with the offline conversion information your business needs to flourish.

30 04, 2014

Great Google Analytics Dashboard Shortcuts

By | 2017-08-08T08:18:29+00:00 April 30th, 2014|Categories: Google Analytics|Tags: , , , |

If you are like most people who are new to Google Analytics, you have not yet broken the surface of possibilities that Google’s dashboards can provide. Google Analytics can help shine light on your website’s traffic sources, seasonality, Google AdWords spend and revenue, social media impact and user behavior. The most difficult art about Google Analytics can be sifting through the mountains of information and metrics and gleaning important trends and risk factors that help your business adapt and grow.

What Are Google Analytics Dashboards?

solutions-galleryDashboards help give you a high-level overview of your properties by displaying multiple reports as widgets on a single page. With one dashboard, you can monitor many metrics at once (such as traffic sources), so you can quickly check the health of your site’s traffic, popular referral sources, organic traffic growth and user engagement by traffic medium. With another report, you can view the impact of your paid search campaigns by tracking revenue, eCommerce conversion rate, keyword data and spend analysis…all on one page.

Each profile in your Google Analytics account displays a default dashboard that is pre-populated with a few widgets. You can add new widgets to a dashboard by clicking Add to Dashboard at the top of any report, or by clicking +Add Widget from the dashboard menu. Click the gear icon in the top corner of each widget to see these customization options. To view and manage your dashboards, use the Dashboards menu on the left, found under the Home tab.

You can create up to 20 dashboards for each of your profiles, and each dashboard can contain up to 12 widgets. Dashboards are available only in the view in which you create them.

But What If You Don’t Know Where To Get Started?

Google has made this process easier through its powerful Google Analytics Solutions Gallery. More proficient Google Analytics know how to effectively create their own custom dashboards, with key metrics and comparison data while newcomers to Analytics don”t know where to get started. The new Solutions Gallery takes custom dashboards created by Google Analytics experts and expert marketers and release them (for FREE) to the masses.

Whenever you find a shared dashboard that you think would be helpful, all you have to do is click on the link while logged in to your Google Analytics account, choose the property you want to add the dashboard to, and you now have a pre-built and powerful dashboard!

2014-04-30_13-21-12

2014-04-30_13-42-55There are 16 different filters that you can apply to the Solutions database so you can easily find the dashboard or bundle that is right for your business. This includes acquisition, conversions, display advertising, organic search, engagement and many more. You even have the ability to find pre-made segments, custom reports and goals to make tracking your success and analyzing your data even easier.

2014-04-30_13-44-52Make sure to look at the reviews from each importable dashboard or bundle to see how successful they have been and use customer satisfaction to drive imports. The gallery will keep track of dashboards you have previously used and imported as well which makes it easier to re-use dashboards that work well for your business or clients.

Save Time With Bundles

A couple of great finds in the Google Analytics Solutions Gallery involve bundled sets of dashboards which can be helpful to use right out of the box or customize to your liking. One such great example is the “New Google Analytics Starter Bundle” which incorporates over 20 reports, segments and dashboards that give even new Google Analytics users a leg up on the competition.

2014-04-30_13-47-04

Another great bundle is the “Device Segments” bundle which includes custom advanced segments to see how traffic sources, campaigns and pages perform depending on devices (tablet, mobile, desktop). All of these bundles can be easily by simply searching for “bundle” in the “search for solution” search box.

Customize, Customize, Customize…

The last step to help fully utilize these new dashboards in your account is to customize them so they are right for your business. Some of the dashboard’s widgets may contain dimensions or metrics that don’t apply to your business. If you cannot track revenue in Google Analytics, you can edit the widget or dashboard to focus on tracking conversions such as registrations, signups or contact form submissions.

Customizing each dashboard and segment is super simple.

2014-04-30_14-01-35

From your dashboard, mouse over the “edit” pen in the upper right corner and click to open up the “widget settings” pane where you can customize each widget to only show dimensions and metrics you want to see or care about. The same thing applies for advanced segments.

2014-04-30_14-07-34

Open the Segments drop-down at the top of your analytics window and select one of your imported segments, then click the cog in the upper right, then click edit and voila! You now can customize your custom advanced segments. The same is true for custom reports to help alert you to drops in traffic or revenue or erratic behavior on your site.

In Conclusion

The Google Analytics Solutions Gallery makes diving deeper into Google Analytics easier and more painless. Almost every option of analysis and trending can be found in the gallery and the option to import your own exists if you wish to share your own knowledge and give back. Save time, energy and frustration and make use of this wonderful and free feature today! If you are working on a very complex Google Analytics setup or configuration don’t hesitate to contact Beacon today!

30 04, 2014

Google Analytics for Colleges and Universities

By | 2017-08-07T16:22:23+00:00 April 30th, 2014|Categories: Higher Education|Tags: , , |

How would you like to be able to tell exactly how many prospects you have at your defined admissions cycle steps? How about seeing your abandonment rates between steps in the admissions funnel? How about what sources or efforts are actually driving applications? How about sources that are actually driving actual enrollments? What patterns of activity do people who apply or enroll do? How much does social media actually play a role in the admission process?

Google Analytics College Universities These are all questions that marketing directors and VP of Admissions should be asking themselves and currently it’s very challenging if not impossible to answer these questions. I’ve worked with dozens of schools over the years and have found a consistent theme when it comes to their ability to tie all the data together. Many schools use third-party application software that doesn’t tie into their analytics and essentially houses all their admissions applications data external from their website analytics data. I saw these challenges as an opportunity. The data that could be leveraged if we could connect all the disparate systems would invaluable for marketing decisions.

While GA is an awesome tool for analysis, without having all the data centralized and aligned to match visitor activity into a single user, Google Analytics alone still doesn’t solve this challenge. This is why we built GAFUSION. It is the must have tool for any college or university that wants to view all their marketing data in a centralized location and be able to easily see what activities are driving key conversions and ultimately lead to applications and enrollments.

Colleges and Universities online marketing is a lot different from your typical ecommerce marketing. The application and enrollment process can span years over many devices. And applications can be submitted through many channels such as your website, a third-party website, your admissions office, they can even mail them in. This is why having a centralized conversion database that uses sophisticated matching algorithms to sort through the data and isolate a unique visitor and their activity and push it back into GA with their unique Google Analytics identifier that ties that usage and conversion data to their original sources and mediums is so important.

University Admissions Funnel Tracking

Imagine being able to easily see the type of activities above for any defined period of time. Imagine being able to compare/contrast against the previous year and see where you are making gains or losing prospects. Imagine being able to see the sources and marketing activities that are driving prospects into each step in the funnel. GAFUSION can help you do all of this. When it comes to Google Analytics in the higher education space, Beacon Technologies has the experience and GAFUSION is the “must-have” tool to accomplish this.

22 04, 2014

The reality of Universal Analytics Tracking Offline Conversions:

By | 2017-08-08T08:10:42+00:00 April 22nd, 2014|Categories: Google Analytics|Tags: , , |

By now you’ve heard the hype that Universal Analytics was designed to track users and all their interaction including offline conversions. While Universal Analytics does provide additional measurement capabilities, it is important to understand what those are and what the challenges are with implementing these.

Universal Analytics essentially assigns a visitor with a unique ID that you can use with the API to push additional hits to the GA servers that will be assigned to that user. So if you know John Smith at your retail location bought a pair of shoes, as long as you know John Smith was on the website and his unique visitor ID is 123456779, then you can push a virtual hit that represents that transaction into GA.

So the big question is how do you know John Smith at the store is the same John Smith that was on the website 2 weeks ago and even more curious is how do you know what his unique GA visitor ID is? And once you know that, how do you go about pushing a virtual transaction hit into GA associated with John Smith’s unique identifier. And on top of that, how do you go about creating meaningful reports of the data?

The short answer to making Universal Analytics provide this is a really complex series of matching algorithms that have to be executed outside of Google Analytics, new database creations and systems integration, highly customized tracking scripts, highly customized post transaction jobs that process data autonomously, and a fully customized setup and configuration implementation. So while the idea on the surface sounds very attractive, being able to actually use Universal Analytics in this method can be a very costly and time consuming activity. For a fully custom implantation, back-end system integration, and system automation, you are likely easily looking at a six figure plus project which pushes this functionality out of the price range of the majority of businesses.

Fusion Online offline funnel

This is exactly why we built GAFusion. We’ve built the entire system described above that you can easily plug into. And because we built this as a SAS model, the cost of building, maintaining, updating, and improving the system and functionality is distributed across all of our clients. This means you can have this highly sophisticated system and take full advantage of the new functionality of Universal Analytics for a fraction of the cost. Implementation is super easy because all you have to do is add a single tracking script site wide to your site and provide us a with an XML feed of your offline conversions to track.

The coolest part is that it functions with both async and universal analytics so even if you aren’t ready to upgrade to Universal Analytics, you can still get the full benefit of the hyped functionality. When you are ready to migrate, we can take care of that for you and keep your data flowing. If this sounds too good to be true, give our free trial a test. If you aren’t a believer once you try GAFusion, there’s no commitment. That’s how confident we are in our system that allows you to take full advantage of Universal Analytics tracking offline conversions and transactions.

For more information, read up on how it works here or contact us to step through a demo and get started today.

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