Tip: 4 steps to site optimization

Many people use Google Analytics to improve their online marketing campaigns and keyword buying, but Google Analytics also offers powerful ways to identify visitor navigation trends on your site. Without the right data, optimizing a website is no easy feat. For beginners to the web analytics world, though, all the data provided around content optimization can be a bit daunting -- so here are four steps to help you optimize your site using the data available in Google Analytics:
1. Create a funnel path and goal that mimics the expected navigation
You designed your site, so you know how you expect your users to navigate through it. Create a funnel and goal that mimics the expected path that your site is designed for. Note: if your site is not using the e-commerce tracking code, give your goal a value and take a look at this post about setting goals on a non-e-commerce site.
2. Give it a few days
Give your site a little while to perform, and let Analytics collect at least 3 or 4 weeks of data. Weekends, special events, and holidays may lead to skewed results so giving your site some time to perform enables you to get more reliable, indicative metrics.

3. Pull up a few key reports and re-evaluate your funnels
Open up your Analytics account and visit Content Optimization > Content Performance > Top Content report. Sort the list of pages by the $ Index column. The $ Index value tells you how much each page on your site is worth (as opposed to how much each site visit is worth. The $ Index is based on how often a transaction is completed or goal is reached when a specific page is also accessed during a visit. The $ Index will give a value to that page calculated based on the value of the goal reached.
Use this metric to evaluate the pages in the report. Remember, this column won't be populated with data unless you have a goal, and that goal has a value (see step #1). When you sort by $ Index, ask yourself what are the pages at the top of that column? Are they in your funnel process? If not, why are they worth more than pages in your funnel? Also, review the exit paths in Content Optimization > Goals & Funnel Process > Defined Funnel Navigation. Where are these visitors going? Do these pages have a high $ Index value? If so, you may want to reconsider the navigation path that you've set up, or maybe there are some design flaws that are making the certain pages difficult to navigate through.

4. Optimize that site!
Armed with this information, your next task is to make some changes. Burn the midnight oil and redesign your site. Then continue using Analytics to evaluate your site changes, because keeping visitors and turning them into customers -- or goal converters -- should always drive your site changes.

Posted by Alex Ortiz, Google Analytics Team

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Sending data from Lantronix to Google Analytics

The following is a guest post from Kurt Busch, CEO, and Mariano Goluboff, Principal Field Applications Engineer at Lantronix.

Background

Google Analytics makes it easy to create custom dashboards to present data in the format that most helps to drive business processes. We’ve put together a solution that will make several of our devices (networking and remote access devices) easily configurable to enable delivery of end device data to Google Analytics. We use the Lantronix PremierWave family of devices to connect to an end device via a serial port like RS-232/485, or Ethernet, intelligently extract useful data, and send it to Google Analytics for use in M2M applications. 

What you need

To get started, grab the Pyserial module, and load it on your Lantronix PremierWave XC HSPA+. You’ll also want a device with a serial port that sends data you want to connect to Google Analytics. A digital scale like the 349KLX is a good choice.

Architecture overview

With the Measurement Protocol, part of Universal Analytics, it is now possible to connect data from more than web browsers to Analytics.

Lantronix integrated the Measurement Protocol by using an easy to deploy Python script. By being able to natively execute Python on PremierWave and xSenso devices, Lantronix makes it very easy to deploy intelligent applications leveraging Python’s ease of programming and extensive libraries.

The demonstration consists of a scale with an RS-232 output, connected to a Lantronix PremierWave XC HSPA+. The Python script running on the PremierWave XC HSPA+ parses the data from the scale, and sends the weight received to Google Analytics, where it can then be displayed.

The hardware setup is show in the picture below.

The technical details

The Python program demonstrated by Lantronix uses the Pyserial module to parse this data. The serial port is easily initialized with Pyserial:

class ser349klx:

# setup the serial port. Pass the device as '/dev/ttyS1' or '/dev/ttyS2' for

# serial port 1 and 2 (respectively) in PremierWave EN or XC HSPA+

def __init__(self, device, weight, ga):

while True:

try:

serstat = True

ser = serial.Serial(device,2400, interCharTimeout=0.2, timeout=1)

except Exception:

serstat = False

if serstat:

break

self.ser = ser

self.weight = weight

self.ga = ga

The scale used constantly sends the current weight via the RS-232 port, with each value separated by a carriage return:

def receive_line(self):

buffer = ''

while True:

buffer = buffer + self.ser.read(self.ser.inWaiting())

if '\r' in buffer:

lines = buffer.split('\r')

return lines[-2]

The code that finds a new weight is called from a loop, which then waits for 10 equal non-zero values to wait for the weight to settle before sending it to Google Analytics, as shown below:

# This runs a continuous loop listening for lines coming from the

# serial port and processing them.

def getData(self):

count = 0

prev = 0.0

#print self.ser.interCharTimeout

while True:

time.sleep(0.1)

try:

val = self.receive_line()

weight.value=float(val[-5:])*0.166

if (prev == weight.value):

count += 1

if (count == 10) and (str(prev) != '0.0'):

self.ga.send("{:.2f}".format(prev))

else:

count = 0

prev = weight.value

except Exception:

pass

Since the Google Analytics Measurement Protocol uses standard HTTP requests to send data from devices other than web browsers, the ga.send method is easily implemented using the Python urllib and urllib2 modules, as seen below:

class gaConnect:

def __init__(self, tracking, mac):

self.tracking = tracking

self.mac = mac

def send(self, data):

values = { 'v' : '1',

'tid' : self.tracking,

'cid' : self.mac,

't' : 'event',

'ec' : 'scale',

'ea' : 'weight',

'el' : data }

res = urllib2.urlopen(urllib2.Request("http://www.google-analytics.com/collect", urllib.urlencode(values)))

The last piece is to initialize get a Google Analytics connect object to connect to the user’s Analytics account:

ga = gaConnect("UA-XXXX-Y", dev.mac)

The MAC address of the PremierWave device is used to send unique information from each device.

Results

With these pieces put together, it’s quick and easy to get data from the device to Google Analytics, and then use the extensive custom reporting and modeling that is available to view the data. For example, see the screenshot below of real-time events:

Using Lantronix hardware, you can connect your serial devices or analog sensors to the network via Ethernet, Wi-Fi, or Cellular. Using Python and the Google Analytics Measurement Protocol, the data can be quickly and easily added to your custom Google Analytics reports and dashboards for use in business intelligence and reporting.

Posted by Aditi Rajaram, the Google Analytics team

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Tell a Meaningful Story With Data

This article was originally posted on Google Think Insights.

Most organizations recognize that being a successful, data-driven company requires skilled developers and analysts. Fewer grasp how to use data to tell a meaningful story that resonates both intellectually and emotionally with an audience. Marketers are responsible for this story; as such, they’re often the bridge between the data and those who need to learn something from it, or make decisions based on its analysis. As marketers, we can tailor the story to the audience and effectively use data visualization to complement our narrative. We know that data is powerful. But with a good story, it’s unforgettable.

Rudyard Kipling once wrote, “If history were taught in the form of stories, it would never be forgotten.” The same applies to data. Companies must understand that data will be remembered only if presented in the right way. And often a slide, spreadsheet or graph is not the right way; a story is.

Executives and managers are being bombarded with dashboards brimming with analytics. They struggle with data-driven decision making because they don’t know the story behind the data. In this article, I explain how marketers can make that data more meaningful through the use of storytelling.

The power of a meaningful story

In her “Persuasion and the Power of Story” video, Stanford University Professor of Marketing Jennifer L. Aaker explains that stories are meaningful when they are memorable, impactful and personal. Through the use of interesting visuals and examples, she details the way people respond to messaging when it’s delivered either with statistics or through story. Although she says engagement is quite different from messaging, she does not suggest one over the other. Instead, Aaker surmises that the future of storytelling incorporates both, stating, “When data and stories are used together, they resonate with audiences on both an intellectual and emotional level.”

 In his book Facts Are Sacred, Simon Rogers discusses the foundations of data journalism and how The Guardian is using data to tell stories. He identifies ten lessons he’s learned from building and managing The Guardian’s Datablog, a pioneering website in the field. I found three of the lessons particularly insightful:

1. Data journalism (and analytics in a broader sense) is a form of curation. There is so much data and so many data types that only experienced analysts can separate the wheat from the chaff. Finding the right information and the right way to display it is like curating an art collection. 
2. Analysis doesn’t have to be long and complex. The data collection and analysis process can often be rigorous and time consuming. That said, there are instances when it should be quick, such as when it’s in response to a timely event that requires clarification. 
3. Data analysis isn’t about graphics and visualizations; it’s about telling a story. Look at data the way a detective examines a crime scene. Try to understand what happened and what evidence needs to be collected. The visualization—it can be a chart, map or single number—will come naturally once the mystery is solved. The focus is the story. 

Stories, particularly those that are meaningful, are an effective way to convey data. Now let’s look at how we can customize them for our audiences.

Identify the audience

Most captivating storytellers grasp the importance of understanding the audience. They might tell the same story to a child and adult, but the intonation and delivery will be different. In the same way, a data-based story should be adjusted based on the listener. For example, when speaking to an executive, statistics are likely key to the conversation, but a business intelligence manager would likely find methods and techniques just as important to the story.

In a Harvard Business Review article titled “How to Tell a Story with Data,” Dell Executive Strategist Jim Stikeleather segments listeners into five main audiences: novice, generalist, management, expert and executive. The novice is new to a subject but doesn’t want oversimplification. The generalist is aware of a topic but looks for an overview and the story’s major themes. The management seeks in-depth, actionable understanding of a story’s intricacies and interrelationships with access to detail. The expert wants more exploration and discovery and less storytelling. And the executive needs to know the significance and conclusions of weighted probabilities.

Discerning an audience’s level of understanding and objectives will help the storyteller to create a narrative. But how should we tell the story? The answer to this question is crucial because it will define whether the story will be heard or not.

Using data visualization to complement the narrative

Analytics tools are now ubiquitous, and with them come a laundry list of visualizations—bar and pie charts, tables and line graphs, for example—that can be incorporated into reports and articles. With these tools, however, the focus is on data exploration, not on aiding a narrative. While there are examples of visualizations that do help tell stories, they’re rare and not often used in meetings and conferences. Why? Because finding the story is significantly harder than crunching numbers.

In their “Narrative Visualization: Telling Stories with Data” paper, Stanford researchers discuss author versus reader-driven storytelling. An author-driven narrative doesn’t allow the reader to interact with the charts. The data and visualizations are chosen by the author and presented to the reader as a finished product, similar to a printed magazine article. Conversely, the reader-driven narrative provides ways for the reader to play with data.

With the advent of data journalism, we’re now seeing these two approaches used together. According to the Stanford researchers, “These two visual narrative genres, together with interaction and messaging, must balance a narrative intended by the author with story discovery on the part of the reader.”

A good example of a hybrid author-reader approach is the presentation of The Customer Journey to Online Purchase tool. A few short paragraphs explain why the tool was created and how it works, and an interactive chart allows marketers to break down the information by industry and country. Additional interactive data visualizations provide even more context.

Another extremely efficient and visual way to tell a story is by using maps. In a tutorial on visualization, I show how a large data set can be transformed and incorporated into a story. It’s an example of how to take charts and graphs to the next level in order to add value to the story. In this case, I use Google Fusion Tables and some publicly available data to illustrate analytics data with colorful, interactive maps. The visualization provides more content for those interested in diving deeper into the data.



A good data visualization does a few things. It stands on its own; if taken out of context, the reader should still be able to understand what a chart is saying because the visualization tells the story. It should also be easy to understand. And while too much interaction can distract, the visualization should incorporate some layered data so the curious can explore.

Marketers are responsible for messaging; as such, they’re often the bridge between the data and those who need to learn something from it, or make decisions based on its analysis. By rethinking the way we use data and understanding our audience, we can create meaningful stories that influence and engage the audience on both an emotional and logical level.

Posted by Daniel Waisberg, Analytics Advocate

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Understand the full value of TrueView ads with the new Video Campaigns report

Advertisers know that video ads have the ability to reach and convince customers in ways that other formats can’t, but traditional TV ads are often prohibitively expensive, difficult to target, and hard to measure. That’s why so many advertisers have looked to YouTube TrueView ads for their video needs.  With more than 1 billion unique users each month from across the world and with 40% of that traffic on mobile, YouTube is one of the best places to reach your target audience with high-quality, compelling video.

We’ve heard lots of feedback from loyal Google Analytics users asking for better TrueView reporting, which is why we’re so excited to announce a new Google Analytics Video Campaigns report that focuses on your TrueView ads. With this new report rolling out over the next few days, users can now see the detailed effects of their TrueView campaigns on their website traffic and revenue. You can access the new report under Acquisition > AdWords > Video Campaigns.

Click for full-size image

If you’ve never created a TrueView ad, it’s easy to do with AdWords for Video. Just head into AdWords, and under the +Campaign button, select Online Video.  

Once you’ve created an auto-tagged TrueView ad in AdWords and linked your Google Analytics and AdWords accounts, your TrueView-ad-driven traffic will show up in the Video Campaigns report after about 24 hours. This report has the familiar look and feel of the other AdWords reports but includes TrueView-specific metrics like Paid Views, Cost Per View, and Website Clicks. There are also new metric groups like Engagement, which helps you understand how users engage with your video and your website.  

Using this newly available data, you can fine-tune your TrueView campaign settings to optimize for views, clicks, or goal conversions. You can also segment the reports by Ad Content or Video, helping you analyze the quality of your video creatives in the context of your website goals. 

In addition, since TrueView ads are often more brand-focused, traffic they generate to your site will often be indirect traffic.  In order to analyze this type of traffic, check out the new Google Display Network Impression Reporting pilot, which can help you understand conversions that resulted from unclicked impressions or video views.  With this report, it’s possible to see how your TrueView ads are generating value beyond just direct clicks; you can dive deeper to understand how impressions, views, and clicks all contributed directly or indirectly to conversions on your site.

Click for full-size image

To get started with Video Campaigns reporting, simply link your AdWords and Google Analytics accounts and start an auto-tagged TrueView campaign via AdWords for video. After that, head over to the new report to fine-tune your budgets and targeting.  See you on YouTube!

Posted by Jon Mesh, Google Analytics Product Manager

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New tools to grow your mobile app business

Today at the Game Developers Conference in San Francisco we will be announcing two key launches powered by Google Analytics and Google Tag Manager. You can follow the livestream today at 10:00AM PDT (5:00PM UTC) with the Google Analytics sessions from 2:30PM PDT.

Announcement #1: Bringing the power of Google Analytics to AdMob
We’re happy to announce that Google Analytics is fully available in the AdMob interface on a new Analyze tab. App developers now have a one-stop way to measure success and adjust their earning strategies based on what they learn.

Today’s app developers have to make decisions quickly and implement them seamlessly if they want to stay relevant. It also helps if every business decision is backed up and validated by reliable data. Until now, app developers using AdMob and Google Analytics had to use two separate tools to monetize and measure. Starting today, they’re now in one place.

More than just Google Analytics inside AdMob
The new tab is simpler, yes. But app businesses can also now make decisions faster without losing data accuracy. They’ll also benefit from a new set of features that make measurement the foundation of all monetization programs:

• drop down menu to switch between individual apps reports
• new home page with combined Google Analytics and AdMob reporting
• new Analyze tab with all Google Analytics reports

To see the new feature in action, sign in to your AdMob account and look for the Analyze tab at the top of the page. 

click to enlarge

Your new home tab in AdMob will now incorporate data on how your app is monetizing as well as how it is performing overall with insights on in app purchase, traffic and ads metrics in your app: all in one tab - a unique feature just in Admob.

click to enlarge

Get started in one click with Google Analytics and AdMob 

1. Login or open a new account on AdMob and sign up for Google Analytics (GA) in the new Analyze tab. 

2. If you are already using Google Analytics for your apps, you can link your existing account with AdMob in the Analyze tab. 

3. If you are not using Google Analytics, you can sign up via AdMob and complete the process without leaving the interface.

Announcement #2: New Content Experiments with Google Tag Manager

People have a lot of choice when it comes to apps and keeping them engaged is a challenge. Businesses who experiment with different app layouts have a higher chance to find the best performing solution and keep users engaged. A few months ago we announced Google Tag Manager for apps, today we are enabling content experiments: an easy way to set up and run experiments to change anything from in-app promotions to menu layout. With Google Tag Manager you can modify app configuration for existing users without having to ship a new version.

But how can we always be sure that we are changing it for the best? Wouldn’t it better if you could validate business decisions with data? Now you can run content experiments on a subset of your users to choose the best option - where to show promotions? How often? Data in Google Analytics will answer your questions and you can now be sure your decisions will be backed by data.

Google Tag Manager has been built to be very intuitive, even for people not familiar with coding. Businesses can now let their marketers or business analysts run experiments without requiring a developer to be involved. App experiments are now accessible to everyone.

click to enlarge

Getting started with Google Tag Manager

1. Sign up for an account at www.google.com/tagmanager and create a mobile container
2. Download the SDK for either Android or iOS. 
3. Start programming! Use the SDK to instrument configuration and events you care about in your app.
4. When you’re ready to dynamically change your app, use the Google Tag Manager interface to start configuring. Remember to press the “Publish” button to push your rules and configurations to your users.

Posted by Russell Ketchum, Lead Product Manager, Google Analytics for Mobile Apps and Google Tag Manager

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Tailored ads, better results: Dynamic Remarketing powered by Google Analytics

Back in August, 2012, we launched Remarketing with Google Analytics, which enabled advertisers to create sophisticated remarketing lists using Google Analytics’ 250+ dimensions and metrics. 

Today, we’re excited to announce a deeper remarketing integration between AdWords and Google Analytics. 

A single set of tags can now power both Google Analytics and Dynamic Remarketing on the Google Display Network using the Google Merchant Center. Retailers (with other verticals in beta) will gain power and precision for their remarketing along with access to detailed product level reporting through this integration.

What is Dynamic Remarketing?

[original article here]

Every customer is unique. Dynamic remarketing takes this into account, letting you create and deliver beautiful customized ads that connect visitors with their past shopping experiences on your site. If you’re a retailer with a Google Merchant Center account, you can use dynamic remarketing to construct remarketing ads on the fly with the products and messages that are predicted to perform best based on visitors’ past actions on your site.

For example: Customers who browsed the winter tires category on an advertiser’s website might see an ad that includes the exact products they’ve already viewed, in addition to related products from the company’s catalog. In the Tirendo example above, the ad also shows details of recently viewed tires, including the prices.

Early users are seeing great results

"We've been thrilled with the performance of Dynamic Remarketing with Google Analytics and Conversion Optimizer, which has so far driven a 203% increase in conversions and 100% increase in conversion rates vs. our display average. Combined with Google Analytics' powerful reporting on these same metrics, we've been able to derive actionable insights which we've put to good use throughout our other campaigns."

- Janina Rix, SEA Manager, tirendo.de

To begin using Dynamic Remarketing

1. Create one or more remarketing lists using Google Analytics
2. Update your tags to track Product ID, Cart Value, and Page Type as custom variables (or dimensions)
3. Enable the Dynamic Link in Admin > Property > Dynamic Attributes. This will let Google Analytics send attributes to your AdWords account. [more below]
4. Create a Dynamic Remarketing Display campaign in AdWords

Here’s a quick visual guide to the new interface.

Step 1: Configure account details

Step 2: Make sure the attribute names match your custom variables

Step 3: Click ‘Save’ and finish by creating your first Dynamic Remarketing campaign in AdWords

Want more help? Download a remarketing starter pack from the solutions gallery. 

Please stay tuned for more remarketing-related updates in the near future!

Happy Analyzing, Dan Stone and Lan Huang on behalf of the Google Analytics Team

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Storytelling with data using Measureful and Google Analytics

The following is a guest post from John Koenig, CEO at Measureful.

The democratization of data within organizations over the last few years has put data even more under the purview of marketers. This shift has created a necessary discipline in digital intelligence: data storytelling. Data storytelling strives to create a clear, more meaningful picture of complex metrics through effective storytelling techniques. 

Combining Measurable and Google Analytics brings together a powerful measurement and presentation tool to help quantify efforts and present a compelling case. Google Analytics is the vehicle for discovering stories, while Measureful brings these stories to life.

A Beginning, Middle and End

A top down, linear approach following these 3 steps helps keep your marketing reports focused and your audience tuned in.

1. What happened? 

If you’ve built even a basic Google Analytics strategy, you’ll have already identified your objectives or KPIs (key performance indicators). Start each report by covering these first. Be short and concise with KPIs and focus on basic performance to set the tone for the rest of the report.

These are most often a conversion event such as revenue or a user-defined goal such as a new lead. This is one portion of your report that should be fairly static. Objectives generally don’t change frequently and thus other portions of your report should roll up to these. The narrative of your report will largely be focused around explaining changes to this key group of metrics.

2. Why and what caused it?

This is where most reports fall into trouble. Even if you have access to large amounts of data and reports, it doesn’t mean you need to use all of it. The reality is you only have the attention of your audience for a small amount of time so be selective, focus on bringing together cohesive points, and leave everything else out.

This means your reports should be dynamic and change each month. That’s right, your reports should change. If they aren’t changing you’re not telling a story, you’re regurgitating data.

Focus on identify 2 to 3 subtle narratives to focus on but do not bypass exploratory and quantitative analysis. You still need to begin each period analyzing changes and interpreting data to determine the most effective points. This is analysis work, but if you’ve set up a strategy, this doesn’t have to be time-consuming or overly complex. 

I suggest looking at 3 areas to help build your storylines -

1. Attribution

2. Campaigns

3. Outliers

If Revenue (your KPI) increased last period, drill into theAll Traffic reporint in Google Analytics and begin to attribute why this change occurred. It is not importatnt to  report on every segment and dimension but instead focus on why this change occurred.

This is also the portion where you can outline any specific campaigns that were run during the period and include metrics specific to these and their performance.

Lastly, look for outliers. While these may not be immediately apparent, both Measureful and Google Analytics provide tools for helping with these. In Google Analytics, set up rules in Intelligence Events. With Measureful, use the Smart Reporting feature. This works similar to Intelligence Events, but runs automatically and covers trends for many different segments and time-periods. Turn it on and let it help you identify unique stories in your Google Analytics data.

3. What’s next?

Give your story an ending by reiterating your points, making recommendations and covering next steps. This is where you can push your agenda, ask for more budget or suggest some new strategy or tactics.

Storytelling in Practice

Gerber relies on a sophisticated measurement strategy using advanced Google Analytics features to quantify marketing efforts and drive campaign decisions. John Robbins is the Digital Marketing Manager at GerberGear.com and is responsible for a myriad of digital channels and campaigns and is expected to report on performance.

John leverages both Google Analytics and Measureful to help keep the whole team easily informed and knowledgeable of key findings and changes.

Tying it all together with Measureful

With analytics data in place, the linear approach is easily applied and the Gerber Monthly Marketing Report built using Measureful’s WYSIWYG editor.

For example, Gerber’s top-line of metrics were setup to provide a quick view of performance for the month while two over-time visualizations were add for context. Measureful’s reporting platform includes automated narratives with analysis on performance versus the previous month, year and compared to the 12-month average. 

After a bit of analysis, it’s clear that a few channels performed very well and thus the focus of the reports begin to take shape around these narratives. While Gerber’s digital strategy goes well beyond the contents of this particular report, it's most effective to report on the metrics that are important to business objectives. Measureful helps Gerber focus a report on the key take-aways and points and thus steer an audience’s attention to what’s most critical.

And finally, it’s helpful to end a report with clear points and next steps.

Gerber went from long and time-consuming marketing reports that were often overlooked to a 4-page, focused report that drives home the main points in their marketing and analytics strategies.

Data storytelling is an essential skill to effectively cross the chasm of understanding and ultimately action. Charts and tables do not necessarily mean you’ve done a good job of communicating important findings. Meausureful can help weave Google Analytics data into a coherent narrative, and turn your data into a powerful communication tool.

Posted by Aditi Rajaram, The Google Analytics team

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On your phone, tablet or laptop: Your results front and center with AdWords Express

The following was originally posted on the Inside AdWords blog.

When you log in to AdWords Express today, you’ll notice that it’s now easier to find the information that’s important to you, whether you’re on your phone, tablet or laptop. After gathering feedback from AdWords Express users, we’ve redesigned the dashboard with ad performance stats front and center.

See how many views, clicks and calls your ad has received from customers on different devices 

Check your ad’s performance on the go

It’s easy to manage your advertising, even when you’re away from the office. For example, to check how many customers have seen your ad from their tablet (while using your own phone) just look under the “Views” graph.

Check your ad’s performance on the go

Go beyond the click with Google Analytics

Now you can see more details about how users interact with your website after clicking your ad by linking your Google Analytics and AdWords Express accounts. Once you connect your accounts, you’ll see a new card on the AdWords Express dashboard (as well as in your Analytics account). 

Google Analytics information in AdWords Express

To learn how to link Analytics and AdWords Express, visit the help center.

If you have additional feedback on this new design, please let us know. And if you haven’t yet started using AdWords Express, you can sign up today. 

Posted by Francisco Uribe, Product Manager

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Invest In Yourself: Learning Digital Analytics In 2014

We’re excited to help digital marketers become more data savvy through the Analytics Academy. Initially launched in October of last year, our first course attracted more than 145,000 students - and more than 30,000 finished the course and earned a certificate of completion.

That’s why today we’re excited to announce the launch of our next course in the Analytics Academy titled “Google Analytics Platform Principles.”

In this course we’ll dive deeper into the details of how the platform collects, transforms and organizes the data you see in Analytics. Understanding how these processes work is the first step to refining your implementation and uncovering more valuable insights about your business.

In this self-paced online course, you’ll learn about:

• the four components of the Analytics platform: collection, processing, configuration and reporting 
• how Analytics collects the data you need across different devices
• how your data is transformed before you see it in your reports
• key concepts for customizing your Analytics data in useful ways

Registration is now open and the course begins March 11, 2014. You can sign up here.

The importance of education

It’s never been a more exciting time for businesses as technology is driving innovation at an astounding rate. With the introduction of mobile devices (and tablets) and the ability to understand user behavior - the fundamental way that we do business is changing. And the key driver is data.

All of these new technologies create information - data that we can use to better understand the needs of customers. If we understand the customer better, we can help them achieve their goals, while we achieve ours.

Nowhere is this more evident than in digital marketing and digital advertising. 78% of marketers feel the need to become more data driven and almost 40% of major brands see a talent gap in analytics. Marketers need to know how their campaigns drive direct conversions, and more importantly, how they improve the overall performance of other campaigns. This can be an imposing task for someone that doesn’t know the difference between a conversion and bounce rate. 

No matter what your role in business, from marketing to product to PR, you will need to work with data. Luckily there many opportunities for all of us to learn. Make 2014 the year that you invest in yourself and develop your analytical skills.

To paint the picture of the opportunity, we also created an infographic to get you excited about embarking on your own personal analytics education (see a preview below, but view the whole graphic here). We hope to see you at our MOOC in class!

Posted by Justin Cutroni, Analytics Evangelist, Google

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