Showing posts with label Developer. Show all posts

Wordsmith for Marketing: Using the Reporting API to automate agency client reports

Wednesday, November 04, 2015 | 7:31 AM

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This is a guest post by Cole Faloon, a developer for Wordsmith for Marketing at Automated Insights.

Digital marketing professionals live and breathe Google Analytics, AdWords and social media, constantly measuring just how well their strategies are performing. But communicating successes in client reports takes an inordinate amount of time. Enter Wordsmith for Marketing, the client reporting solution from Automated Insights that automatically transforms Google Analytics, AdWords and social data into plain-English reports.

The vastness of data in Google Analytics made it an obvious foundation for Wordsmith for Marketing. Our app is built around the Google Analytics Core Reporting API. The app pulls down metrics like visits, page views, and conversions for different periods, comparing the data across spans of time.

The API is flexible enough for us to receive dates at the ranges we need. We can slice up the data by pre-defined dimensions by week, month, and quarter.

Another feature we love? Google's implementation of the OAuth 2.0 Authorization Framework. It allows users of our solution to sign in with their Google account, getting us access to their Analytics data right away and creating a fluid user experience. They just log in and they’re ready to go.



Empowered by Google Analytics, we give marketers a clear explanation of how their clients’ digital marketing efforts are performing and advice on how to improve; they have the option of editing the reports to add finishing touches or comments before sending them on to their clients. Wordsmith for Marketing automatically produces insightful client-ready analysis, saving marketing agencies hundreds of hours and thousands of dollars while allowing them to better serve their clients. 


- The Google Analytics Developer Relations team, on behalf of Wordsmith for Marketing

Using Google Analytics to understand real-time messaging behavior

Tuesday, September 08, 2015 | 12:01 PM

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This is a guest post by Nico Miceli, a Google Developer Expert for Google Analytics, Technical Analytics Consultant on Team Demystified, quantified selfer, and all around curious guy. He blogs at nicomiceli.com and tweets from @nicomiceli.

Hello, my name is Nico, and I love data. I quantify everything, and the Google Analytics Measurement Protocol is my favorite way to do it.

With the Measurement Protocol, I can send, store, and visualize any data I want without having to build a backend collection system. I’ve even used it in my personal life to track my sleep patterns, the temperature in my house, and the number of times my brother’s cat actually uses his scratching post.

So when my team started using Slack, a real-time messaging app for teams, I wanted to get the stats. Which clients are contacting us most frequently? When are the contacting us? More importantly, who on our team is the wordiest and uses the most emojis? Out of the box, the app offered some data, but it wasn’t enough for me to answer all the questions I had.

After taking a look at the technical documentation for the messaging app, I realized that Google Analytics is the answer! With the Measurement Protocol and the Slack Real Time API, I could get SO MUCH DATA!! With help from fellow developer Joe Zeoli, Slackalytics was born.

Slackalytics (in beta) is a simple, open source bot for analyzing Slack messages. Built in node.js, it grabs messages from Slack (using the Slack Real Time Messaging API), does some textual analysis, and counts the occurrences of specific instances of words and symbols. Then, using the Measurement Protocol, it sends the data to your Google Analytics account. 



Screenshot of the report showing the custom metrics (emoji, exclamation, word, and ellipse counts) for different Slack channels.

Because the data gets stored in Google Analytics, you can visualized and analyze within the UI or use the Google Analytics Core Reporting API. I like to combine this data with other information so I have export it all into a Google sheet using the Google Analytics Spreadsheets Add-on.

In this beta version of Slackalytics, I’m using two Custom Dimensions: User ID, Channel Name... and six Custom Metrics: Word Count, Letter Count, Emoji Count :), Exclamation Count !!!, Question Count ???, Ellipse Count...

But this is just a fraction of what’s possible. Slackalytics is open source, so you can build your own version. If you’re a developer: Fork my project on GitHub.

If you’re not a developer: Fear not. You can still create your own messaging analysis bot by following my detailed walkthrough on setting this up.

Developer or not, you can build and test your own bot by using Google Analytics and any communication app that has a realtime API. Find out when your clients ask the most questions, monitor other integrations and bots, find out who talks in ☺     or build your own new Custom Dimension & Metrics combos.

- The Google Analytics Developer Relations team, on behalf of Nico Miceli

Supermetrics: Bringing more of your cost data into Google Analytics

Tuesday, May 12, 2015 | 11:52 AM

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The following is a guest post from Supermetrics, a Google Analytics Technology Partner.

Google Analytics has some great tools to help you keep track of how well your ad campaigns bring new users to your website, including Goals, Multi-Channel Funnels, and Enhanced Ecommerce. But acquisition or conversion data alone don’t give you the full picture of ad performance. To understand how well your campaigns are doing, you need to contextualize conversion rates with cost data. 

Set up automatic cost data uploads 
AdWords linking lets you see your AdWords data imported to your Google Analytics account, though getting data from other sources can take longer and be a more manual process. You can make the process easier and go faster with a tool like Supermetrics Uploader add-on

Built using the Google Analytics Data Import feature, Supermetrics Uploader lets you set up automatic daily uploads from your Facebook Ads and Bing Ads with just a few clicks. You can also use Supermetrics Uploader to to import historical advertising data going back several years, and use it to manually upload CSV formatted data from any source. If your ad destination URLs are tagged with utm parameters, the imported cost data will be mapped to Google Analytics session data, and you’ll immediately see your return on ad spend (ROAS) and revenue per click (RPC) metrics for each campaign.

Watch this one-minute video to get an overview of Supermetrics Uploader.


See all of your cost data in your reports
Supermetrics Uploader can help get you a clear picture of how all your campaign spend compares with the results without having to switch between different reporting systems.

Within twenty-four hours after scheduling your first upload with Supermetrics Uploader, your data will start appearing in your Google Analytics Cost Analysis report, and in any of your Custom Reports that include ad cost, impressions, or clicks. All of your imported data will also be available in any 3rd party tools that connect to the to Google Analytics Reporting API.


- The Google Analytics Developer Relations team

Supercharge your Google Analytics with SkyGlue

Tuesday, April 28, 2015 | 10:28 AM

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The following is a guest post from SkyGlue, a Google Analytics Technology Partner

SkyGlue is a powerful add-on tool for Google Analytics that helps web analysts to get more out of Google Analytics. With SkyGlue, you can automate Event Tracking for your website, zoom in on visitor analytics, and export and integrate your Google Analytics data with your own database or CRM. 
Automatic Event Tracking: Custom data collection without IT help
Your website probably offers many ways for visitors to interact with your content, so you need to know what your visitors do on your site, and not just which pages they visit. Although you collect important data about interactions like clicks, downloads, and modal popups using Google Analytics Event Tracking, it requires a fair amount of additional setup. And if you don’t have the IT resources to set up Event Tracking, it means that you’re missing out on collecting this important data. 
SkyGlue helps you gain independence from IT resources by automating Event Tracking with on-the-fly customization using SkyGlue web portal. By adding one line of JavaScript to your website, the SkyGlue app can track interactions with any HTML element on your website and then send this data to your Google Analytics account.  
SkyGlue Event Tracking visual overlay
Visitor analytics + Data export
SkyGlue supports multiple approaches to visitor tracking and offers special reports that let you see the entire sequence of visits and interactions. Integrated fully with Google Analytics advanced segments, these reports let you zoom-in on selected groups of visitors, helping you understand your customers’ behavior, discover patterns, identify technical glitches, improve customer service, and find ways to increase conversion and retention rates. You can also use SkyGlue to export your Google Analytics data on a daily basis, and integrate it with your own CRM and other data sources.
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SkyGlue Individual Visitor Report (not based on real data)
SkyGlue puts some of Google Analytics most powerful features in the hands of every analyst. Use it to automate Event Tracking, get access to visitor analytics reports, and export and integrate Google Analytics data with other data sources. 
SkyGlue is free to try and takes only a few minutes to set up - check it out and see customer reviews in the Google Analytics Partner Gallery
For more information, visit the SkyGlue website and read real-world examples of how SkyGlue has already helped many business and organizations get more out of Google Analytics.  
- The Google Analytics Developer Relations team

Tackling Quantitative PR Measurement with AirPR & Google Analytics

Wednesday, April 08, 2015 | 9:30 AM

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The following is a guest post by Leta Soza. Leta is the PR Engineer at AirPR where she lives and breathes PR strategy, content marketing, community cultivation, and analytics. Her analytics adoration stems from the firmly rooted belief that you can’t manage what you can’t measure, so bring on the data. She works with everyone from Fortune 500 companies to innovative startups in order to assist them in proving the ROI of their PR efforts while optimizing their strategies. 

It’s no secret that PR has historically been difficult to measure… quantitatively that is.

PR pros have always had to rely on less than stellar metrics (AVEs, impressions calculations, etc.) to show ROI, and with seemingly no viable reporting alternatives, PR has basically been relegated to the budgetary back seat.

For years, the industry has struggled to prove its value, lagging behind in technological innovation. But as every aspect of business becomes driven by data, vanity metrics are becoming unacceptable and PR is being held accountable for demonstrating its impact on the bottom line.

At AirPR, we’ve made it our mission to provide analytics, insights, and measurement solutions for the rapidly evolving PR industry. Our Analyst product focuses on increasing overall PR performance while seeking to solve systemic industry challenges through the application of big data.

Analyst, our measurement and insights solution, was created to assist PR and communication professionals in understanding what’s moving the needle in terms of their business objectives. 

Interested in how many potential customers came to your website from that press hit? Curious which authors drove the most social amplification during a specific quarter? Want to more deeply understand message pull-through or even attribute revenue? Analyst simplifies getting these answers.

One of the key features of Analyst is our unique integration with Google Analytics. Our integration arms Analyst users with a comprehensive snapshot of the PR activities driving business objectives, as well as the insights to understand the media placements (earned or owned) that are achieving specific company aims, giving PR professionals a single dashboard dedicated to displaying the performance of their efforts. Completing the GA integration creates a comprehensive view of the most meaningful and actionable PR data in aggregate which then allows users to click into any piece of data for more context. 
AirPR Analyst Dashboard (click for full-sized image)

In PR attribution is key, so we leverage Google Analytics data in order to display PR-specific performance and demonstrate ROI. Our aim: To change the way the industry thinks about PR analytics, insights, and measurement and to provide the solutions that support this shift. 

To quote legendary management consultant Peter Drucker, “In this new era of ‘big data’ it is even more important to convert raw data to true information.” Our goal is to deliver actionable and meaningful information. When decision makers understand what’s working, they can increase effort on certain aspects, eliminate others, and make impactful budget allocation decisions for future PR campaigns, much like they do for advertising.

To learn more about AirPR Analyst, check us out in the Google Analytics app gallery.

Posted by Leta Soza, PR Engineer at AirPR 

Google Analytics Demos & Tools

Thursday, November 20, 2014 | 9:00 AM

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As a member of the Google Analytics Developer Relations team, I often hear from our community that they want to do more with GA but don't always know how. They know the basics but want to see full examples and demos that show how things should be built.

Well, we've been listening, and today I'm proud to announce the launch Google Analytics Demos & Tools, a new website geared toward helping Google Analytics developers tackle the challenges they face most often.


The site aims to make experienced developers more productive (we use it internally all the time) and to show new users what's possible and inspire them to leverage the platform to improve their business through advanced measurement and analysis.

Some highlights of the site include a full-featured Enhanced Ecommerce demo with code samples for both Google Analytics and Google Tag Manager, a new Account Explorer tool to help you quickly find the IDs you need for various Google Analytics services and 3rd party integrations, several examples of easy-to-build custom dashboards, and some old favorites like the Query Explorer.

Google Analytics Demos & Tools not only shows off Google Analytics technologies, it also uses them under the hood. All pages that require authorization use the Embed API to log users in, and usage statistics, including outbound link clicks, authorization status, client-side exceptions, and numerous other user interaction events are measured using analytics.js.

Every page that makes use of a Google Analytics technology lists that information in the footer, making it easy for developers to see how all the pieces fit together. In addition, the entire site is open sourced and available on Github, so you can dive in and see exactly how everything works.

Feedback is welcome and appreciated!

By: Philip Walton, Developer Programs Engineer

Introducing the new Google Analytics Partner Gallery

Tuesday, June 24, 2014 | 6:58 AM

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Google Analytics has a vibrant ecosystem of analytics practitioners, advocates, and developers that drive great conversations, learnings, and sharing among passionate users. A central part of this ecosystem is partners, which can help users quickly increase the business value of Google Analytics through implementation expertise, analysis, and integrations.

To make it easier to find services and apps that are important to your business, we’ve re-launched the App Gallery as the Partner Gallery, the new destination to find partners and review their offerings. It includes:

Certified Partners are vetted by Google and meet rigorous qualification standards. This includes agencies and consultancies who offer web analytics implementations, analysis services and website testing and optimization services.

Ready-to-use applications that extend Google Analytics in new and exciting ways. This includes solutions that help analysts, marketers, IT teams, and executives get the most out of Google Analytics and complement functionality.



The Partner Gallery includes new features and improvements:
  • A brand new look and layout.
  • A combined view of both services and apps so you don’t need to visit multiple sites to find a solution.
  • New search capabilities and category selection making it easier to filter and find what you’re looking for.
  • Google Analytics Certified Partners are sorted based on your location to find partners that have an office near you.
  • Media assets like screenshots / videos / case studies that highlight customer success stories and illustrate app features.
  • Comments and ratings to review user experiences and provide feedback.
Visit the Partner Gallery to browse partner services and apps. If you’re interested in the Google Analytics Certified Partner or Technology Partner programs, learn how to become a partner.

Pete Frisella, Developer Advocate, Google Analytics Developer Relations team

New user and sequence based segments in the Core Reporting API

Friday, April 11, 2014 | 10:30 AM

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Segmentation is one of the most powerful analysis techniques in Google Analytics. It’s core to understanding your users, and allows you to make better marketing decisions. Using segmentation, you can uncover new insights such as:
  • How loyalty impacts content consumption
  • How search terms vary by region
  • How conversion rates differ across demographics
Last year, we announced a new version of segments that included a number of new features.

Today, we’ve added this powerful functionality to the Google Analytics Core Reporting API. Here's an overview of the new capabilities we added:

User Segmentation
Previously, advanced segments were solely based on sessions. With the new functionality in the API, you can now define user-based segments to answer questions like “How many users had more than $1,000 in revenue across all transactions in the date range?”

Example: &segment=users::condition::ga:transactionRevenue>1000

Try it in the Query Explorer.

Sequence-based Segments
Sequence-based segments provide an easy way to segment users based on a series of interactions. With the API, you can now define segments to answer questions like “How many users started at page 1, then later, in a different session, made a transaction?”

Example: segment=users::sequence::ga:pagePath==/shop/search;->>perHit::ga:transactionRevenue>10

Try it in the Query Explorer.

New Operators
To simplify building segments, we added a bunch of new operators to simplify filtering on dimensions whose values are numbers, and limiting metric values within ranges. Additionally, we updated segment definitions in the Management API segments collection.

Partner Solutions
Padicode, one of our Google Analytics Technology Partners, used the new sequence-based segments API feature in their funnel analysis product they call PadiTrack.

PadiTrack allows Google Analytics customers to create ad-hoc funnels to identify user flow bottlenecks. By fixing these bottlenecks, customers can improve performance, and increase overall conversion rate.

The tool is easy to use and allows customers to define an ad-hoc sequence of steps. The tool uses the Google Analytics API to report how many users completed, or abandoned, each step.


According to Claudiu Murariu, founder of Padicode, “For us, the new API has opened the gates for advanced reporting outside the Google Analytics interface. The ability to be able to do a quick query and find out how many people added a product to the shopping cart and at a later time purchased the products, allows managers, analysts and marketers to easily understand completion and abandonment rates. Now, analysis is about people and not abstract terms such as visits.”

The PadiTrack conversion funnel analysis tool is free to use. Learn more about PadiTrack on their website.

Resources

We’re looking forward to seeing what people build using this powerful new functionality.

Posted by Nick Mihailovski, Product Manager, Google Analytics team

Sending data from Lantronix to Google Analytics

Friday, March 28, 2014 | 9:33 AM

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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


New tools to grow your mobile app business

Tuesday, March 18, 2014 | 6:30 AM

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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

Storytelling with data using Measureful and Google Analytics

Friday, March 07, 2014 | 10:08 AM

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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