Google mentions a number of scenarios that become possible with this upcoming integration in the announcement post.

While all of these are exciting, one touches on an area where I see this new capability opening the flood gates- integrating with Data warehouses.

While of course it is possible to integrate huge amounts of Google Analytics data with data warehouses thanks to the existing API, and many of our customers are doing this already with sophisticated, automated integration into their enterprise systems using Analytics Canvas, the direct access to the most granular data in a platform like Google BigQuery is a game changer in terms of scale.

A new level of clarity through integration of data at the most granular level

What this integration between Google Analytics and BigQuery means is that now Google Analytics data can be tied to other enterprise data at a more granular level- and over a scope and scale that is necessary for the largest Google Analytics Premium customers.

This integration also makes Universal Analytics even more powerful and useful- tracking everything at a very granular level everywhere, with the customer at the center of it all will allow businesses to have a new clarity across their entire operation. The multiple digital and real world touch points they have with their customers and prospects will be visible and data scientists will have a field day.

Google has announced that this will be available “later this year” and will be available to Google Premium customers.

Stay tuned for more news- and to hear how Analytics Canvas will be taking advantage of the new capability.

The post Google Analytics and Google BigQuery- Oh My! appeared first on Analytics Canvas.

This is the kind of analytics that old-school marketers dreamed of and new-school marketers expect.

The biggest change is the ability to track more than just website traffic by integrating your own datasets with Google Analytics. This opens up a whole new range of possibilities as you can now capture data from more devices, including those anchored in physical locations, and easily connect that data in Google Analytics to analyze and report on it.

What’s The Catch?

All those millions of websites that have installed Google Analytics, based on the ga.js library, will have to migrate to the new Universal Analytics which uses a new library called analytics.js, offered via the new Measurement Protocol. Replacing the old tracker and upgrading to UA is not trivial – it will involve a lot of code, and until Google releases a migration guide, your data will be in two different profiles.

Trying to marry that data together into a single report is keeping many marketers and developers on the sidelines.

But not Analytics Canvas users.

If you want to integrate the two datasets, Analytics Canvas can be used to extract data from both GA and UA, combine them, and prepare integrated reports. I won’t go into the details about setting up the new Universal Analytics. KISSmetrics has already written an in-depth post and if you’re looking for some very clear instructions I recommend you check it out.

Once you’re setup, simply use Analytics Canvas to extract data from both profiles, choose a logical cut-off point for each and combine them into a database table. From there simply build your reports off of this new table to maintain your time horizon.

Integrating Your Own Data

What’s so exciting about UA is that this simple idea of connecting data from any source allows you to use Google’s free service to capture data, analyze results and make decisions on a whole array of topics that have nothing to do with sales and marketing.

As an example, Loves Data created a video discussing how you can use UA to tie caffeine to productivity which inspired us to create an experiment that analyzes the location of the fans in our office to the temperature in each room. We’re working on it now and will write a series of posts once it’s under way.

Ready to start your own experiments and take advantage of UA? It’s now in public beta so simply log-in to Google Analytics and create a new account or property and you’ll be on your way.

Google

The post Can’t Wait for the Migration Guide? Combine GA and UA with Analytics Canvas. appeared first on Analytics Canvas.

Google’s front-end solution provides a summary of all your properties and allows you to access and export the data so that you can compare sites and segments. They also provide back-end access via the Analytics API to help automate extraction and generate reports summarizing your traffic.

When you have multiple properties to analyze it’s easy to get excited about the insights that can be uncovered when analyzing them together, like spotting search traffic anomalies, determining the impact social media by region, or even comparing funnel performance between sites.

But that excitement can quickly get washed away with the anxiety of spending all your time exporting and combining data or bogging down Excel with too many rows and worksheets.

In this post we’ll look at how to use the front end method in Google Analytics and how to access the Analytics API using Analytics Canvas without writing code or SQL queries.

Front End Solution For Accessing Multiple Google Analytics Accounts

The Google Analytics web front-end allows you to see high level data for all your assets. Simply choose All Accounts then click Accounts List and Show Metrics. You’ll see visits, average session time, bounce rate and goal conversion rate for all of the assets under your account.

If you wanted to customize a dashboard and apply it to each profile, build it once then share it with yourself and add the custom report to each one of your profiles. It would be a little time consuming but if you rarely change your reports it certainly would work.

But what if you routinely perform new analysis and don’t know how to access the API or write SQL queries?

Use the APIs Without Writing Code

The Google Analytics Application Gallery has a number of desktop and web-based solutions to help you get at your data, automate reports, create dashboards and perform serious analysis.

For in-depth analysis, Analytics Canvas can be used to:

• connect multiple Google Analytics accounts to one dashboard
• run a monthly report for all properties with aggregate and individual Excel dashboards
• apply changes to some or all properties at once
• compare segments across sites
• automate reports and refresh them with the click of a button

For example, if we wanted to determine the impact of social media on traffic to our sites, we can use a visual interface with blocks and connectors to setup a canvas for our analysis.

First we’ll need to select the profiles to include. If you have many sites, use the filter to quickly find the sites you’re looking for. You can choose to create one block for all selected profiles or one block for each. In this case we’ll choose one each.

Then we’ll need to define the query. In this case we’re going to analyze the source, visits and avg time on site.

And finally setup our canvas. In this case we’re pulling all of the profiles into a combine block, performing a calculation, segmenting the data, summarizing it, pivoting our results, then exporting from the pivot block to 3 Excel data blocks.

The first export is our aggregate data block which summarizes all the accounts and the second two are sub-sets of the data that we want to report on.

During the course of our analysis we may find that we’re not looking at all the right metrics and in addition to tracking the average time a visitor spends on our site when referred from social vs other channels, we also want to see if they view more pages.

If you were pulling data manually into Excel you’d have to repeat a significant number of steps. With Analytics Canvas you simply revisit your query, choose the metric, update your blocks, and in no time your new data set is available.

Press Play

The best thing about your new canvas? To refresh your report and publish it to a database or Excel template simply open the canvas and press “play”. You will be amazed at how quickly your reports are updated.

Whether you want to conduct a comparative analysis across profiles on keywords, referral sources, and location, or simply want an easy way to automate and update reports, Analytics Canvas has you covered.

Ready to get at all that data and create the reports you really want? Sign-up for a free trial of Analytics Canvas and see how easy it can be.

The post Access Multiple Google Analytics Accounts, Properties, and Profiles to Create Summary Reports appeared first on Analytics Canvas.

Google Analytics is clearly an enterprise capable analytics platform. As higher and higher traffic websites take advantage of its features, Google has put in place some limits on how much data can be included in a query- if a query requires more than this, it implements sampling (called fast access mode in the Google Analytics user interface) this ensures that the user interface and API respond quickly.

Sampling provides an estimate based on a sample of visits in cases where Google has not pre-aggregated datasets. The most common cause of sampling is the use of advanced segments in a query.

In many cases, sampling only slightly affects the accuracy of the result- but in many others, it makes it impossible to get valid data.

The good news is, that Google has provided a fantastic API, and that lets tools like Analytics Canvas provide a solution.

How does it work?

Generally sampling kicks in at 500,000 visits in the query period. The way we can eliminate sampling is by breaking a query up into multiple queries by time period so that each individual query does not trigger sampling.

For example, imagine a site that gets 20,000 visits a day. Any query of more than a month in duration will trigger sampling. However, a query including 7 days will only involve 140,000 visits, and therefore the API will return exact data.

Analytics Canvas lets you automate this- we call it query partitioning.

Lets look at an example from one of our clients. We have done a query on a site for a period where there are almost 9 million visits. We’re looking for a specific source, so we have defined an advanced segment. This results in very heavy sampling- in fact less than 6% of the visits are actually included in the sample.

Lets do a comparison between the sampled data and unsampled data that we can get using Analytics Canvas. In this case, to make the query all we need to do is specify that we want to break the query up into 15 day increments to ensure that the exact data is retrieved. Analytics Canvas then automatically aggregates the results of all the different queries:

Here is how sampled vs unsampled data sets compare:

We can see that doing analysis on the sampled data alone could lead to very different conclusions and a significant amount of detail is lost due to the sampling process. While the number of pageviews is off by 8%, those pageviews are allocated by the sampling among about 400 pages when in fact, over two thousand different pages were viewed.

If you have a high volume site I’d strongly suggest you consider Google Analytics Premium where manual unsampled exports are possible. While a number of our customers subscribe to Premium, at $150,000 a year it’s not for everyone. But for companies that do serious business online it offers huge value.

So while there are limits on how much data can be included in a query, for both Premium and regular Google Analytics customers, Analytics Canvas can help you uncover those hidden insights.

The post How to eliminate sampling by using the Google Analytics API appeared first on Analytics Canvas.

Visits, clicks and pageviews don’t really matter – what matters is, for a given channel, is the value being created greater than the spend? Google Analytics lets you track this if you have the cost data uploaded.

Why automating cost upload is key to ROI tracking

If you have a manual, labor intensive process to track ROI, you are turning it into a postmortem-only measure.

Digital campaign optimization is not something that should be done only after the campaign is complete. Sure, you might learn something for the next campaign but you’ve already wasted all that money. If a channel or ad isn’t working, why keep spending money on it?

Constantly optimize your campaign mix

• Set up your spend and process in a way that you can quickly adjust where the spend is going. Specify a total daily spend but make it possible to determine each day where it goes make sure the people responsible understand that their budget will change daily.
• Automate your cost upload, so that you can refresh it each day. This means when the team comes in, Google Analytics will have ROI waiting for them for every channel.
• Every day, at a specific time, have a mix optimization meeting. Look at your best performers, look at the worst. Discuss the why.
• Using common sense, adjust the mix. Move the budget away from under performers to the channels that are delivering ROI.

Obviously, there are often other things to consider than the immediate ROI of a channel (is the channel one where for brand purposes you need to keep some presence? Is it something that is leading up to a planned coupon, contest or other event that will drive higher quality traffic, is the time span of a day too short to really see how the channel is performing, etc.)

But once you have a routine at a frequency that works best for your business and campaign, you can make decisions more quickly, move the spend to where it is going to do the most good, and your return on investment WILL be better than an approach where you wait for the campaign to be half (or worse completely) over before making adjustments.

The bottom line is that by automating the cost upload process you can analyze your spend more frequently without the painful, tedious exercise of preparing and uploading your data.

So get your automation on and keep your eye on the prize – ROI.

The post Automating Google Analytics Cost Upload for Maximum Campaign ROI appeared first on Analytics Canvas.

Funnel analysis is a key part of ecommerce analytics, and being able to understand how your visitors move through your cart and checkout process (and where they leave) is a key part of optimizing any website.

Google Analytics has some good functionality in this area, letting you see how many users are moving through your funnels for a given date range, as well as the excellent Goal Flow visualization that lets you see where visitors are coming from and going to around your funnel pages.

However, there are a number of types of analysis that are simply not possible within Google Analytics itself.

Pushing the limits of funnel analysis by using the Google Analytics API

Introducing the advanced funnel query in Analytics Canvas.

• Define a funnel using events, custom variables, goals, pages
• Look at your funnel on a segment by segment basis
• See the evolution of exit rate by funnel step over time
• Eliminate sampling in many cases for high traffic sites
• Look at funnels accross multiple profiles and accounts at the same time
• Automate your funnel analysis and integrate the data into your enterprise systems

Analytics Canvas lets you configure a funnel using an easy graphical interface, and then automatically creates all the API calls needed to give you the insight you need.

This new query lets you define funnels using events, custom variables, goals and pages. The result is a much more powerful way to understand how your visitors are interacting with your funnel and to have much more sophisticated funnels.

Here is an example of a series of funnel steps defined using the new feature:

Once you define the funnel, you get all the details for each step in a clear dataset with the following values:

• The number of visits that entered the funnel at that step
• The number of visits that entered from a previous step
• The total number of visits that completed that step
• The number of visits that went to a later step
• The number of visits that exited at that step

Whats more, you can specify the period and frequency that you want to run the analysis, meaning you can analyze your funnel performance as it evolves over time.

Why would you want to do this? Because if you are making changes to your checkout process, or signup pages etc., then you want to know when the exit rate of a funnel step changes FAST, so you can fix any issues.

We’re looking forward to seeing the more sophisticated analysis that serious ecommerce sites will be able to do with this new functionality- give it a try on your funnel and discover the optimization you are missing.

The post Analytics Canvas Advanced Funnel Analysis appeared first on Analytics Canvas.

• Google Analytics Cost upload and Bing Ads API connectivity
• Advanced funnel Analysis
• Enhanced GA profile management for those accessing hundreds of profiles at once
• Advanced query partitioning to avoid sampling

Cost Upload into Google Analytics for online advertising ROI reporting

Sure, ad words might be a significant part of your overall digital marketing spend, but it’s not all of it. When Google Analytics introduced the ability to upload data INTO GA and created its Ads return on investment report, your ability to track cost and return from all of your advertising campaigns took a quantum leap. Analytics Canvas is the best way to take advantage of this functionality, particularly if you have lots of ad spend sources, and want to automate. You can learn more here with a helpful tutorial.

Advanced funnels for ecommerce analysis

While Google Analytics provides funnel analysis, we’ve stepped up the bar by pushing the Google Analytics API to its fullest, and combining it with Analytics Canvas automation and database connectivity. If you want to better understand your funnel, you have to give this new capability a try.

Define your funnel steps using:

• Events
• Custom variables
• Goals
• Page path

Once you define the funnel, you get all the details for each step in a clear dataset, and can automatically generate funnel analysis monthly, or even daily, to track evolution over time.

Accessing and combining data from hundreds of Google analytics profiles at once

Many Analytics Canvas customers need to connect to dozens or even hundreds and hundreds of Google Analytics profiles. In V1.6 we’ve added even more features to help make this as easy as possible.

Filtered search, better options for multiple selection, editing and saving of profile lists make Analytics Canvas the choice of anyone with hundreds of websites that use Google Analytics. Check out our video tutorial that shows you how it works.

Sampling? No thanks!

If you try to query more than 500,000 sessions, Google Analytics will return sampled data. Analytics Canvas can automatically break the query down into smaller time frames, each of which is under the limit, so therefore avoiding sampling. Companies with serious web traffic can get access to raw data, and then pump it into databases using automation to integrate with their enterprise systems.

In version 1.6 partitioning is even easier to use, with more options for large numbers of queries and automation.

The post Analytics Canvas V1.6 Released- Cost upload, advanced funnels and easy access to hundreds of GA profiles appeared first on Analytics Canvas.

First, it was great to get together with practitioners and share expertise and knowledge, both seeing the “usual suspects” and meeting new folks.

The Keynotes

There were as always a series of great presentations- Jim Sterne’s “Sterne Measures” gave an inspiring look at what it takes to be an Analyst in today’s ever more data drenched world, Stephane Hamel talked “big data”- (including a kind shout out to Analytics Canvas in one of his case studies- thanks Stephane!), Simon Rodrigue of Walmart Canada gave an excellent keynote where he shared Walmarts perspective, and provided an excellent combination of vision and practical aspects in terms of tools and strategies.

Ginny Long of Moen, and Scot Wheeler of Critical Mass shared how Moen was tackling the challenge of attributing offline sales to online behavioral data, and Ross Jenkins from RAPP presented a case study around behavioral intent that was both entertaining and technically fascinating (which often isn’t easy to do).

The message- communication is key.

eMetrics is an amazing place to “get your data geek on” and talk shop- in fact, when practitioners get together it’s so great to be able to talk shop all the time that we all have to remember that one of the skills a great analyst has to have is the ability to talk about analytics and insight WITHOUT “talking geek”.

This was something that came up throughout the conference, starting with Jim’s first keynote- above all else, if Analysts are going to succeed in delivering all the value they can, and driving true business improvement through analysis, they have to be able to communicate to the business- not just themselves.

A recent post on econsultancy “a plea to all data geeks:speak human”- might be a bit harsh in suggesting we analysts are some sort of alien race- but the points are valid (and wonderfully presented).

Many of the speakers at eMetrics touched on this as well- an analyst needs to be able to tell a story, not just spout numbers or dive into technical detail when challenged or questioned.

When presenting information, of course there will be data and charts- but make sure that there is also the “So what?” Tell a story, and focus on both the insight, and the action that you think can be taken to drive business goals forward.

Jim underlined this very well in his presentation by putting it this way- “Have an opinion.” Don’t just give people data and dashboards. Tell them what you think, tell them the story you are seeing in the data.

You need the data and charts to back you up, but the business needs the insight- and your role will be more valuable and valued if you deliver it in a way they can understand and act on it.

The post eMetrics Toronto 2013 – Tell a story! appeared first on Analytics Canvas.

But Google knows it hasn’t provided everything. That’s why they created the Google Analytics APIs.

Many readers might be using an excel based plugin to pull data using the API directly into a spreadsheet for manual manipulation. Often this is a great way to start.

Here are five ways to take your Analytics to the next level using Analytics Canvas:

1. Avoid sampling and get your raw data

Nobody likes sampled data that is “close but not quite right”- and in fact, if you have lots of traffic, or when analyzing highly segmented data the sampled results won’t even be close, because the sample size can be extremely small. The problem arises when you request a date range in the Google analytics UI that results in more than 500,000 visits being included. But with the API, because you can do mulitiple smaller queries, you can often avoid ever exceeding this limit- and you get the exact data. To see how to do this with Analytics Canvas, check out this blog post.

2. Combine data from lots of different profiles and accounts

While the Google Analytics UI gives you great access to a single profile, it lacks tools for combining data from multiple profiles and accounts. Using the API lets you do this quickly and easily, and saves you lots of tedious export, cut and paste and manual merge. Analytics Canvas can query even hundreds of Google Analytics profiles at once, and consolidate all the data into a single file or database table, saving hours of work every week.

3. Integrate your Google Analytics Data with data from other systems

Because the API lets you get data into another database, it then becomes possible to combine data from your systems, or data sets extracted from other vendors systems and connect it to your Google Analytics data. If you manage your tagging and code right, you can use Custom variables to link your Google Analytics data to your CRM data for customers that login to your site, and gain new insight as well as provide better service.
Having your Google Analytics data be a silo, disconnected from all your other systems should be a thing of the past- integration lets you deliver the service your customers expect, and understand what works across your entire enterprise. For retailers, connecting offline and online datasets can give a quantum leap in understanding through techniques like tracking point of sale coupon redemption, online/offline offers and buying behavior regardless of where it happens.

4. Break free of all limits in Segmenting and exploring the long tail

While Advanced segments are very powerful, there are always limitations, and only so far you can push things within the Google Analytics UI. It means that by leaving your data only in GA you are forgoing a whole world of more advanced segments and analysis.

With Analytics Canvas, it’s no longer necessary to have an SQL expert, or a database programmer to create very sophisticated analysis.

By being able to first get at ALL the data, unsampled, then create any number of filters, segmentation rules and subsets, without limitations in terms of numbers of dimensions or metrics, an Analyst armed with Analytics Canvas can go farther, faster, and without needing to specify everything to the IT department.

This more advanced, free form analysis is all the more powerful when you’ve integrated your Google Analytics data with data from other systems.

5. Automate, Automate, Automate!

On top of all the above, because the API can be automated, whether you build it yourself, or use tools such as Analytics Canvas, it makes it possible to have the data be extracted, formatted and delivered without having to have an army of under utilized analysts wasting time on cut and paste. Reporting is often necessary, but if you’re doing it purely manually, chances are you are paying far to much, and are missing out on true insight that your analysts could be discovering- if they had some better tools in their toolbox.

Get the free trial of Analytics Canvas now and discover how to take your use of the API past a simple Excel export.

The post Five ways to step up your use of the Google Analytics API appeared first on Analytics Canvas.

If you use Google Analytics, and had more than 500,000 visitors in 2012 and want to use an advanced segment in your reporting (and you should use segments, because segments rock) then it means it is also time to deal with sampling.

• A query trying to see Non-paid search by source ignores 94% of the data on a site with about 9 M visitors in 2012

The evil yellow “fast access mode” box that informs you that GA is giving you an estimate only, based on a potentially quite small sample set. To do your reporting properly, you need to get unsampled data from Google Analytics- how?

One way is to just do lots of exports, each one on a time period small enough to avoid sampling. If you have a lot of visitors, then you might need to do dozens or even hundreds of exports, then add all that data up. This year, don’t waste all that time cutting and pasting. There is a solution to get unsampled data even if you have almost half a million visitors a day- by automatically generating all those queries using Analytics Canvas.

Avoid sampling and consolidate all your data exports into a one click operation

Analytics Canvas lets you avoid the nightmare this year. And because it has a 30 day, full function free trial you can even do your 2012 year end reporting for free.

In Analytics canvas, you can just select automatic partitioning, and it does all the work for you, making a query for every period, and then consolidating the data for you, ready to export into excel, or wherever you need it. Because its automatic, you can pick a period that is short enough that you KNOW there won’t be more than 500,000 visits, so no sampling.

We’ll show you an example- here is a query with a weekly partition- we’ve specified no more than 7 days per request, and set the date from Jan 1 2012 to Dec 31 2012. This results in 52 queries, and no sampling.

Do you need to have information for the entire year from Google Analytics and use an advanced segment? If you have lots of visits, then you need to watch for sampling- give Analytics Canvas a try for free, and discover how you can turn days of mindless work into a quick automated query.

The post Avoiding sampling in Google Analytics for your year end reporting appeared first on Analytics Canvas.