analytics tools

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Align your Google Analytics Channel Groupings with your marcom plan

by Kelly Kubrick on April 17, 2017

Cast your mind back to Planes, Trains and Automobiles, the Steve Martin / John Candy comedy where those modes of transport were to deliver the travellers home. Media has a similar concept with sources, or channels, that deliver prospects to us. Traditionally, those channels included direct mail, radio or TV, and newspapers or magazines.

Today, we have “new” media sources like Google and Bing (search), or Facebook and Twitter (social). When rolled up into categories like Search or Social those categories are known as Channels. However, sources are increasingly fragmented (how many social networks are out there today?), distracting us from knowing which channels are working for us.

Are you confident you know which marcom activities are worth continued investment?

Picture a busy but under-resourced marketing communications team challenged with finding prospects for a new brand. From the get-go, this team has done everything right. They undertook comprehensive market research and used it as the foundation for their strategic plan. That plan led to multiple outreach tactics / activities:

  • Forming strategic partnerships with established, aligned, non-competing organizations
  • Creating relevant, valuable content to be shared across multiple social media networks
  • Publishing relevant blog posts to encourage community engagement
  • Producing a monthly educational email newsletter (with just a hint of promotion) to efficiently leverage their blog
  • Purchasing advertising to to uncover potential pockets of customers
  • Launching an affiliate marketing program to entice bloggers and other websites to promote their message for them

Further, the team put together a measurement plan with established targets, and set Google Analytics up correctly to ensure they captured ‘clean’ prospect data. And, gold star to them – they were executing comprehensive digital campaign tracking to measure the impact of their individual activities.

However as the time requirements for juggling that many activities increased, the available resources did not.

Increased pressure to undertake more (and more) activities without additional resources

Within a few months, everyone wanted to know if all the activities were worth the level of effort required to support them, or if some could / should be cut. However, even as the data flowed in, Google Analytics seemed disconnected from the team’s activities and their reports didn’t support decision making. For example:

The team regularly reviewed their Google Analytics’ Channels report, labelled in the Google Analytics interface as “Default Channel Grouping”.

Default Channels Grouping

Google Analytics Default Channels Grouping Report

If you aren’t familiar with it, Google explains that the Channels report displays

“rule-based groupings of your traffic sources, [showing] your data organized according to the Default Channel Grouping. Default groupings are the most common sources of traffic, like Paid Search and Direct.”

And, according to Google, this allows “you to quickly check the performance of each of your traffic channels.”

The problem is that Google’s Default Channel Groupings aren’t necessarily how organizations might describe their Channels internally. Further, Google’s language labelling the individual Channel might not even exist in your organization’s vocabulary.

Even with measurement best practices, it can be hard to prioritize

So, although the concept of Channels makes sense in theory, typically, the Default Channel Groupings only make sense to the person familiar with your Google Analytics UTM code naming conventions. And, as with many organizations, the majority of the marketing communications team members weren’t familiar with the UTM name/value pair naming conventions (how are we counting paid social? is our email traffic really captured correctly?).

This meant team members weren’t confident in knowing which activities were captured in which Channel. And, if there’s a lack of confidence in the data, people start disregarding it.

Frustratingly, even when this Google Analytics savvy-team used advance reporting features such as expanding their report view to include Source/Medium as a second dimension of data (see screenshot below), the volume of data still obscured any insights to help them prioritize their efforts.

Google Analytics Channels report by Source Medium dimension

Google Analytics Channel report with Source/Medium as a secondary dimension

What does (Other) mean?

One of the frustrations of Google Analytics is the (Other) line item found in many of its reports. In the Default Channel Groupings report, it’s particularly difficult to discern what (Other) contains. Even when used with a second Source/Medium dimension applied, the underlying data still only makes sense to those familiar with the original UTM campaign parameter naming conventions. Even then, Other can take a lot of digging.

Instead, what if (Other) could be eliminated and the remaining Channels sorted into buckets labelled in a way that makes sense to your team? That way, colleagues would have much more confidence interpreting what the reports are showing them.

What to do? Take charge of the Channel rules

Fortunately, instead of using the Default Channel Groupings provided by Google Analytics, you can create your own, reflective of your own marketing-communications activities. Google Analytics provides a useful, and relatively friendly, “make your own rules” tool that allows you to override its ‘system-defined’ rules.

Thus, instead of hoping Google attributes your email traffic correctly, you can ensure your Email traffic does in fact land in the Email channel. Or, instead of having Google lump all your social traffic into Social, you can segment it into paid versus organic.

The ‘Custom Channel Groupings’ tool is in the Admin section of your reports, by View, under Channel Settings > Channel Groupings. With it, you can create a custom set of your own business rules to define Channels, and then toggle between it and the Default Groupings View. This screenshot below illustrates how you can toggle between the two:

Toggle between Default Channel Groupings and your customized channel groupings

Toggle between Default Channel Groupings and your customized channel groupings

 

Six steps to customize your Default Channels Grouping

You can create a Custom Channels Grouping report for your team using these step by step instructions. It’s time to take control of how your traffic sources are attributed in your Google Analytics reports!

1 Review your historical Google Analytics “All Traffic” report, ideally for a minimum of 3 months of data.

2. Look carefully at the “Other” group, and categorize it according to your organizational lingo. Do the same for Sources and Medium, identifying consistencies in both – by determining ‘typical’ sources and mediums (media, for the grammatically inclined). How do those compare to your activities? Which are the sources / mediums of traffic that represent your traffic driving activities versus sources of traffic you’re receiving ‘passively’?

3. In your TEST Google Analytics View (not sure what a TEST view is? See Why you want multiple Views in your Google Analytics), create a new custom Channel Groupings (View Settings > Custom Channel Groupings > + New Channel Groupings) report. In it, define your rules. For example, create a rule that states:

a) If “Medium” exactly matches “organic”, attribute that traffic to the Channel “Organic Search”; or

b) If Medium contains a string of characters generated by your email service provider, attribute traffic to Email

4. Leave your traffic to accumulate for at least 1 week in the TEST view. Go look to see where your traffic has ending up, by Channel. Is it where you expected?

5. Regularly refine the rules and with the intent of squeezing your ‘Other’ bucket to insignificance. Rinse and repeat to identify, classify and refine traffic as it materializes on your website in your TEST view. This is why it’s critical to build the report in TEST; it’s a safe place to refine your rules without affecting your production data.

6. Once you are happy with how your traffic is being attributed by Channel, re-create the same report in your Master View (again, see Why you want multiple Views in your Google Analytics). However – excellent news – instead of needing to recreate it manually, Google Analytics offers a wonderfully efficient way of “sharing an asset” within your own Google Analytics account, via email. In a matter of seconds, this feature allows you to ‘import’ your beautiful new Channels report into your Master View.

Once you’ve imported the new report in your Master View you can now choose to view data using your custom channels. Ta dah!

Below is a final screenshot that shows the difference in traffic attribution between the Default and the Custom Channel Groupings. Take note of a few of the items noted on the screenshot itself:

  • Red circle: Notice how (Other) has been reduced from 16.39% of the traffic to a mere 1.11% of the traffic? This helps eliminate confusion about what (Other) represents;
  • Navy blue circle: Notice how Referral has been broken out in to 2 Channels – MLL Brands and MLL Partners? For this particular team, Partners represents their organization’s strategic partnerships, showing them exactly how much traffic is coming from organizations whom they have formal agreements with (instead of mixing their traffic with other random websites that might be sending traffic). MLL Brands equate to this teams suppliers and represents a different expectation / relationship to the organization (known only to and meaningful only to that organization).
  • Yellow circle: Notice how Social has been segmented into 3 channels – “Paid Social” where paid media buys drove social traffic; “Organic Social (driven by MLL)”, representing traffic originating from their own organic, UTM tagged updates distributed through their own social media networks, and finally, “Organic Social (received by MLL)”, representing social media traffic they have received without sending out updates.

Default vs Custom ChannelsThis Custom Channel Groupings report offers the team much clearer insight into the impact / effectiveness of their efforts. This allows for faster decision making about which activities to pursue.

I strongly recommend you consider implementing it in your organization’s Google Analytics account.

If you have any questions or would like to discuss how to implement this at your organization, please feel free to contact us at your convenience. It would be our pleasure to put together a proposal for your review.

Have fun!

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Kelly KubrickAlign your Google Analytics Channel Groupings with your marcom plan

How to remove referral spam from your Google Analytics reports

by Kelly Kubrick on March 5, 2015

Referral or “ghost” spam is ‘bad’ traffic that can inflate your digital analytics reports and make it appear like your website is receiving more visitors than usual. It’s often characterized by very high bounce rates with one second or less session duration, and 100% new visits. To learn more, see the “Vanquish Referral Spam” section in this blog post.

I realize this probably looks overwhelming, but it looks worse than it is…and once you get into a groove, it’ll go faster. The first major clean up is always the worst, but once you start doing this monthly, you’ll be getting excluding a handful of spammers at a time.

Step 1: In Google Analytics run and export an extended time frame of the Referrals report:

  1. Change the calendar to an extended period e.g. 2 years
  2. Go to Reporting > Acquisition > All Traffic > Referrals and expand the number of rows to 500
  3. At the top of the report, click Export > XLSX

Step 2: When that report launches in Excel, click the 2nd tab, called Dataset1

  1. Click Data > Filters, which will enable you to filter the data to sort through it faster
  2. In Column G, Avg. Session Duration, click the little down arrow to open up your filter options. Click “Sort Smallest to Largest”, which will bring all the 0.00 second session duration to the top of your list
  3. Review the resulting sites listed in column A, and delete any that are legitimate referrals as we only want to identify the spammers
  4. You should end up with a list of spam sites. If you’re unsure of a particular referral, check the “pages per visit” metric. If it is 0 or 1, and has a session duration of 0.00, it’s spam – see the featured image above for examples

Step 3: When you have a final list, cut and paste column A into Notepad (or a similar no-formatting tool)

  1. Format the groups into a single line of text separated by vertical pipes|no spaces between each, so you get something like”
    “traffic2cash.xyz|best-seo-offer.com|www.event-tracking.com|semalt.semalt.com|www1.social-buttons.com|buttons-for-website.com|share-buttons.xyz|net-profits.xyz|free-social-buttons.xyz” FYI – that text string above is 182 characters; you can check using something like http://www.lettercount.com/
  2. Add one more character – a backslash before every period, so the above now looks like “traffic2cash\.xyz|best-seo-offer\.com|www\.event-tracking\.com|semalt\.semalt\.com|www1\.social-buttons\.com|buttons-for-website\.com|share-buttons\.xyz|net-profits\.xyz|free-social-buttons\.xyz”
  3. Create groups of about 10-15 referral sites. Don’t go much bigger than that as each final filter text string cannot exceed 256 characters, including the vertical pipes and periods. The amended string above is 194 characters – again, checked using http://www.lettercount.com/
  4. Save that file somewhere close by…

Step 4: Go back into Google Analytics > Admin > Account > All Filters and click + Add Filter

  1. For Filter Name, because you’ll be creating multiple filters, use a standard naming convention like “Exclude spam referral 1 of 10 – created 5Nov20XX”
  2. Click Custom > Exclude > Filter Field = Campaign Source
  3. In Filter Pattern, cut the 1st of your referral spam groups from Step 3, item 4 above
  4. Apply the filter to the TEST views only (so that you can see if they are working)
  5. Click Save
  6. Repeat for all remaining groups
  7. Annotate (need instructions how to do that? see this post: what you’ve done in TEST

Step 5: A week or so later, go back in and check your data in your TEST view

  1. Run the calendar for the last week
  2. Compare Reporting > Acquisition > All Traffic > Referrals between Test and Master views
  3. Assuming all is well i.e. that you see a decline in referral spam in Test, apply the filters to Master
  4. Go back into Google Analytics > Admin > Account > All Filters
  5. Click the name of the filter to edit it, and add it to Master view using the Add > to “Selected Views” tool
  6. Click Save
  7. Annotate what you’ve done in Master
  8. Pat yourself on the back!

Once you get the worst of the spam cleaned up, you can make a reminder to yourself to keep an eye on your Referrals traffic, and potentially add/edit new filters monthly. That’s why it’s important to add the ‘created date’ to the filter name, as you’ll be able to run the data as of that date next time thus saving yourself guesswork on what you’ve already excluded.

Have fun…!

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Kelly KubrickHow to remove referral spam from your Google Analytics reports

How to track digital campaigns using Google Analytics utm codes

by Kelly Kubrick on November 27, 2013

“Tagging” Credit When Credit Is Due: Understanding Digital Campaign Tracking

Imagine a website…It’s a good website. It deserves visitors.

 

 

 

 

 

Those responsible for it agree, and the marketing / communications plans initiate:

  • Press / news releases are issued
  • Advertising is purchased
  • Keywords are bid on
  • Emails go out
  • Social media gets conversational

Good news! Website visitors start showing up…

 

 

 

 

 

Lots more visitors…

Image credit: Penguins sculpture, by Nao Matsumoto

Image credit: Penguins sculpture, by Nao Matsumoto

And right in the middle of all the celebrations, you get the dreaded question. Someone asks you which marketing or communication effort did the trick.

They start pummelling you with questions – which effort brought the visitors? Which didn’t? How did the efforts compare? Which should we do more of? Less of? Should we double down on any of them? Or discontinue any of them?

And once they hit you with all the ‘quantity’ questions, they then want to know the ‘quality’ questions: which effort(s) brought the right visitors for the campaign objective?

And you slowly back out of the room…

I am pleased to tell you there is good news – you can answer all those questions, and with flair and panache. The bad news is that it does take some advance planning.

Campaign tracking is about taking – or ‘tagging’ – credit

Web analytics tools attribute visitors to 1 of 2 ‘default’ traffic sources: the “Direct” (aka No Referral) or the “Referral” source:

“Typical” split measured as by web analytics tools - Direct vs Referral

“Typical” split measured as by web analytics tools

 

 

 

 

 

Direct is traffic a measure of brand awareness

Direct traffic website visitors are those who arrive by bookmark or memorized domain or URL. Think of this source of visitor traffic as a measure of brand awareness; visitors must have had previous exposure to your brand or URL,  to recall or type it into a browser window and / or bookmark it.

Referral traffic is closer to publicity

By contrast, the Referral traffic source ‘refers’ (get it?) to visitors arriving via a third party website. However, to make Referral more useful, we immediately segment those third parties into more specific organic (or unpaid) sources. Examples include:

  1. Search: traffic from commercial search engines like Google, Yahoo, MSN/Bing or About
  2. Social Media: traffic from social media networks like Facebook, Twitter, LinkedIn or Instagram
  3. Publishers such as online newspapers, magazines or bloggers
  4. Institutions such as universities, hospitals or government websites

Think of these referral sources as a kind of publicity (for good or bad). And, as wonderful as all that referral traffic generally is, it can be challenging to secure, and it can be unpredictable. When it does show up, it is fabulous. And when it dries up, it can be scary.

To combat the unpredictable nature of referral traffic, we have another category of traffic source, known as “Campaigns”.

Campaigns are sources of traffic that you have defined in advance of your effort / spend

The definitions are unique to your organization’s marketing / communications / advertising efforts. When those definitions are aligned with your digital campaign tracking efforts, you’re able to isolate those visitors and report on them separately. You can answer questions such as”

  • Do particular campaigns bring more new leads vs. other sources?
  • Are those visitors of a higher quality? Do they read more content? Do they exhibit higher engagement?
  • Do they convert at a higher rate?

Campaigns are sources of traffic unique to your organization’s efforts to drive traffic

Campaigns might include:

  • Emails sent to your newsletter subscribers, prospects or customers that drive traffic back to your site
  • Display advertising (banners, buttons or other ad units) you purchased or traded for
  • Keywords you bid for via networks such as Google AdWords or Bing Ads
  • CPC (cost per click), CPM (cost per thousand) or CPA (cost per action) media buys from publishers
  • Social media updates posted to your organization’s profiles / feeds
  • Press or news releases distributed to your networks
  • Affiliate / partner websites where you negotiated placement; and even
  • “Offline” efforts such as print or radio ads (where you included a unique, or vanity URL)

As they typically require additional effort or cost, campaigns are those sources of traffic you’d like to measure return on, compared to the default direct and referral traffic sources. To do that, we need to isolate campaign visitors from Direct or Referral traffic sources.

But how do we isolate campaign visitors?

By tagging those sources of visitors:

 

 

 

 

 

Like marine biologists who tags wildlife to identify an animal later, or farmers who tag livestock to identify animals in a larger herd, digital analysts ‘tag’. We tag sources of visitor traffic to identify different segments in a larger herd of visitors to a website.

It’s just that we do our tagging via campaign tracking tags, otherwise known as “utms” codes in Google Analytics. FYI, ‘utm’ stands for Urchin Tracking Module. Urchin was the predecessor technology to Google Analytics, and the legacy term has stuck.

Examples of tags

Picture of a penguin tag

Penguin tag

Animals are tracked via physical tags that are attached to them. And digital campaigns are tagged via ‘extensions’ to the URLs we send visitors to.

Every digital analytics tool has a unique set of extensions available to track campaigns.

As a result, the specifics of campaign tracking implementation differ depending on whether your organization uses Google Analytics, Webtrends, Adobe Analytics or another tool.

Below, I’ve provide campaign tracking tags for Google Analytics vs Webtrends:

Google Analytics campaign tags

utm_source=source1
utm_medium=medium1
utm_campaign=campaign1

Webtrends marketing campaign or paid search tags

WT.mc_id
WT.srch=1

Web analytics tools recognize their own campaign tracking tags

When visitors arrive at your website via URLs that contain your campaign tracking tags, your digital analytics tool will recognize them as belonging to particular segments of traffic, and will attribute their arrival to the correct segment for you. Here’s how the magic happens:

When you create content that drives visitors to your website, you typically provide a link: http://www.mysite.ca

In digital analytics, we consider that an “untagged” link. And, regardless of which analytics tool you use, visitors who arrive via untagged links are attributed to the “Direct” source of traffic.

If you want to attribute visitors to a different source of traffic, you need to tag the link accordingly. To tag links, you ‘extend’ the link with extra information. And – the best part is that the extra information does not interfere with the way the web page is displayed to visitors.

Here’s an example of a tagged link:

https://www.onlineauthority.com/?utm_source=email&utm_medium=signature&utm_campaign=2013

What makes the link above special?

image of a question mark

 

 

 

 

 

 

Seriously. It’s the question mark.

The question mark signals that the link is what’s knows a ‘parameter’, and in the case of particular parameters, they are contain messages recognized by particular technologies, and ignored by others. So web servers ignore campaign parameters. Internet browsers ignore campaign parameters. And thus, there’s no impact on the user’s experience of your content.

Parameters have a particular structure: a question mark followed by an ‘equation’ separated by an equal sign:

?parameter-name=parameter-value-decided-by-you

So, if the parameter name were “source”, then you might decide the parameter value is a publisher or your house email list.

Or if the parameter name were medium, then you might decide en the parameter value is a banner or a particular email edition or issue.

Or, if the parameter name were campaign, then you might decide the parameter value is a campaign name like thanksgiving or rrsp-season-2013.

Examples of untagged links:

onlineauthority.com/digital-analytics-courses/

onlineauthority.com/digital-analytics-courses/learn-google-analytics

Examples of those same links, tagged:

onlineauthority.com/digital-analytics-courses/?utm_source=google&utm_medium=adwords&utm_campaign=2013

onlineauthority.com/digital-analytics-courses/learn-google-analytics/?utm_source=google&utm_medium=adwords&utm_campaign=2013

Notice how there are actually three parameters in there, all strung together by ampersands?

Examples of those same links, tagged in colour:

In the first URL, I’ve shown the parameter name in blue:

onlineauthority.com/digital-analytics-courses/?utm_source=email&utm_medium=segment-a&utm_campaign=2013

And, in the second URL, I’ve shown the parameter value in red:

onlineauthority.com/digital-analytics-courses/learn-google-analytics/?utm_source=email&utm_medium=segment-a&utm_campaign=2013

Once you’ve tagged your URLs with campaign parameters, or utms, and distributed them via email, social media, or as the destination URLS for your display ads, those visitors will appear in your campaign reports.

Where do the tagged visitors appear in my reports?

Look for them in your Traffic Sources, or Acquisition reports:

Screenshot to show where campaign-tagged visitors show up in your Google Analytics or Webtrends reports.

Campaign-tagged visitors are found in campaign reports in Google Analytics, Webtrends or other digital analytics tools.

 

 

 

 

 

 

Each parameter represents one report. Thus, the values of your campaign parameter utms will will appear in your Google Analytics campaigns report:

 

 

 

 

And, your Source and Medium parameter values or utms will will appear as secondary dimensions in your Google Analytics campaigns report, and as a stand alone Source/Medium report.

 

 

How do I tag my emails with Google Analytics utms?

Example of an HTML email with links circledIn the code of an HTML email, an organization can include links to their website. And those links can be extended, inside the HTML, with campaign tracking tags or utms.

So, again – instead instead of attaching a tag to an animal…we tag the link inside the HTML code in the email that brings visitors to the website. The tagged links inside this email might look like:

cic.gc.ca/english/immigrate/trades/apply-who.asp/?utm_source=bulletin&utm_medium=email_03&utm_campaign=aut2013

cic.gc.ca/francais/immigrer/metiers/demand-qui.asp/?utm_source=bulletin&utm_medium=email_03&utm_campaign=aut2013

 

How do I tag my social media with Google Analytics utms?

Social media screenshot with shortened linkIn a social media update, organization can include links to their website. And those links can be extended prior to being shortened, with campaign tracking tags or utms.

How do I tag my display advertising banners with Google Analytics utms?

 

 

 

 

When providing creative to your agency or to the publisher you’ve purchased advertising with, you also provide them with the URL you want them to link to. The button and banners above might have the following tags:

digitalstrategyconference.com/ottawa/2013/?utm_source=publisher-a&utm_medium=250×250-ros&utm_campaign=dscott13-eb

digitalstrategyconference.com/vancouver/2013/?utm_source=publisher-b&utm_medium=728×90-biz&utm_campaign=dsvan13-reg

In the examples above, the value of the source parameter is the name of publisher where the button ran (publisher-a vs b), the value of the medium parameter represents the size of the ad unit (250×250 vs 720×90) and its placement (run of site vs business section) and the campaign name represents the offer: the city and pricing codes.

How do I create my utms?

You can certainly create utms and tag URLs manually, using something like Google’s URL builder:

 

 

 

 

But, it’s far more efficient to do it via a spreadsheet, which will help you create and organize Source, Medium and Campaign naming conventions. That way, over time, you’ll maintain consistency, adding more value to your reporting and analysis efforts. In addition, you can use very simple formulas in Excel to automatically build the URLs and thus eliminate potential tagging errors.

Below is an screenshot of an example spreadsheet I created for my clients:

 

 

 

 

And with that – congratulate yourself! You’re now ready to ‘tag credit’ for your brilliant campaigns!

And of course, you’ll be annotating your Google Analytics reports throughout to provide context to the changes in traffic, right?

If this intrigues you enough to begin developing your organization’s digital campaign tracking strategy, contact me to request my campaign tagging spreadsheet template.

When you and your team are ready to roll up sleeves and dive in, we would be happy to provide a proposal to provide your team with training or consulting to implement digital campaign tracking for yourselves.

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Kelly KubrickHow to track digital campaigns using Google Analytics utm codes

Digital Maturity: the Data Strategy Dimension

by Kelly Kubrick on December 20, 2012

Originally published on the Digital Strategy Conference blog; republished with permission from dStrategy Media.

The third dimension of digital maturity is your Data Strategy. It is one of Six Dimensions of Digital Maturity™ assessed in the dStrategy Digital Maturity Model™, a business planning tool to help organizations improve their digital processes against an established standard.

Data Strategy icon from the dStrategy Digital Maturity Model An organization’s data strategy “reflects all the ways you capture, store, manage and use information.” Without a data strategy, organizations struggle with

  • Uncertainty about what data is collected / available
  • Poorly understood data standards, and how that can lead data quality issues
    • Is it ‘stale’?
    • Is ‘clean’ and / or ‘trusted’?
    • Is it ‘usable’ / is it ‘accessible’? In which formats?
  • Deciding how long they should store data
  • Who / which roles should be responsible for protecting and securing data
  • A lack of recognition of the strategic value of the data collected

Now, think about your organization’s approach to your data:

  1. Could you inventory the different data sources your organization has available? Within each, do you know what data you are collecting?
  2. How would you characterize your organization’s collection of customer data such as email addresses, ecommerce sales data, or member information?
  3. How would you characterize your organization’s use of data?
    • How ‘clean’ is your data?
    • Do you trust the data?
  4. Who is responsible for collecting and cleaning the various data sources?
  5. Are you collecting the data needed for you to take action with it?
  6. How quickly does your organization act on the data (offline / operational, customer, or digital) you are collecting?

When assessing your level of maturity in data strategy, think about the data you collect, how you use and share it and how frequently and how quickly you act on it.

Answering these questions is will help your organization determine if it is in the best position to implement your digital initiatives. What do you think? Have you got the right data strategy in place to ensure your organization’s digital success?

Next: Content Strategy

Next, let’s take a look at the fourth dimension, your organization’s content strategy.

Participate in the dStrategy Digital Maturity Benchmark Survey

For specific questions that measure the human resources dimension of digital maturity, take the dStrategy Digital Maturity Benchmark Survey. We will share our collective results at the next Digital Strategy Conference.

Learn how to measure your organization’s digital maturity

Or, to measure your organization’s digital maturity across all six dimensions, register for our upcoming Mapping Digital Maturity Workshop, a practical, hands-on learning session to help your organization create a road map for digital success.

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Kelly KubrickDigital Maturity: the Data Strategy Dimension

Digital Maturity: the Technology Resources Dimension

by Kelly Kubrick on December 10, 2012

Originally published on the Digital Strategy Conference blog; republished with permission from dStrategy Media.

The second dimension of digital maturity is Technology Resources. It is one of Six Dimensions of Digital Maturity™ assessed in the dStrategy Digital Maturity Model™, a business planning tool to help organizations improve their digital processes against an established standard.

Which technologies are in your technology toolbox today?

Technology Resources icon from the dStrategy Digital Maturity ModelHow has your organization addressed the availability and investment in the technology necessary for implementing your digital initiatives?

What types of digital initiatives are underway?

Are you publishing web content? Social media content? Email content?

If you are publishing digital content, are you managing your website internally or does your agency? Are you (or they) managing those efforts via content management systems?

As data is one of the outputs of web, email and social content management systems, are you using any kind of analytics tools to help generate insight in how those efforts are performing?

Are any of your people trying out any tools that let them collaborate more easily? Perhaps Google Drive or Dropbox to share files with your agencies? Perhaps Skype to avoid expensive long distance phone bills?

What kinds of rules and processes or governance do you have for the use of all of these digital technologies?

Answering these questions is will help your organization determine if it is in the best position to implement your digital initiatives. What do you think? Have you got the right technologies in place to ensure your organization’s digital success?

Next: Data Strategy

Next, let’s take a look at the third dimension, your organization’s data strategy.

Participate in the dStrategy Digital Maturity Benchmark Survey

For specific questions that measure the human resources dimension of digital maturity, take the dStrategy Digital Maturity Benchmark Survey. We will share our collective results at the next Digital Strategy Conference.

Learn how to measure your organization’s digital maturity

Or, to measure your organization’s digital maturity across all six dimensions, register for our upcoming Mapping Digital Maturity Workshop, a practical, hands-on learning session to help your organization create a road map for digital success.

read more
Kelly KubrickDigital Maturity: the Technology Resources Dimension

Google Analytics report Annotations: Your Analysis BFF (Best Friend Forever)

by Kelly Kubrick on March 5, 2011
Post updated repeatedly over time…!

One of my favourite features in Google Analytics is called “Annotations. It’s a simple concept, but incredibly easy way to add context to your data for everyone in your organization. that easily allows you to add a quick hit your reports with information specific to your operating environment:

google-analytics-create-annotation

After annotations have been added, they show up like this:

google-analytics-annotations-bubbles

and when expanded, like this:

google-analytics-annotations-expanded

Examples of the context you can add include

  • Email newsletter / blog publishing dates
  • Special event dates
  • Media coverage
  • Campaign start / stop dates, changes to creative
  • Changes to your page tag or profile / view settings

How do I annotate my Google Analytics reports?

  1. Chose a specific date in the calendar
  2. Click the down arrow at the bottom of the calendar
  3. Click Create new annotation

Or watch this 1 minute video:

 

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Kelly KubrickGoogle Analytics report Annotations: Your Analysis BFF (Best Friend Forever)

Why you want multiple Views in your Google Analytics

by Kelly Kubrick on December 10, 2010
Teapot image credit – Fairy Engine

Although the concept of having test vs. development/staging vs production environments is well known to the information technology world, it is not a common concept for those of us on the marketing-communications or business side of the lunch room. However, in digital analytics, the concept is critical.

In Google Analytics, a “View” is a collection of settings and definitions used to generate a unique set of your reports. A View is specific to your account and your organization’s page tag (or Google Analytics tracking code). Within a View, you can have custom settings, including setting a particular ‘home page’, time zone, establishing unique access rights by users, enabling filters and more.

Start with the Google Analytics account hierarchy

Google Analytics account hierarchy

Google Analytics account hierarchy

In Google Analytics, a View is the “inner circle” of the hierarchy of your Account, and the ‘level’ that you’ll spend the most time in.

By contrast, at the outermost ring, you’ll find your Google Analytics Account Settings that define ownership over contents of your account. In the middle, you’ll find your ‘Property’ settings.

Ideally, organizations will have 1 Google Analytics account, but within that account, they might have 1 or more properties (such as multiple websites / domains or a mobile app).

Finally, within a property, there can be multiple views (formerly profiles), which are all different views of the same data set, collected the same way for everyone with Views in the account.

Google Analytics account hierarchy: Account vs Property vs Views

Google Analytics account hierarchy: Account vs Property vs Views

Generally, your website equals your view.

However because of the availability of enabling filters, your Google Analytics account can – and should – have more than one view.

Additional views are generally created because of reporting requirements.

Views are typically created by copying a “master” set of data and then applying filters to the copy.

Filters are our friends

Filters are a means of eliminating unwanted or isolating specific information, thus filters are how we create different Views in Google Analytics. For example: If website XYZ.ca has no filters, we would call it “View A – Unfiltered” versus website XYZ.ca with filters applied, might be named “View B – Filtered”.

A typical rationale for a separate View would be to separate internal / employee website visitor activity from client/customer website visitor activity. Using filters, you can create Views of your website or mobile app data that:

  • Includes only only your prospects / customer and excludes your staff, agencies or contractors, or that
  • Includes only your staff, agencies or contractors but excludes your prospects / customers

Alternatively, you might want to exclude referral spam, also known as ghost spam traffic, which can inflate your numbers with ‘fake’ data.

Always best to create at least 3 Views

Knowing that there might be different filters needed, it’s better to anticipate the request by creating and maintaining at least 3 views in your account from the outset. Further, when you create the different Views, incorporate creation / modification dates and if possible, which filters have been applied.

The 3 views you want should include:

  1. Your “Unfiltered” or “Raw” data view
  2. Your “Test” view and
  3. Your “Master” or production view, where you want everyone spending their analysis time.

Unfiltered or Raw data View

Your ‘unfiltered’ view is exactly that – it includes all data collected by Google Analytics, and is reflective of the “gross” traffic to your website. It includes everybody and everything. And, once you’ve created it, you can ignore it. It will simply collect data, essentially giving you a backup copy in case something ever goes wrong. And believe me – it can go wrong.

Test View

Your test view is a copy of your unfiltered View, but it’s meant as a sandbox – or a playground – where you can safely create, test, apply, delete and generally experiment before applying ‘final’ version filters to your Master View. It’s also a safe place to test configuration changes: your search settings, or Goals or Funnel Visualizations.

Master View

Your Master view is copy of your Raw Data View – but this time with (your fully tested) filters, such as Exclude Employees, enabled and applied. This is the View you want everyone looking at. In fact, I’ve often named this view “USE THIS ONE – Master View: Excludes internal” so everyone internally knows its the place to be.

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Kelly KubrickWhy you want multiple Views in your Google Analytics