Every once in a while I take a pause and answer your questions, your burning questions (!), about digital marketing and analytics.
For some answers, What is Avinash's typical day like? Hour-by-hour report please. :)?, you'll have to wait for my biography (thanks for asking Simo Ahava!). I'll answer a selection of other questions in this post.
We will cover questions in four areas: business/strategy challenges, analytics/technical challenges, career/self-development questions and rampant speculation.
Many of these questions have multiple possible answers, I invite you to participate in the discussion by adding your own answers via comments.
Let's do this!
^ Business/Strategy Challenges
Hi, I have recently started working with more enterprise clients, its been fun but there are a lot of new challenges. I am having issues prioritizing 1) recommending fixing on site issues affecting real traffic levels versus 2) correcting significant configuration issues in Analytics measuring current site traffic. Both are large scale issues requiring buy in from execs and multiple departments.
I need to pick my spots and decide where to assign resources first. Grow traffic first, with even with bad measurement I can find positive ROI areas for growth or invest time getting Analytics in order first for more objective decision making? How do you think about making reconsiderations for a scenario like this??
Prioritize by where you will make money for your client quickly. Even the worst analytics configuration in the world will most likely allow you to measure cart and checkout abandonment rate. If you can fix that, more revenue will immediately flow into your client's bottom-line. They will show affection towards you. Bank it. Next, it should be easy to measure bounce rates for landing pages (you would have to have zero code on the site not to be able to do this). Find campaigns where they are spending most money, lower the bounce rate and reduce acquisition cost. Earn more affection.
When you feel you have enough, use it to buy time/money to go fix the configuration problems.
The mistake we make is that we obsess about every big, small and insignificant analytics implementation challenge and try to fix it because we want 99.95% comfort with data quality. Six years go by. Nothing changes for the business. We wonder why data people are not loved. :)
Don't make that silly mistake.
Book two hours with the senior most company leaders who will talk to you, and create the Digital Marketing and Measurement Model .
If you have the DMMM, you have your priorities clearly laid out.
If there is anything you can measure, even with your broken analytics implementation, do that first. Add value to the business. Then prioritize fixes to the analytics implementation based on what your DMMM indicates is important to measure.
Leverage the Digital Analytics Ladder for Magnificent Success to help you prioritize where to focus next.
Identify where your company is currently, what the next optimal step is in the ladder and give it all your attention in terms of data analysis or analytics code fixes.
Three different strategies to help you figure out what you should do next, even with a horrible analytics implementation. What they have in common is they encourage you to extract whatever value from the data you can first, prove your worth to the business, and then focus on analytics code fixing.
How do you come up with compelling analytics KPIs if there isn't a simple relationship between online activity and profit, for example when you sell online content via a traditional offline annual subscription sales process??
I'm afraid there isn't enough context in your question to answer it specifically. There can be so many different answers based on your specific scenario.
But if you would like a quick collection of tips: Multichannel Analytics- Tracking Online Impact Of Offline Campaigns The enabler of tying offline activity to online is ensuring you have a weak or strong primary key. The post provides more detail.
I believe these two posts with a collection of some of my favorite metrics will inspire you: 1.Best Metrics For Digital Marketing: Rock Your Own And Rent Strategies 2.Best Web Metrics / KPIs for a Small, Medium or Large Sized Business.
Why is it so incredibly difficult to make people understand that last click attribution model is just idiot? That seems so trivial common sense that I am wondering if France is not in a parallel dimension.
This does drive me bananas! In this day and age using last-click attribution to measure digital success is spectacularly dumb. Genuinely awful.
Who is to blame?
First, I blame the analytics vendors. Vast majority of Adobe Analytics / Google Analytics remain last-click based. (Yes, yes, yes, with GA you can dive into Multi-Channel Funnels reports to move beyond last-click.) Many other tools remain 100% last-click based. If they won't take this seriously, how will they users ever see the light?
Second, I blame you and myself and all other analysts. Even when we have free solutions like MCF in GA with free attribution modeling tools, we don't really use them. Yes it does take a small mental shift, but if, the smart ones (!!), won't make the shift how can we blame anyone else? Are all your reports and presentations beyond last click?
Finally, and only lastly, I blame the management teams. They still tend to think of digital as a fulfillment channel. They have still not embraced the strategy for optimizing for marketing portfolios and still obsess about optimizing silos (they learned this from their TV, Print etc. strategies). They are actively losing money and actively creating upset customers. But they don't realize the cost. I blame their entrenched thinking.
Oh, and nothing is weird about France. Pretty much every company here is using last-click (at least until I visit them :)).
If you would like to move beyond the stupidity, sorry, of last-click:
Tactical advice: Multi-Channel Attribution Modeling: The Good, Bad and Ugly Models.
Tag Management. What you need to know before you choose third party tool.
First, if you are going to touch the code on your site make sure you get a tag management tool right now. Analytics implementations are getting numerous (tools) and more complicated with every passing data. Get a tag management tool. It will speed up code changes, it will improve the quality of your tagging, angels will sing songs in your praise.
How should you choose one? I'll share the same advice with you I'd shared about choosing a web analytics tool in Sept 2006… Get the nicest free tag management tool you can find. The Google Tag Manager is a good one, you don't need to use Google Analytics to use it. Deploy it. Enjoy it. Revel in its glory. At some point you'll bump into a small issue. Note down the limitation. If it is not a deal-breaker, keep using the tool, keep benefiting from it. Then you'll find something else. Make a note of that one.
At some point, three years from now, because you'll evolve your sophistication, you'll have five limitations and now it has reached a big problem point for your company. You now have your "what do you need to know before your choose a third party tool" list. You will make the smartest possible decision for your company because your selection will be based on your experience with a free tool that you actually used rather than reading competitive FUD literature, and you found actual problems you could not live without.
^ Technical Analytics Challenges
What would be the future of Adwords marketers with not provided searched query ?
- Their reflex would be to expand the number of bought keywords as work around (manual long train work) to try to understand the performance using directly bought keywords?
- It would drive a part of ads to cheaper bids (for the beginning) of long train keywords ?
- Adwords min bulk quotas to be displayed need to be reduced by Google to follow this responsive behavior ??
There might be some confusion here.
What has actually happened is that Google team has announced that they are removing the query from the referrer on ad clicks by users who use secure (SSL) search on Google.com. So analytics packages et. al. won't have access to this data.
But you as the advertiser will still see the data in the Search Terms report inside your Adwords account. You will be able to measure performance of your bids just as you did in the past.
There is a small bummer here for sure. I like to analyze my AdWords keyword performance using custom reports , especially using dimensions like Matched Search Query, inside Google Analytics and in context of other campaigns I'm running.
I can't do this anymore and I'm sad about that. But, I'm adapting to the new reality and playing with available options.
What is a way to analyze Not provided data in GA, its increasing day by, can you suggest how to analyze brand vs non brand out of it?
You are in luck!
Ok, only partially. But, here's an extremely detailed posts that looks at five different data sources to help you make the best of keyword data that is available in other places to optimize your SEO (or even PPC) strategies: Search: Not Provided: What Remains, Keyword Data Options, the Future.
The post covers what is still there in your analytics tools, competitive intelligence tools, Google Webmaster tools, AdWords Keyword tool, and SEO tools.
And you can definitely do brand vs non-brand analysis using these options. It is not perfect, but it is also very far from insufficient.
My question may be a trivial, but… Do I need campaign tagging with utm parameters for Google Analytics in order to receive more valuable information in multi channel funnel reporting and what exactly valuable information may I achieve ? Let use the question in general way.
Let's unpack what is going on here.
Most of the time the way Google Analytics (or WebTrends or whomever) knows where someone came from is by parsing the information in the URL. If someone comes from a link, that information gets provided to Analytics, you can see where the visitor came from. If there is nothing in the referring string, that visit is marked as Direct.
If you are deliberately sending traffic, say via a campaign or an activity you are undertaking, it is best to pass that in the referral string. That way Analytics knows it was your handiwork to send that traffic. It will put that data in Campaigns section of the Acquisition report.
Here's an example. I post on twitter, http://goo.gl/W6P01k, the link brings you back to my website, and you'll see this url:
The URL parameters help GA put the data in the right place and classify it as a campaign. Like so…
I can now see the value of my social media campaigns clearly, and segment them by Twitter, LinkedIn, Google+ and then lastly Facebook (Oh, I love you Twitter, I love you so much!).
So a very long way of saying that if you do anything to generate traffic, always use campaign tracking parameters. Always. Typically this will apply to Paid Search, Affiliates, Email Marketing, Social Media, and Display campaigns.
If you have a lot of them, aggregate them up. In my case above I can see individual campaigns or just create and advanced segment for social-media.
Fruition Internet Marketing
Do you have any metrics to measure the effectiveness of offline campaigns (Print/TV/Radio)??
You have three options at your disposal, depending on how hard you want to work / how accurate of an answer you want (and remember, you don't always need the most accurate answer – it is very smart to do, even back of the napkin, cost benefit analysis).
I'd outlined the simplest possible option in a post on how I measured the impact of one of our radio campaigns on our digital existence and profits. Here it is: Excellent Analytics Tip #12: Unsuspected Correlations Are Sweet!
The graph above is the end result, fascinating results. Please read the blog post for all the details.
Your second option is to ensure that you invest in various techniques that allow you to create a primary key to tie your offline campaign data with online behavior and outcomes. More details are in my post on tracking online impact of offline campaigns .
Finally, the hardest option, and the one that is most rewarding and perhaps even the most accurate, is to measure effectiveness of offline campaigns by leveraging controlled experiments .
My example in the post is about measuring the value of catalog and email campaigns, but the technique you would follow would be the same. For additional inspiration seek our media-mix modeling techniques.
Measuring multi-channel campaigns and outcomes takes some effort, but if you are willing you can totally do it.
Why is Google Analytics telling me that the average time-on-page for my homepage is 16 minutes? It can't possibly be true?
Two things to remember.
All web analytics tools by default don't measure time on page for a bounced visit. So if many people come to your site and leave instantly from your home page then their time in the system is N/A (not available). Of the sessions where time is measured (because a click was made on a link that goes into your site), it is entirely possible that for a good percentage of people they land on your site, go do something else, for whatever reason, later see the tab open and make a click and go deeper into your site causing a higher time period to be recorded for your site. They can't leave the tab/page open for a lot time, after 29 minutes of inactivity the visitor session is terminated. There could be other such reasons causing your high home page time on page.
Check if you have a high bounce rate, if so you don't need a lot of people to exhibit weird behavior for your time on page metric to get messed up.
Bonus reading: Standard Metrics Revisited: #4 : Time on Page & Time on Site
In recent years an increasing percentage of traffic is being labeled as 'Direct', for the most part I know why this is happening, but is analytics industry working on something that will provide more accurate 'Channel' attribution??
Here is a comprehensive guide to look over: Excellent Analytics Tip #18: Make Love To Your Direct Traffic The post shares six reasons why traffic is imprecisely classified as Direct.
I do think the analytics industry is all it can to classify your traffic as cleanly as possible. There are other shadier ways to solve this problem, they will break privacy laws and breach user trust and so I'm glad no legitimate analytics solution is doing anything like that.
Recently the single biggest reason for a spike in Direct traffic is the massive increase in use of mobile applications by all of us. A huge chunk of social media consumption is via dedicated mobile apps. And I don't think you need me to share with you the number of mobile apps, and numbers on mobile app adoption. Mobile apps don't pass a referrer, the visitor gets classified as Direct.
So, for every single campaign you execute, very link you share via social media, and every single action you might undertake on mobile, make sure you are using campaign tracking parameters .
All the traffic you generate will now be classified correctly. The ones others generate might not be, but there is not much you can do about it.
If you want to go one more step further and really ensure all things at your end of the responsibility spectrum are covered, check that you have your analytics code implemented completely and correctly.
My current challenge: I want to measure how much the increase in usage of my subscription-based online content is caused by an increase in new subscriptions, and how much is caused by efforts we make to stimulate older subscribers to use more our content (ongoing training, phone calls…)?
As far as I’m concerned, I’m dead on the unique visitors metric (or news vs. returning), as it seems more and more people/companies clean or block third-party cookies.
Short version: how can I measure the results of our efforts in client acquisition and retention distinctively, if I cannot totally rely on unique/new vs. returning visitor data?
You are right, you cannot rely on new and returning visitors/users.
This is a little bit of a complex problem, so you are indeed better off working with an authorized consultant who can evaluate your unique circumstances are help you implement the right solution very quickly. Here's a list: www.bit.ly/gaac You can also try to "figure out out" :), but I'm afraid if you don't have the technical chops (and that is ok) it will simply take you too long.
All that said there are two solutions that might work.
You can use custom variables, with scope set to Visitor or User, to anonymously identify people who have received your new subscriptions and measure increased content consumption by those people. You can also of course use this strategy to differentiate between new and old subscriptions. Oh, and if you want to analyze behavior of new subscribers from a specific time period, say everyone in Jan 2016, you can use the spiffy cohort analysis option in advanced segmentation . Truly sexy stuff.
Another more advanced strategy might be to leverage the User ID option with the new Universal Analytics roll-out by the team at Google. This will allow you to do some pretty spiffy things related to tracking people and do so across devices (which my above recommendation will not do).
Bonus: User ID implementation guide .
What is the best way to avoid sample data in segments and views in GA? (without upgrading to GA premium :))
Use standard reports. They are not sampled (unless you apply filters of some kind or advanced segmentation on top of the report and other such things).
Sampling kicks in most frequently when you are looking at the data across a very large time period and use my favorite Google Analytics features like Custom Reporting and Advanced Segmentation.
Also please remember that while the default sampling is applied at 250k, you can change this (look at the top right of any given report) to anywhere from 1k to 500k.
For a more detailed and specific answer: How sampling works in Google Analytics
With sampling what GA is trying to do is not have you wait for five hours to get a perfect answer, or have your query time out, both of which happen commonly in other tools for large datasets. It is very quickly trying to five you a good enough answer. It uses very advanced strategies to ensure it is a good enough answer.
Sometimes that is simply not sufficient. Either our peers don't know how to use sampled data, or have a psychological barrier to overcome. In those cases, please use the techniques outlined above or pay for the Premium version.
^ Career / Self-Development Questions.
How to not get frustrated if you are responsible in corporation for digital marketing, but you are the almost only one there, because digital dept. is nonexistent and you get to your Hippo two times per year to discuss digital things?
On the surface it may looks like that everything is running smoothly as you care about website, run campaigns, do reports & analyses, but you know all the time that your company did not buy "big picture" yet.
It does not seem like your company takes digital marketing seriously. If they did, you would see the HiPPO more than twice a year. Even if you were not the most important person on the digital side of your business.
So with that as a background, what do you do?
If you have enough influence (and you can have that even without a big title), then try to take charge of as much of the digital effort as you can and prove to them that by being serious you can win big. Pick the area with the most amount of revenue or cost, use data and digital savvy to improve revenue even more or reduce cost a lot. That will attract attention.
If you have very little influence, try to pick a small area. Say, email marketing. Rock it. Prove how well it can work. Perhaps the right light will shine on your effort and your management team will take you seriously, and then the digital business.
If you have no influence, keep doing the best you can but get your resume ready and find another job. This is not always an option, you might be in a geographic location where this in not an option at all. But if it is an option, in this type of a scenario without any influence for the sake of your personal passion and ambition you are better off some place else where you can add value and achieve professional success.
Do you believe that a person who focused on the technical in and out of the analytical tools, had a job that did nothing but implementation and training users how to use the tool, is at a disadvantage to those those that only use the tools to drive insight / reporting but cannot tell you how the tools work?
If yes, why do you think this is the case and do you think it is fair??
It is one of those cases were we have to define what disadvantage really means.
If you consider disadvantage to be having a limit on how high your salary can be and how high your influence on the business side can be then yes, I do believe that having a job that is only focused on implementation is a disadvantage.
But if you are at your happiest doing a job that is technically challenging and allows you to solve difficult data collection and data processing challenges, then it is not a disadvantage. You are doing what makes you happy. Is there anything more important?
As to why I consider it to be a disadvantage (with the above mentioned definition)… Analysis is an incredibly difficult challenge not because it is hard to use the tools, it is hard because you have to be comfortable with ambiguity, you have to deeply understand business strategy, you can't just stop at data puking rather you have to identify actions to take (which means big network of people relationships and business savvy) and compute impact and then recommend things that will work (or you are out of a job). These jobs also mean, for better and for worse, more interfacing with senior management and influencing them (in your technical job you won't as much, even as your job is important), and that does matter a lot.
So, those jobs will pay more, will allow you to drive more change than a job that is simply implementation and tools training.
For more on this, and salary structures and job promotion options, please see this post: Analytics Career Advice: Job Titles, Salaries, Technical & Business Roles.
What is the best way to start really learning Google Analytics, beyond the basics? Certification? Specific reading materials? or just old-fashioned hands-on training??
If you simply want to learn how to use Google Analytics, your very first stop is the Google Analytics Academy, learn all the material in the Digital Analytics Fundamentals course and proceed to take your Google Analytics Individual Qualification (IQ) test.
I do believe that tools training can take your career forward, but less far than you might desire. You want to actually get good at analytics. The business of analysis. Transforming data into insights. And all that good stuff.
In that case seek books, blog posts, certifications that teach you how to think about analysis. This blog is a good start, :), but there are others. I link to some in the right navigation. You are welcome to consider my book Web Analytics 2.0 (which is not tool centric).
In terms of certification, I'm biased but I do recommend the Web Analytics Master Certification program at Market Motive (my start-up) that focuses on the art and science of analysis (and not reporting or a particular tool).
This blog post shares other practical tips, books and certification options: Web Analytics Career Guide: From Zero To Hero In Five Steps!
Thanks for everything you're doing for the community. As a B2B marketer looking to get more heavily involved in web analytics, I'm looking for a place to start – specifically your books.
As a beginner, should I plan to start with the slightly older An Hour a Day, or is that information already in or updated within your second book Web Analytics 2.0? ?
Please also see the post above titled Zero to Hero, I believe you'll find it to be of value. And please see the Unmissable Articles listed on the bottom right of this post.
^ Rampant Speculation
Suzanne van Tienen
To what extent do you personally believe unique user (cross-device) and persona based analytics will succeed – and stick??
Let's get this out of the way: The world already lives in a multi-device, multi-channel world. It is silly, even today, to pretend otherwise. Your current, today, right this very moment, digital analysis should be based on person-based analysis.
Not people-based, a euphemism I use to refer to small groups of "persons" where you can't identify any one person. Person-based, where you can track a person and their behavior across devices and channels. Digital first. Digital and real-world in the near future.
How likely is this?
See my reply above to Joseph Boisseaux where he, rightly, complains about all of still being stuck with last-click attribution. And switching away from that is actually really easy, and businesses still refuse.
So person-based analysis will take a long time. Initially it will just be technical challenges (it is really hard to implement a unique user_id tied to one person, no matter easy analytics tools say it is). Then there will be challenges related to privacy and government rules (unclear at the moment, and if they become clear what their impact might be).
Does this mean you should not try?
No. You are making wrong decisions already by not focusing on person-based analysis. Every little step you take away from visit-based analysis makes you less wrong every day. And that is totally worth shooting for!
Let's end on that note of optimism.
As I'd mentioned at the start of this post, each question above could have a slightly different answer. I would love to have you jump in and help the folks who asked the above questions benefit from your experience and wisdom. Please share your insights via comments below.
Thank you. Merci. Arigato.