Your Web Metrics: Super Lame or Super Awesome?

Awesome Lily Web Analysts are blessed with an immense amount of data, and an amazing amount of valuable, even sexy, metrics to understand business performance. Yet our heroic efforts to report the aforementioned sexy metrics lead to little business action. Why?

Sure your organization could be to blame (org structure, bad boss, ineffectual team). Perhaps your client did not provide you with the all important Web Analytics Measurement Model. Maybe something else (surprisingly, excuses are not all that hard to find when you are looking for them :)).

Even with all that, I think the problem is you.

You: The person responsible for "providing data" / "analyzing metrics" / "reporting."

You are the problem because you, mesmerized by the enchantress that is web data, are reporting "crappy" metrics.

Since crappy sounds bad, let's just say you are reporting super lame metrics. (Sounds better right?)

Oh, and I don't mean reporting super, super lame metrics like % of Exits from a Page. I think we've realized that is absolutely useless for unstructured experiences (most web behavior).

I mean the metrics contained in 99% of web analytics reports: Visits, Page Views, or Time on Site. I mean the metrics contained in 99% of digital advertising reports: Impressions, Clicks, or Emails Sent. I mean Social Media campaign metrics like Number of Followers (or Likes), Video Views, or (just kill me now!) # of Press Reports.

Surprised to find the bedrock of your (and my) existence classified as super lame?

They are. And it is time we accept that. How else will we be recognized as the magnificent creators of business value, rather than people who whine about data (or worse, much, much worse, JavaScript tags and s.props and custom variables)?

These metrics are super lame because. . . .

1. They are supremely tactical.

There is nothing hugely business bottom-line impacting we can learn from them. Okay we got 17 million fans on Facebook. That was success? People saw 3.2789 pages last month and it was 3.3592 this month. Okay, now what? What does the number of press reports or views of our video actually tell us?

2. They simply report, usually, "top of the funnel" activity.

Getting people to just show up to our digital existence or just sending them email is not the point of what we do. Our goal as a non-profit is to ensure we get more people to our protest, more donations, more leads for places we can add value to. Our Goal as a B2B business is to connect a high value prospect to an Authorized Dealer / Rep, to try to revolutionize our marketing by going after the search long tail with AdWords, and more. It is not hard to imagine what a B2C site is trying to do.

So why is our reporting dominated by reporting of visits and time on site and impressions and all that? It's work, but what about what happens from that work?

3. They require too much inference.

When you present a large number of Visits or Page Views or Followers, what you are essentially inferring is that more is better. You are inferring something that is not there: success. Or you are hypothesizing, when you report that data, that these large numbers mean that customers are happy and business is successful. I believe it is dangerous to make that inference. Why not seek direct success indicators? Even for our branding campaigns?

4. They are "one night stand" focused.

This is perhaps the thing that makes me hopping mad and scream like a banshee. In the early days of the web it was cute to just get someone to come to the site and most stuff happened within one session / visit.

By 2011 as web experiences have become richer and more frequently and more complex I am so mad that our life is not dominated by pan-session metrics. That our campaigns are not focused on Visitors (not just Visits!), longer term understanding of people and customers (not just entrances and bounces!), customer lifetime value (and not just single visit conversions!), and all that stuff that is mandatory for the long term success of any company.

Frustrating when you think about it, right?

The bottom-line is that while they are all "standard" metrics, they measure tactical top of the funnel activity requiring too much inference and cause us to simply chase one night stands. Let us not make them the center of our web analytics existence.

Let us banish them to the land of "oh yes that was cute when our intern measured that when we first got a web analytics tool, but don't be silly, our dashboards don't contain that anymore."

sign right direction wrong direction

Let us move to the land of the "OMG that was such high speed from data to business action that I think I might have experienced a datagasm!" I.E. super awesome land.

Super awesome metrics. . . .

~ Force strategic analysis of metrics that contain data material to the business bottom-line!

~ They are infused with direct customer voice so we don't need to infer and look at data with our own biases (just let them tell us!).

~ Make us look at behavior across sessions to encourage a business focus on long term value (customer and business).

~ Due to their inherent nature in most cases they make it very obvious that the performance you are looking at is good or bad. It is hard to get to this, but it is so magical!

Salivating? Can't wait to hop into bed with 'em?

Now here is the amazing thing. You know which metrics I am referring to. I doubt I am going to shock you below. The problem is reaching datagasms requires some hard work (surprise!); it requires some fine caressing of the data; it requires going beyond the standard report in Google Analytics.

Here are some metrics I consider super awesome. . . .

Visitor Loyalty & Visitor Recency.

Notice my immediate focus on Visitors. Cookie issues be dammed (use first party okay?), this is the best we can do for now, use it! I love Loyalty and Recency because they measure what actually matter (repeated frequent visits by an individual. Do not be tempted by the not very useful % Repeat Visits).

For content sites (NY Times) it is focusing on a longer term relationship (and that might even mean not focusing on Page views per visits and reducing the number of ads on a site!).

For non-profits (The Smile Train) it means focusing on creating a connection that causes future donations.

For ecommerce sites (like Amazon) it means focusing on an experience to cause the next 20 purchases, or (like TurboTax) focusing on such a delight this March that I'll be back next March.

I love these metrics. When you focus on their performance it will force you to materially change your website experience, customer relationships and business value.

Why focus on conversion rates from your AdWords or DoubleClick campaigns? What was the quality of that traffic beyond the one night stand? Visitor Loyalty, bam!

[Learn ins and outs and how-to: Visitor Loyalty, Recency, Length & Depth]

Days & Visits to Outcome.

In some sense an enabler of the above. If your business leaders continue to want one night stand data then report these metrics (standard in Google Analytics and WebTrends and every tool).

Two different visits shows the length and depth of an experience leading up to an outcome (typically a ecommerce conversion, but could just as well be a lead, a donation, or any outcome you desire).

It helps force changes in customer experience (why just have a Search Travel Deals now and not a Save Travel Deals You Found So That We Can Email You When The Price Goes Up Or Down button?), it forces you to worry a out multi-channel campaign attribution (or not!), and more such delightful outcomes.

Strictly speaking, it is a pan-session metric (as are the above two), but I still think of it as a single outcome focused. So do this, migrate to above.

[Learn ins and outs and how-to: Analytics Tip #6: Measure Days & Visits to Purchase]

Conversation Rate.

Social Media is all the rage. Tweeting, Facebooking, Blogging, YouTubing. For most brands that, thus far, has simply translated to: "Oh we shout at people via TV, Magazines, Radio etc, what is the best way to shout via these new channels."

Sad. Heartbreaking. Your inner happy child just died.

Fear not. (She has nine lives!)

The true essence of social media, if you want to do it right, is the ability to reach your audience directly (no intermediaries) and have a relationship with them. If you want it. The essence of that relationship, one key facet, is the ability to spark and participate in conversations.

So why measure Followers and Likes and Posts? Why not measure Conversation Rate? For blogs: # of reader comments per post. For Twitter: # of replies sent per day, # of replies received per day. For Facebook: % Feedback.

If you are conversing, find out who you are conversing with. Is it adding any value to your brand; should you be doing it more? The roads to all those interesting questions, and incentivizing the right behavior by your company, starts with this super awesome metric.

[Learn ins and outs and how-to: Social Media Analytics: Quantitative & Qualitative Metrics]

Task Completion Rate.

The sub-title of Web Analytics 2.0 is: The Art of Online Accountability & Science of Customer Centricity.

That second part? That's why I love Task Completion Rate as a metric.

I see Analysts and Marketers and HiPPOs (of all sizes) torture the clickstream data, make leaps of faith, and start their recommendations with: "I think." Sub-optimal on so many fronts.

Don't think. Just ask.

Task Completion Rate is the % of people who come to your website who answer yes to this question: "Were you able to complete the task you came to this website to do?"

Combine that with the Primary Purpose question ("Why are you here?") and you have a gold mine of fantastic data. Why people come, how much you let them down. No guessing. No making stuff up. No inferring things from Time on Page or % Exits!

Use the customer voice, hit people on the head with it, reward those who work hard to improve the customer experience (based on, I can't stress this enough, customer identified pain and Omniture or Yahoo! Analytics guessed), and reassign those who don't. I call that #winning.

[Learn ins and outs and how-to: The Three Greatest Survey Questions Ever]

Economic Value.

What can I tell you about Economic Value that you don't already know? Oh, after Task Completion Rate, it is the single greatest gift a Digital Anybody can give to their boss / company / mom / angels.

It is the total $$$s (or Pesos or Rupees or Kroner) in Economic Value added to your business bottom-line by visitors to your website completing all the possible Macro and Micro Conversions.

Our inability to quantify the value of our digital existence is the single biggest reason for the sad undesirable level of appreciation. We just focus on the 2% conversion rate (orders or leads) value added. The thing we call Revenue. We forget all the other Micro Conversions. Absolutely criminal.

If your web analytics tool does not allow you (in five minutes without touching the JavaScript tag) to set up goals and goal values, then ditch it. You are wasting everyone's time; your mom is not proud of you.

Once you identify the Economic Value of your website you'll be able to clearly articulate: 1. All the jobs your website is doing. 2. True and complete value of those jobs. 3. Identify holistic value of your digital marketing campaigns. 4. Identify where you are falling short and where you are glorious. 5. Make your mom proud.

How is any metric that can help you do that not super awesome?

[Learn ins and outs and how-to: Excellent Analytics Tip #19: Identify Economic Value]

Five simple, effective super awesome metrics.

It is not that Visits and Page Views and Impressions and Fans and Clicks are useless. They are not. They are just not worthy of all the attention you give them. They are not. . . super awesome.

In the small chance that a picture is worth a thousand words, why take chances :), here's a slide from my recent keynote. . .

examples of super lame super awesome web metrics

So you can see there are many more super lame and super awesome metrics than mentioned in this article.

My hope is that the specific examples outlined help you find specific examples you can start your own revolution with.

My wish that you'll look not at the specific examples above, but more why I choose them for my Super Awesome list. The thinking behind the decision, the insights and value I desire. If you get that you'll be prepared regardless of what your company is up to on the web, regardless of what web analytics tool you are using.

. . . . and one more thing

I'll leave you with a practical example of how evolution from super lame to super awesome metrics (with a just regular awesome stage in between) looks like.

This is a real example of trying to measure how advertising done by a company is performing. They start at the normal place everyone else does; Clicks and CPC's. The company impact is just keeping costs low. I call this the Toddler stage (who, let me point out as a father of a small child are super duper awesome and I don't mean to imply anything else), but it is, super lame. How are you winning? How deep are your insights?

Then we mature to the regular awesome stage. The focus is on Conversions (yea!!!) and Revenue. Company impact is maximizing Revenue Per Acquisition. The Rockin' Teen stage. Good. But not great.

company impact measurement optionssm

[Click on the image above for a higher resolution version. The slide above is from my 60 min. webinar on YouTube: Agile, Outcomes Driven, Digital Marketing]

The super awesome stage is the last one. Ninja's live there. Measuring complete Economic Value to the business as the company impact. Kissably super awesome.

Consider this. Just look at the colored rows. You could have made a decision about which campaign was working better at each stage. But at only one would you have made the right decision and, because of how important that number is, earned a promotion.

That's what I'm talking about!!

Being super awesome.

You can create the above evolution for your company for any metric you desire, for any outcome that is expected by your business. And now you know how.

Good luck!

As always it is your turn now.

Surely you have your personal favorite super lame metrics. . . what are they? Why do you think they are "super lame" (or to be polite, less than useful)? And which metrics, if any, do you consider super awesome? Where have you fully focused your attention in order to identify valuable insights that have actually been actioned? What do you love?

Please share via comments.

Thanks.

Comments

  1. 1
    Flappy says:

    Hi Avinash,

    Great article, thanks.

    I consider every lonely metric lame, and all unsegmented data is pretty lame.

  2. 2
    Joe Teixeira says:

    Hi Avinash! Hope all is well with you!

    Here are my thoughts:

    – This post reminds me of your "So What?" test that you put together a while back (I think you're linking to it in the post). Applying the "So What?" test is a good way to validate this post (like when you say there month 3.2789 P/V last week and this month there are 3.3592 P/V…SO WHAT????)

    – I think the vast majority of the readers here are pretty much in agreement with you about Super Lame vs. Rockstar Super Heavy-weight Champion of the World metrics. But I think evolution is something that unfortunately is developing a lot slower than anyone would like to admit.

    – When dealing with / talking with the person that is new to data and new to the online way of being (it's 2011 but there are many folks who are still learning how to "be" online), we have to start with the super-lame metrics and the core fundamental basics. It takes time for the caterpillar to become the social butterfly.

    – Part of the reason for this slow evolution cycle in web analytics are the WA vendors. All of them, combined. Log-in right now to any tool, and what's the first thing you see? Visits, Time on Site, Page Views. For us in the industry, that's no better than the cover of a book or the front cover of a magazine. For many, many others, the "first page" is all that is seen, which is stunting our growth because books are often judged by their covers, although we teach our children and those around us not to do so. (Okay enough book / magazine references :)

    – How about a Super Awesome metric: Micro to Macro Conversion Impact? In other words, what was the number of Goal 17 micro conversions that led to Goal 1 MACRO conversions? This combines elements of rock-stardom like pan-session analysis, visitor loyalty, and economic value of the impact of searching your site, signing up for your monthly newsletter, or submitting a testimonial to a major (Macro) goal of buying a $500 tablet or filling out your RFQ and being a qualified lead.

    Thanks Avinash!

  3. 3
    Himanshu says:

    My super lame metrics are 'averages' and 'totals' of any metric you can think of like total visits to a site, avg. time spent on the site, website conversion rate, website bounce rate etc. They don't give any useful and actionable insight.

    My super awesome metrics are all those you have listed (and more like $index value) but at much more granular level. For e.g. i am not satisified with the loyalty and recency metrics on a site level. I need to know who is showing more loyalty and who is showing less & what i can do about it. It is better to know something like that non-members from a particular traffic source shows more loyalty than the site average.

    Similalry i am not interested in conversion rate of a website. I would like to know the conversion rate of each traffic source, medium and campaign, conversion rate of each website section, conversion rate of members vs. non members, conversion rate of high selling products….. I called this subatomic analytics. The devil is in the detail :)

  4. 4
    Tommy Merry says:

    Web Analysts are blessed with an immense amount of data, and an amazing amount of valuable, even sexy.

    LOL!

    I never thought of Metrics as being sexy, before :-)

  5. 5
    Ned Kumar says:

    Hi Avinash,
    As always you bring to fore some excellent points – in this case regarding measurement, analysis, & reporting.

    While vendors can definitely help in the transitioning of the 'thinking-culture' (from the super-lame to super-awesome), I think education plays a bigger role in moving ahead on this path. I am of the opinion that we should not be teaching the folks which metrics to use; instead, we should be teaching them how to think about adding business/economic value and let the metrics flow from it. This in my opinion will automatically cull out a lot of the super-lame metrics out of sight (& even if they are present, they will be a part of something else).

    The other thing this will do is to take focus away from "more is better". Taking Facebook as an example, one might start out by looking at # of fans. Does this add value? – probably not. The next step is look at # of active fans. Better? Yes, but not good enough. How about fan interaction in terms of # of posts/fan? Now we are beginning to get a sense of engagement. And so on…..

    I also think that Economic value can be used as the litmus test to decide if a metric is 'super-lame' or 'super-awesome'. To be classified as super-awesome, a metric has to directly impact or correlate with the economic value.

    Thanks for a great read.

  6. 6
    Shilpa Gupta says:

    Excellent Article Avinash. A great Web Analyst must segment and trend data in various dimensions. For example:

    Super Lame: What percentage of traffic is coming from each Source?

    Super Awesome: For each traffic Source, what is the Bounce Rate, Average Time on Site, Pages Per Visit etc.

    This can produce insights such as "Search traffic has higher intent than direct and referral traffic with lower Bounce rate,
    higher avg time on site and higher
    pages/visit."

    I recently posted an article on my blog for Effective Creative Testing (http://www.shilpagupta4.com/2011/06/28/effective-creative-testing-2/) where

    Super Lame: Success metrics
    Super Awesome: Success Metrics + Data for variables/Metrics effecting the testing environment.

    The idea is universal to look at data from all dimensions and segment as much as you can for actionable analysis and insights.

    Thanks,
    Shilpa.

  7. 7
    Randy says:

    Like everything else in moderation, I'm not sure any metric should truly be *banished*…

    While I agree that while top of the funnel metrics are often not particularly useful, the one thing they do provide is a measure of scale. Just as I'd look silly jumping up and down saying "We got 30,000 visits yesterday!", I'd be silly reporting a 50% conversion rate…if 1 out of my 2 daily visitors to a landing page converted and earned a Billion-dollar business a few dollars in revenue.

    When I'm presenting analysis, I'll show the numerator, denominator, the ratio, and the economic value. At that point, the business has enough to make a decision:

    – Is the campaign "successful" (conversion ratio, hopefully benchmarked vs. other campaigns)
    – Is the campaign "scalable" (denominator, top of funnel metric)
    – Is the conversion "profitable" (value per conversion, again benchmarked against other campaigns for budget allocation)
    – Is the campaign "valuable" (total revenue…$250 per conversion doesn't matter to a billion-dollar business, if there is 1 conversion per day)

  8. 8
    Josh Braaten says:

    My favorite metric has got to be economic value. Even done in the worst case scenario (All goals = $1, #5 from your post on calculating economic value), I'm surprised by how much it cuts to the chase because it factors in conversion rate and volume. More specificity leads to less rationalization about why at least "some" of the metrics are good.

    My lamest metric is "Mentions." Just because brand monitoring allows us to track everything, I don't think we should. Moving beyond mentions to "share of social voice" is of a lot more value than just simply mentions.

  9. 9

    You are so right in starting with p.i.c.n.i.c (problem in chair not in computer) principle.

    It is always about the people and what they do with the KPIs that are generated.

    And there is no such thing as 'rockstar metrics' and lame metrics – there are only rockstars and lamers.

    @Ned Kumar: Good Poinnt! Education, thinking and knowing the business is extremely important.

  10. 10
    Nicolas says:

    Love (and hate) this post!

    It shows me – one more time – than I'm expending most of my work day in lame activities.

    In my case I inherited tons of reports that all are expecting and I couldn't change the focus from data to action.

    My first step to succeed is show the lame metrics by segments trying to add some knowledge to the raw data I'm giving away.

  11. 11

    I've worked in the web industry for several years now and I'm constantly stunned at how people just want to see "number of visits" as a statistic and don't care about anything else. This goes for clients, developers, managers, you name it. I suppose the reason being is that people just like simple, big numbers that don't make them think.

    Of course once you start digging a little you realise that number of visits alone is worthless and rather easy to manipulate. I mean I've seen sites get huge dumps of visits from places like Stumble Upon which although immediately looks impressive is actually worthless once you analyse the data and see that factors like time on site and conversation rate etc were very, very low. It all goes to prove that quantity of traffic isn't everything, it's the quality of it and often getting 10 loyal and converting visitors is better than 1,000 who just bounce right off.

    Great post :)

  12. 12
    Gary says:

    Awesome. Datagasm.

    We report a lot in super-lame fashion. In fact, any ninja who read one of our reports would probably think that our customers may have been duped, and they're easy for any ninja to steal away. I would welcome all challengers on that front, because the super-awesome comes out of the conversations. In order to stay persistently adhered to business outcomes, we have to speak in a customer-centric way. That means, super-lame. However, that reporting, which we don't email until 5 mins before a real-time interaction (call, skype, meeting), is the foundation for our conversation. I would almost fear, with one or two exceptions, that introducing super-awesome metrics into the lexicon will confuse our customers. Instead, we rely on drawing those out from the actual conversations (and we insist those are weekly).

    At the same time, I worry about our customers hiring someone ninja-like, and them having poor opinions of our reports…based only on the once-over (sans conversation). Should be interesting to discover what happens there, because we love our customers, and they're smart, so it's only a matter of time before they hire a ninja or two… Anyway, thanks for another stimulating post, looking forward to the threads.

  13. 13
    Landin says:

    You nailed it Avinash.

    I think Google analytics and other vendors need to add a popup screen after logging in saying something like "What outcome are you measuring today?" and when a user clicks on it, it takes them to the segmenting page so it forces them to learn what they should be looking for and how use segments (surprisingly, a lot of people have no idea how to use this).

  14. 14
    Tim says:

    Thanks Avinash, great post as ever and great food for thought.

    One question about Micro-conversions and particularly Economic Value though: Doesn't the above treatment assume that all Economic Value via Micro-conversions in incremental? I.E. How does one ensure there is no overlap or over-attribution if all the Micro-conversions just contribute to the same end purpose (total Revenue / sales / etc)?

    Tim.

  15. 15
    John Stansbury says:

    Another great post that keeps WA and its practitioners honest. It inspired me to create the partially tongue-in-cheek Stansbury's Web Analytics Maturity Model:

    Mature: You know how and where to look for the next way to add incremental margin

    Maturing: You know how and where to look for the next way to add incremental topline revenue

    Nascent: Your favorite part of web analytics is hacking javascript

    Cheers,
    j

  16. 16
    rakesh kumar says:

    I am a newbie in analytics and your tutorials have helped me a lot.

    I wish more people can write like you.

  17. 17

    Flappy: You've captured the essence of my key lessons connected to metrics! And it took you one sentence, it took me a couple chapters of my books. :)

    Joe: You are right that we have to start in the "super lame" world, and then evolve. What I find heartbreaking is how many companies with years of analytics behind them are stuck with the "super lame."

    Part of the blame absolutely lies with the vendors. Just yesterday I shared this with the Analytics team: "Why don't we burn every single first report in all the section and move to an Acquisition – Behavior – Outcomes model? Right there on every first report let us show the depth of the metrics we have, focus on the three important pieces and train the entire world to think different? After that if people want to go to the lame tabs then they still can!"

    I'll let you know what comes of it. :)

    Himanshu: Agreed on how sub optimal averages are (while we are on the topic I would throw in percentages, compound metrics and ratios in there too!).

    Your super awesome suggestions are super awesome, but they are segmentation strategies for the metrics and dimensions that someone is analyzing. You are totally on the money about the value of that analytical strategy.

    Ned: As the founder of Market Motive, the teacher of the Web Analytics certification course, I could not agree more with you when it comes to the value of education. From your mouth to God's ears. :)

    The challenge is how to get everyone to get that "master certified" level quickly. This post is to clearly highlight what is lame and with that spark the need to be super awesome (seek education and evolution).

    See my reply to Joe on the vendors. I absolutely think there is a big role they can play in not encouraging super lameness.

    Randy: If you don't "banish" some metrics…. how do you focus?

    Ok just teasing you there. :)

    In the course of our analysis, you are correct, we will look at many metrics (including the ones I've listed as "super lame"). My hope is that the centrality of our analytical focus will be driven by super awesome metrics. Let them dictate what we consider important, if we are succeeding or not.

    I'm immensely appreciative of you adding a thoughtful perspective to the discussion (and some wonderful universally important questions).

    -Avinash.

  18. 18

    Ulrich: I smiled outloud reading your comment (and people around me on the flight were wondering why :)).

    I can honestly say I had never heard of the PICNIC acronym, and I love it.

    With every fiber of my being I believe that people matter more than all else – I like your framing that there are only rock-stars and lamers. :)

    Landin: Ohh. . . I love this idea.

    I am going to send this to the leaders in the Google Analytics team and suggest it as a serious consideration. At some point we are going to have to force people to think harder. Else there is no hope for all of us!

    Gary: I am with you on the need for evolution (as a couple other folks have also suggested). Let's start with the lame and aspire for the awesome (and then make sure we get there!).

    But if I were the person who saw one of the early Stats Bureau reports you describe below then I am afraid I might form a sub optimal opinion of Stats Bureau. I always looks for hints of super awesomeness (a focus on outcomes, applications of smart segmentation, beyond clickstream info etc). You don't have to have a lot of it, as I say I just need a hint (signs of intelligence if you will).

    You of course do great work, and as you say, that shines through in your in person presentations.

    Nicolas: Step one of any change is recognizing that the problem exists! :)

    The path forward you've described in your comment is optimal, I wish you all the very best.

    Tim: Here's a blog post on Economic Value that outlines how I view the macro and micro conversion framework (please see the ecommerce and non ecommerce examples mentioned):

    Usually macro and micro conversions are additive. I can buy something on marksspencer.com AND I can sign up to get email AND order a catalog AND look up a store AND…. so on and so forth. Hence the end result is Revenue from the macro conversion PLUS Economic Value from micro conversions.

    It is possible that for some businesses a micro conversion is additive, in those cases I would recommending adjusting the Goal Value (see above post) accordingly, and using controlled experiments to identify true instrumentality.

    -Avinash.

  19. 19
    HT says:

    Your hammer this point Avinash: draw insight from your data.

    As always, brilliant.

  20. 20
    Doug says:

    YES! This is now my favorite post of 2011. And not just because my company is building exactly the type of analytics application that measure these sorts of awesome, business-centric metrics – although the validation is certainly nice, don't get me wrong. No, it's my favorite because it gives a clear vision of what is possible and a path for getting there….and it lights a fire under the collective a**es to start making changes

    It's true that we've all been focused on lame metrics for far too long, but if we continue to chip away at the awful groupthink we've all been part of (i.e., thinking that lame metrics are actually awesome ones – wake up people) real value will be added. In the end, those with awesome metrics really will be viewed as superheroes!

    @Joe Teixeira – i agree with your point about the analytics tools highlighting and forcing these lame metrics upon us. But keep the faith – things are changing! Companies like our are hard at working trying to cut through the lameness. It is an evolutionary process and it won't happen overnight or with version 0.1, but it's happening.

    Really, just a great post Avinash. I'm off to tell everyone I know to read it. :-)

  21. 21
    pere rovira says:

    Hi Avinash,

    I'd love it if you could convince Google to make a Google Analytics for Rockstars :), where all the lame metrics simply don't exist… just as GA made a great favor to the industry by introducing cheap analytics to the world, now it's time that GA leads the way to a really different software.

    On the other hand, I think focusing too much on metrics as the main problem is also a mistake. To me, on top of reporting awesome metrics, the analyst needs to help and build the organizational culture / processes / etc. to make sure that a company is dynamic, risk-taker, customer-centric, etc.

    I know an analyst alone cannot be responsible for a company's culture, but without this, no metric is good. Hence, to me the right question is whether awesome metrics are enough in order to change a company's culture. My experience tells me metrics alone are not enough. I've demonstrated to some of my clients that they could make an additional million euros a year, even a month!, if they re-focused their advertising spend or reconsider the design of some landing pages. But it doesn't always work, and this is because not everybody in a company WANTS to make more money / have happier customers / etc. A lot of people, including senior managers (or especially senior managers) just care about keeping their jobs the same, working as little as possible and not risking to be different.

    And don't get me wrong… I LOVE analytics. But it cannot be anymore only about metrics. Focusing on action, risk, a passion for customer care… is just as important, and much harder than picking the right metrics. But also more rewarding.

    I guess you agree… and actually some of your articles offer some of the best tips to change a company's culture.

    Thanks for your blog, and your amazing readers, always the best read around.

    Cheers
    Pere

  22. 22
    Matt Lillig says:

    I say Avinash posts of video of himself "hopping mad and scream(ing) like a banshee" and we'll measure the number of "hits" it gets! And if it gets a lot of "hits", we'll throw some marketing dollars behind it with some display ads and that should lead to a higher click-through rate on those display ads…becasue we'll get lots of "hits". And THAT will be our monetization model and how we'll make money.

    This is seriously how some online marketers still think.

    Good post Avinash!

  23. 23
    Meryem says:

    I use basic metrics with a mix of custom made to analyze user experience and satisfaction while they visit my site.

    Working on them like minimalizing bounce rate, improving clickthrough and conversion rate to get it to even more closer to new benchmark levels is best fun jobs that I find every webmaster must be enjoying to make web even better space to visit for online world comforts.

  24. 24

    Pere: I assure you that with all my heart and soul I am trying to fight the good fight and get the tool to become ever more useful. Not just a collection of more and more data.

    You are right to point out the portfolio of elements it takes to be truly successful. It is not just metrics and not just smart people and not just the right organization and not just the right level of imagination and not just having process and not just the statistical horse power and not just the (what appears to be a whole lot out there in web analytics) javascript Godliness!

    It takes everything. We can be successful if we have some of the above things, but it is the quest to have all of those things that is key. Taking a cue from you… I would prioritize it all in this order:

    People (smart marketers and analysts), Web Analytics Measurement Model, Leadership, Culture, Tools.

    To me you start with the first and as you get good the second becomes the problem to solve, then you get good at that and the next becomes the challenge and so on and so forth.

    Would you agree on the prioritization?

    Matt: Ha ha! That is a super awesome comment. :)

    I do not doubt for one moment that it is exactly how many digital marketers think.

    -Avinash.

  25. 25
    Joko Susilo says:

    Great article.

    You explain clearly about web metrics. I learned a lot about the visitor loyalty & visitor recency from this post

  26. 26
    Tom says:

    Hi Avanish

    I agree wholeheartedly, and would actually go further. I consider 'web analytics' as a discrete discipline rather lame. By that I mean, why treat it differently? It is a source of business data that should be integrated with the rest of your business data to produce the most valuable measures and analysis for your business.

    I want to be clear, i love analysing web data, but it's the data i love, not the reports that are pre-canned in whatever peice of software i happen to be using.

    Once the data is stored and organised, and we have access to the tools to report and analyse it, i agree absolutely with your comments on the 'lameness' of certain measures.

    Tom

  27. 27
    Paromita says:

    Hi Avinash,

    Great article. I just need to add a new metric on the list – Lameness Ratio & calculate the lameness of the existing metrics and make sure that the online marketeers get to calculate that & put it on their PDRs…lol

    Wish everyone just understood things with this much clarity.

    Awesome !!!

  28. 28
    Mohit says:

    Avinash as always this is another great post from you.

    The key challenge I face is that people who are responsible for bringing ups / downs in these super awesome metrics does not want to look data in that way. They think that if they run a TV campaign which brings x% spike (up/down) in traffic is good enough to know.

    I am sure we all need another metric for our HR teams "%super lame hippos in company" they have hired in a period of time :-)

  29. 29
    Beth says:

    Avinash, LOVE the new look!!!

  30. 30
    Scott says:

    Hi Avinash,

    I don't think pageviews are entirely useless except when looked at on their own.

    One thing I discovered for a friend's site — I ignored the number of clicks and instead looked at the number of "Converted Visitors". I surmised that for her site (a web comic) a NEW visitor would have to read a certain number of comics (each on its own page) before deciding whether or not he/she liked it, and would also have to spend a minimum amount of time on the site to truly be reading and not just clicking.

    So I defined the conversion as:

    – New Visitor
    – At least 15 pageviews
    – At least 15 min on site

    As a result, we discovered:

    – If a new visitor stayed long enough for 15 pageviews, they would often stay for 50 and spend half an hour, with a good chunk would have 90 pageviews and staying an hour.
    – A referring site with a relatively low amount of clicks suddenly became a star player because it provided the most conversions.

    I'm not sure if this doesn't count as "super lame" because I don't just use pageviews or time on their own (it specifically applied to new visitors to see who would be most likely to go from from new reader to a regular) but just thought I'd put it out there to see your thoughts.

  31. 31

    Dammned! I have my "Web Analytics Master Certification Dissertation Defense" today!
    And I realyse I have been using some of those super Lame metrics to analyse this very Blog.
    God I am killed!

    Or perhaps it was beter like this because I would have trown ayaw my all report and started it allover again but had no time left to do so.

    Ok at least I know what John will harass me on.

    Well Avinash. In WSI some of my best emblematic colleges have put together this Competitive analysis template that is partially based on those lame metrics about social media impacts.

    My only consolation, If I don't succeed the master certification, is at least that I will be the hero of my WSI network when I will propose a revised competitive analysis template based on
    # of reader comments per post, # of replies sent per day, # of replies received per day, % Feedback.

    I just wonder, is there any tools that helps me gathering those info easily?

    We hear each other later today.

    Dominique

  32. 32
    Kim says:

    I love comparing any segmented metric from this year to last year to see if things are getting better or worse. Are we growing, flat-lined, or are we sinking?

    That seems key to me if you want your business to last.

  33. 33
    Emily Hill says:

    Thanks Avinash!

    I've found that sometimes I unintentionally let Lame metrics slip into a report b/c they're wearing Super Awesome clothing. That is, I forget that even a multi-facted, segmented, task-completion-focused measure can be useless to the audience if I fail to include an element of *Context*.

    To keep my Lameness in check, I use this test: "The Number-less Report." I ask myself, "If I had to literally cover up every actual number in this report, would it still tell a story?"

    For charts, this means my Super Awesome metric trendline better have a comparison line establishing context–a benchmark line from our past campaigns, say, or a goal line for where we need to be in order to meet our sales plan this quarter.

    For tables comparing metrics across segments or showing % change over time, this means I better have a bullet point that explains in actual words (yes, words!) what I find interesting about this information and what we can do about it.

    If your report could theoretically still be compelling and actionable without any numbers, then you can be pretty confident you didn't let any Lame metrics slip in, as sexy as they might appear on first glance.

  34. 34
    WendyB says:

    Well, according to you – I'm reading Web Analytics 2.0 right now – some are lame and some are awesome.

    Exit page = lame
    Bounce rate = awesome

    Your book is required reading for a social media class I'm currently taking.

    Good stuff! Thanks, WendyB

  35. 35
    Big SEO Agency says:

    Hi Avinash,

    I love your posts because I learn heaps from you. However, when I read them I can tell that they're positioned more toward 'in-house' analysts – analysts with one, or at least very few, sites to analyse.

    How you would scale the analysis of 30-50 blue-chip/enterprise client sites?

  36. 36

    Mohit: It is tough to deal with entrenched mindsets, especially if they happen to belong to the most Senior Leadership in companies.

    I've blamed us (Analysts & Marketers) for not doing more to engage our Sr. Leaders with such awesome stuff that they are forced to pay attention to what we are saying. Here's just one example of that:

    ~ The Difference Between Web Reporting And Web Analysis

    And I've taken every opportunity I've been privileged to have to get our Sr. Leaders to understand that they own a part of the problem and that they should fix that. Here's an example of that:

    ~ Online Marketing Still A Faith Based Initiative. Why? What's The Fix?

    At the intersection of those two things lies awesomeness. I hope we pull it off.

    Scott: The analysis you were doing, the hypothesis you had created (more page views perhaps equals value down the road) is super awesome. Let us separate that from the value of the metric itself.

    Web Analytics is all about creating hypotheses and then letting the data prove or disprove them.

    It is not clear from your comment where your journey ended. Did you find out that more page views equals more outcomes for your friend? More money perhaps, more speaking engagements, more leads, more comic sales? If so then that is great. If not then it might be optimal to consider what might be a better metric to show if business value is being created.

    The thrust of this post is to emphasize that obsession about outcomes and "awesomer" metrics that show us that. But in doing your analysis you'll certainly use many metrics (including some I lovingly call "super lame"). That is ok. Just don't let them become the destination, they are just a starting point.

    Emily: I like this idea a lot Emily, "covering up the numbers."

    I could not agree with you more about context. It is heartbreaking to see even great metrics languish in the land of no actionability because the Analysis Ninja (or hence forth… the so called Analysis Ninja) forgot to include any context.

    For those that are new I try and send them to this post first:

    ~ In Web Analytics Context Is King Baby! Go Get Your Own.

    Thanks for adding your perspective.

    Avinash.

  37. 37

    Hi Avinash,

    Thanks for your private answer, I appreciated it.

    Still you did not adresse my question about what tool do you know that would help us to find easily the metrics you encourage us to look at for impact of social medias.

    Thanks for all your help and support during this Master Certification Programm.
    It was Awesome as you like to say.

    Again thank you and John!

    Dominique

  38. 38

    Dominique: I'm afraid that we are in the very very early days of Social Media Analytics and at the moment there is no single source we could go to in order to get all the data that we need. This will change over time as social platforms, tool vendors, metrics reach some level of harmony (and throw up APIs!).

    Until then we have to follow the multiplicity strategy and use different tools. For Twitter, as an example, here are some tools that I use to measure success:

    ~ Twitter: Quantitative & Qualitative Metrics

    I hope the above post will serve as a template for the approach you can take for other social channels.

    -Avinash.

  39. 39
    Mark says:

    Excellent article! I find myself often falling back into the "super lame", partially based on previous expectations and the difficulty of reshaping this content to paint a better picture of performance.

    I really enjoyed Pere Rovira's comments about the current impetus on metrics without insight/influence into other portions of the business. It's often easy to get consumed by a single overly positive/negative metric and ignore other influences that are equally or even more important.

    I'd also happily vote for the "Rockstar Analytics" package from Google; the introduction of Goals has helped us a bit, but there's still a long way to go!

  40. 40
    mvarga says:

    Sorry @Avinash, as great your post is, this time we really enjoy

    @Ulrich Naegele

    Your PICINIC principle amused us very much.

  41. 41
    Daniel Smith says:

    Avinash – super awesome post mate.

    I'm so a toddler right now – looking forward to implementing some of your recommendations and becoming a ninja though!

    Cheers
    Dan

  42. 42
    Leinenbach says:

    You are always incredibly kind towards readers much like me.

    Thank you.

  43. 43
    Cleve Young says:

    I have given up simply accepting requests for specific metrics and sending back the report (unless it's from a VP of course).

    Whenever I get a request for a metric I respond with "What is the business question you want answered?" That way I can use my discretion as to what is the most appropriate data to supply. Granted, this doesn't always work and there is still WAY too much lame, top-line data being given out; yet slowely but surely I'm conditioning others to send me questions which need answers and not simply data requests.

    It's frustrating at times, but on those increasing occasions when I'm able to send back some super awsome multi-visit conversions which are tied back to sales and profit I get that tingly feeling which keeps me coming back for more.

  44. 44
    Paula Talmelli says:

    I love your post and your entire blog!

    But I miss the option to share the posts by email. As you said, email is still an useful and profitable tool. So why just share your knowledge through the social media? ;-)

  45. 45

    Avinash,

    This is a great way to focus on outcomes. Figuring out what to use and what NOT to use is great way to the path of success. Being in this industry for less than 2 years I really value the Ninja's, they are hard to come by :-)

    -Raghu

  46. 46
    Francisco Meza says:

    Lamest Metric = Browser Type and Pixels

    Better Metric = Conversions

    Best One I have = ROI

    I ordered your book and plan on attending your classes

  47. 47
    Hiren Vaghela says:

    Its really wonderful article Avinash. Web metrics is vital part always for GA. The way you explain i loved it and i didn't miss any video of your and Nick. So much thing i learned form the videos and now i have started to read your blog regularly.

    I also want to know where i can put my question where you are answering the various question video.

    Thanks in advance for your any input.

  48. 48
    Deric Loh says:

    Hey Avinash,

    You are the problem because you, mesmerized by the enchantress that is web data, are reporting "crappy" metrics.

    Ok time to share some humble thoughts :)

    Guess alot of time its getting into the minds of the respective business owners and clients on how we can help them "Shine" with the direct learning from the data and what are the immediate next steps for them to "Execute" which ultimately leads to how they can drive the desired Revenue increment or cost reduction and customer satification. And even if they can't fix that immediately, they are taking action based on the analyst's input.

    The more the analyst get into the minds of helping business owners succeed, and show the direct results leads to them slowly and gradually tapping into the expertise and recognizing the input from them. No longer just about some random figures from a data geek whom doesn't understand the business.

    Rock on,

    Deric

  49. 49
    Kunal raj says:

    Thanks Avinash, great post as ever.

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