Occam’s Razor by Avinash Kaushik

Know the difference between a Reporting Squirrel and a Analysis Ninja?

One is in the business of providing data.

One is in the business of providing, to use a old fashioned word, information.

This one of the core reasons why most dashboards are “crappy”, i.e. they are data pukes that provide little in terms of context and even less in terms of actionable value.

Here are some examples of sub optimal dashboards, sub optimal in my mind from a actionable perspective. . . .

Perhaps the most common type is above. Lots of data, even drill downs included, but you can’t look at it and go: “Wow we need to do . . . “. No sirrie bob you can’t.

I wanted to point the above out purely because of a common feature of 80% of Web Analytics Dashboards, in excel with a billion tabs to look through. This is not a dashboard, it is the result of a massive sum of money paid to a Consultant who is trying to impress you with his / her excel skills - without actually telling you anything.

You are walking down the street. You look at someone from behind and you think “hmmm she’s / he’s pretty”. So you speed up and overtake them and in the process you sneak a glance at them (yes you are married but looking is still ok :), and you are hugely disappointed. Not pretty. That’s the dashboard above. Very sexy and Web 2.0′fied and a ton of data there, but a lot less actionable than you might have hoped.

Why is this so? All the above efforts are well intentioned, took lots of honest work and probably took months to put together. So why?

Here are some hidden (corrosive) reasons why most dashboards tend to stink when it comes to helping the Executive make any decisions:

1. They leave the interpretation to the Executive (/ customer / requestor / other Squirrels). This is a fatal flaw because most dashboards are highly aggregated views of any KPI and are missing all the nuance and analysis (that only you as Ms. Ninja have, and you don’t go with dashboard).
2. Most Executives actually want insights / action recommendations but they don’t trust the Squirrels / Ninjas / VP’s / Data Providers. So they ask for numbers. We dutifully cram as many of them on to a A4 size paper in 3 size font and send it along with a magnifying glass.
3. Most Squirrels / Ninjas live in a silo. Going out to collect enough tribal knowledge to actually know what is going on to then make recommendations from the data is not something that we do, nor are we encouraged by our Executives or our organization structures. This incentivizes data pukeing.
4. Often dashboard creators tend to be “outsiders” (Consultants, Experts etc) and they often don’t have deep practitioner experience that would allow them to understand the human / “below the surface” issues like the above three. That leads non-Practitioners to make the common mistakes like creating the above three dashboards.

If you want your Executives / Customers to take action, you have to give them information and not data. It takes effort to get there, it will take all your charms (though no violation of any HR intimacy policies), and it will take some time.

Step one as always is to become aware of the above three problems.

Step two is to get a possible solution from the Occam’s Razor blog. :)

My attempt at solving this problem was to try and attack it from a human psychology perspective: How can I create a “dashboard” that will incent the right behavior from the Squirrels / Ninjas while giving Executives the information they need to make decisions (rather than engaging in a bitchfest which is the typical outcome).

Recommendation #1 was to move to a Critical Few philosophy for Executive reporting: Only report the three or five (at most!) metrics that define success for the whole business. Kill all the ancillary metrics that were nice to know (and my kill I mean let lower levels worry about it).

Recommendation #2 was my humble, admittedly ugly, attempt at a “Action Dashboard”:

4Q. (Sorry Jonathan! :)

Each quadrant representing a solution to a human problem that lead to crappy dashboards.
(Apologies for having to redact some of the data above, to protect the innocent.)

Let me walk you through it.

First very up top a clear identification of what the Critical Few metric was, who was responsible for that metric from a business perspective (translate into “head on the line”) and who was responsible for the analysis.

Also note the little red dot. That here indicated trouble. It can have two other colors, yellow for don’t fire anyone yet but get ready and green for send someone a big hug and a box of chocolates. Next. . . .

The first quadrant (the graphic) shows the trend for the metric. Ideally segmented (as is the case here, cart abandonment is illustrated for four key customer segments).

This quadrant is to satiate Executive curiosity that you know what you are doing, it will be glossed over (and that’s good!).

The second quadrant (Key Trends & Insights) is to add value by interpreting the trends and adding context. It says there that some things are up or down (in english :), and it also warns which data might be bad etc. You are starting to do your job here.

This quadrant is the one that Executives will read a lot initially, over time they will gain confidence in you, they will love that you share context (hello Ninja!), over time they will gloss over it (a good thing).

The third quadrant, clockwise, (Actions / Steps To Take) is force the shy Web Analyst to get out and talk to Marketers, Website Owners, VP’s, Whomever it takes to get all the tribal knowledge, identify root cause for the trends in the metric and recommend solid action to take. The Analyst will rarely be able to do this by themselves. It will require human contact with others, it will require conversations, it will mean identifying solutions collaboratively. It is a fantastic opportunity to become smart about the business.

This quadrant is key to driving action. No longer do you leave things to interpretation or let’s blame people etc. You are recommending what actually needs to get done. Your Executives will kiss you and over time this is the only quadrant they’ll read. It will also mean that monthly meetings will move from bitch fests to deciding who does what. Amen!

The fourth quadrant, (Impact on Company/Customer) exists in case it is not clear to the Executives why they need to take action (listen to poor old you the lowly Analyst). I feel it is the key thing missing from any dashboard, they are normally missing the kick in the rear end and this quadrant delivers it. It is the answer to this question: “As a result of this trend (up or down) what was the impact on the company and its customers”. It also forces you, Marketer / Analyst, to do hard work to estimate the impact and put it on paper.

This is the killer quadrant, if nothing else drives action this will, knowing exactly how much money was lost, how many customers were pissed, how much opportunity was wasted. Now when they ignore you they do that at their own peril and with their butt on the line. Trust me action you recommend will be taken.

See how simple it is?

You fix the human problems, you address the flaws in the system today and you actually become much smarter about the whole business (thanks to q3 and q4).

Win - win - win.

Over time you’ll gain a lot more trust from your Executives and all the crappy dashboards can die and be replaced with one that looks like this one. . . .

Now you are asking your Executives to simply layer their own judgment on the recommendations and help the company take action. Who needs to see the numbers? They pay you and I to deliver actionable insights.

I stress that it won’t happen overnight, but shoot for that nirvana state.

May the force be with you.

Ok now your turn. Care to share your own learnings and battle scars? Your success stories? Perhaps critique my “Action Dashboard” (sorry could not think of a better name, do you have suggestions?). Your perspectives are most welcome and would be greatly appreciated. Thank you.

PS:
Couple other related posts you might find interesting:

• Five Rules for High Impact Web Analytics Dashboards
• Web Analysis: In-house or Out-sourced or Something Else?
• How Should Web Analysts Spend Their Day?
• Seven Steps to Creating a Data Driven Decision Making Culture.
• Six Data Visualizations That Rock!

Reality: A small fraction of people who can benefit from data actually use it.

This is especially true for the world of web analytics.

I realize as we swim around our fish bowl this seems hard to believe. :)

But it is very true.

Sure one problem is that many Fortune xxx companies don’t even have a web analytics solution or, worse, are paying z millions for it and using it to report page views.

Either little or quite sub optimal use. And that’s a shame because you can get a lot lot lot more from the web analytics tool.

So why are we in this sad state?

In talking to many Marketers and Sales folks and Website Owners and “Management” it becomes clear that much of the hype about web analytics being like climbing to Mount Everest or being useless or messy or full of “dirty data” has sunk in quite deep. [Tears rolling here.]

Or “web analytics” auto translates into people’s minds as “counting hits”. [Uncontrollable sobbing by me at this point!]

People would rather pull off a finger nail than learn how to leverage their website data. [Large clumps of hair pulled out, to clean the aforementioned tears!!]

This is all soo sad because the reality is that. . . .

Web Analytics is like Angelina Jolie: It’s sexy, it kicks butt, and is a goodwill ambassador!!

Right?

We believe it, but how do we get to a point where others in the organization do as well?

Step One for each and everyone of us (and you are unique and abnormal in that you read a web analytics blog!) is to accept and recognize the fact that Web Analytics might be having a lot less impact than it should. Once you accept then you can move on and do something about it.

Step Two is to realize it is a challenge to win a Olympic medal in swimming, but that should not scare you from trying to learn to swim and get pretty good at it. There is a shallow end of the pool where it is easy to get started and get better over time. Nothing wrong with wanting to compete at the Beijing Olympics of course, just make sure upfront that that is what you are shooting for with your effort: one massive payoff after a lifetime of investing.

Step Three is to try and get everyone in your organization just a bit more excited about using data, make it more appealing than pulling off finger nails. Maybe even attempt to convert them into Raving Data Lunatics (people who will do anything to get their hands on data before making their next decision!).

A reader’s email started this whole train of thought:

I’m going to try to convince decision makers within my company that they should start incorporating web analytics in their everyday work. However, these people have more than enough on their table and adding another task on their todo list is easier said than done, to say the least.

My question is: Have you run in to this before and do you have any good tips on how to approach these people in order to make them all fired up for the task and adding it to their todo list without hesitation?

See yourself reflected in this reader’s email? I am sure we all find ourselves in that situation from time to time.

Go do Step One and Step Two first, then here’s how to do Step Three. . . .

# 1: Do Something Surprising: Don’t Puke Data Out.

You are undeniably smart. When we get a new job or interact with a new team or get our first web analytics tool installed our first tendency is to impress the Marketers and Decision Makers with the quantity of data we have.

We proceed to puke data out.

Reports go out. The adventurous amongst you might even export into excel and proceed to send 16 tab spreadsheets with every conceivable number anyone could want, along with the directions to heaven.

Try to resist.

That is what they expect, by now, and they are wary of data pukes.

Surprise them.

Give them a gift, a gift of an answer.

Go have a conversation with someone who wants to talk to you and listen. Ask these questions:

“Please tell me a little bit about your job?“
“What aspects of your life / job touch our website?“
“What’s one question you wish you could get answered about our website, or what’s one thing you could learn from our website Visitors?“

Now go back and answer that one solitary question. Don’t send a report back. Call them and tell them the answer. They’ll be hooked after you do this once or twice.

Now teach them to fish (metaphorically of course).

Remember you can’t convince people by puking data out, you can’t expect that “they’ll figure it out“, and repeating things sixteen times or moping about how “they don’t get it ” does not work.

Smile, go have a conversation and go back with a answer. How is it possible that that won’t work? You are so pretty!

# 2: Start With Outcomes / Measuring Impact, Not Visits.

Just open any web analytics tool and you’ll notice that Visits and Visitors and Time on Site and Repeat Visits and Pages and other such stuff stares at you.

Go ahead try it, I’ll wait here. Check out any one you like: Google Analytics or Omniture or WebTrends or CoreMetrics or the one your brother-in-law just invented (the one that proactively sends a small electric shock to Visitors who abandon shopping carts on your website).

And like duty bound people that we are we rush that out of the door. We try to explain cookies and time on site and exits to our Decision Makers.

You might as well be taking Japanese (unless you in Japan, in that case you might as well be talking Hindi).

When you start make sure you start by showing how wonderful Web Analytics is at measuring Outcomes, the reason for your website’s existence.

Show them how much money your website is making. Show them how many leads you got. Show them Macro and Micro Conversions. Show them how the site is solving for driving traffic to your retail stores, or movie theaters.

All those things they get! And they’ll be hooked.

Then they’ll ask:

Angie, where do these people come from?
Jennifer, how come that is only $14 million, what about all the great persuasive content we have?
Maya, is this right, only 15 people out of 20 million checked out our store locator, why do you think it is (because the link is invisible!)?
Michelle, so you are telling me our pathetic website is generating more leads than all our sales people combined?

See what I am saying?

They will ask you for “traditional web analytics ” data, but if you start there they will have very little appreciation for why it is important to listen to you. What’s your hook? Not the purple shirt and pretty jeans you are wearing today. Its Outcomes and Impact.

Go back to wearing kakhi’s, and give them the addictive stuff.

Or to put it in Bill Clinton’s famous phrase: It’s the outcomes stupid .

# 3: Create Heros & Role Models (and no, not yourself, put your red cape back).

It is really hard to convert the entire organization, and it does not matter if you have 50 people or 20,000. And here is the other troubling factor: why should they all, at the same time, listen to you? And do you even think you can excite everyone all at the same time with something generic? And. . . . I can go on about the reasons.

Find someone receptive to your advances (and I don’t mean in that way). Find a willing partner, find someone with low hanging fruit or with a willingness to listen to you or someone who will atleast let you tag the site right or someone who is spending a lot of money or someone with a small site or. . . . you catch my drift.

Now put your heart and soul and all your skills as a Analysis Ninja in finding them actionable insights. Live and breath their business (ps: this is always a good idea). Make the Decision Maker a absolute hero from data driven decision making.

Here is the amazing piece of human psychology: Heros rarely want to stay in their cubicle farm / corner office and be happy. They want to fly around (in your red cape no less!) and talk about their heroism. They want to share (/brag).

Let them tell your data story. Let them excite their peers. Let them show how they did it.

And here is the amazing thing: You still come out on top.

The other Decision Makers / Marketers will, again human psychology, get jealous and will want to themselves become heros (or get a higher bonus as well). They will ask the original hero how she/he got so smart. Guess where all the roads will point: You my dear.

Go ahead sit down on your gray chair and smile a evil smile, and don’t forget to stroke that white cat as you smile! :)

Ok so that is me just teasing you a bit, but you can never go wrong by creating evangelists for the impact data can have on a business. Create those evangelists, make them heros, let them sell.

You just go find a gray chair and look for a white cat! Ok ok I’ll stop now!!

# 4: Web Analytics 2.0 Baby! Use Your Customers & Competitors.

HiPPO’s might not listen to you. Marketers will be full of themselves. Even your boss won’t really pay attention to you.

Here is the dirty little secret: You have two powerful weapons - your Customers & Competitors!

I have consistently found that few HiPPO’s or Marketers or Decision Makers will argue with your Customers, and hence customer insights. You can tell them all you want that dancing monkeys on the home page don’t work. But give them that same feedback from 4Q (a free survey - checkout the improved invitation ) and bam the dancing monkeys are gone!

So use this power.

Figure out what your best customer listening channels might be (oh and clickstream is not a direct customer listening channel, I call it Behavior analysis, here I am recommending Experience analysis - more: Trinity Strategy ).

The other great strategy is to build excitement by using competitor metrics (say using something like compete.com or hitwise.com or other sources - say customer satisfaction survey indices).

No one wants to look bad in comparison to their competitors and everyone wants to beat them with ever more consistency! Leverage this!

Present analysis about share of search or media mix modeling or upstream and downstream traffic or task completion or other such things.

Don’t you think Marketers at DHL will be so much more happier with the above graph (”oh what are we doing so well!”) and ones at FedEx and UPS will want to know how to get better.

Problem of excitement solved!

# 5: If You Want Excitement, Make It Fun!

Ok ok so perhaps not everyone thinks Analytics is Angelina Jolie. (Boy that was hard to say!) But have you tried to make it Sexy and Fun?

(Oh I totally forgot to ask you: Have you drunk the Kool-Aid? Forget almost all of the above if you are not convinced that Analytics is Angelina Jolie. Nothing harder than trying to convince people of something you don’t believe in.)

There are so many small and big things you can do to make Web Analytics fun.

Do #2 on this list first, it is always extremely sexy and in fashion to make money / improve conversions / measure multichannel impact. But try some of these other things as well. . . .

Hold contests.

The first time we ran a multivariate test we wanted everyone excited (and learn some statistics) and so I had a contest. $1 to get in and the challenge was to guess by how much conversion rate would improve from that first test.

Oh boy everyone wanted a piece of it. We had 25 dollars I think before the test started. Guesses were all over the place, 5% and 20% and 9% and …. As soon as the test was live they were all checking the Offermatica results (and I had explain statistical significance!) and asking why B was not winning or D or whatever they were rooting for.

It was a hoot. And they learned about testing and a very valuable lesson: That to have huge impact on conversions you need to create versions that are very different. You see the conversion in that test only went up by 0.75%.

The winner had guessed .65% (and was laughed at before the test started because it was such a low number). I was the winner. And I put the $25 to buy cookies for the office. :)

Do such stuff. Have a quarterly contest to the person who figures out the most useless metric on your “golden blessed dashboard”. Or the Marketer that figures out the most creative use of VOC. Or the department that logs the most actions taken. Or . . . . you are more creative than I’ll ever be.

People love to play, and they love to win. Tap into that.

Hold Internal “Conferences”.

Why is it that you need to go out to learn and share? Why not hold a half day “conference” in your own company every quarter where Marketers come and show off their key learnings to everyone else?

Find the biggest conference room you can find (or book a conference room at a nearby hotel), mike them up, have them do presentations, let them teach.

People will learn from each other, but it is also exciting (and a honor) to stand up and present and teach. Oh don’t forget to invite their bosses.

If you want to go all out, print shirts (you can get them for as little as 15 bucks!) or, this works really well, hand out a plaque to the presenters (something they can proudly display on their desk, trust them they will - right Jeff? :).

Notice you also just made someone a hero.

Hold Office Hours.

We often live in our caves (with our Angelina Jolie posters!). All requests have to come in via the ticketing system, it will be “prioritized”, Excel goes out.

Sad.

Each week set aside half a day where anyone can come and ask you (/your team) any question they want. About a existing report or for some ad hoc analysis or for how to access / interpret report. This is not so much fun as much as you’ll become more accessible and people will know that when they want to learn you are there.

Or have a scheduled hour where you invite Marketers / Decision Makers and have them shout out questions and you show them live with ClickTracks or IndexTools or AdCenter Analytics how you can answers their questions on the spot!

Fun is your friend.

End of the story. . . .

Web Analytics is exciting. It can be a amazing high when you figure out a new way to analyze the data, or answer a real business problem. Sometimes you answer a particularly tough Marketing problem and then Web Analytics can even be a orgasmic experience.

But you need to think different.

Try the above tips, and I wish you all the very best in exciting your organization (big or small).

Ok now your turn. Would you care to share some of your insights? Big or small? What has worked for you? Please share your own strategies and success stories. Thank you.

PS:
Couple other related posts you might find interesting:

• Six Rules For Creating A Data Driven Boss!
• Seven Steps to Creating a Data Driven Decision Making Culture
• Convert Data Skeptics: Document, Educate & Pick Your Poison
• Competitive Intelligence Analysis: Metrics, Tips & Best Practices
• Five Free “Advanced” Web Analytics Examples: Look Outside, Think Different
• Multiplicity: Succeed Awesomely At Web Analytics 2.0!

Common complaint: “Sure I have web analytics data, I have no idea what to do! I swear I have really tried hard and looked at all possible reports. I can’t find anything interesting“.

Does this sound like something you would say?

Know what the single most important missing ingredient?

Context.

Often numbers don’t “speak” to you, or as loudly as they can about what you should do, because you are missing the context you can place around those numbers. Something that makes you want to take a pause and say: “ahhhh I get it now” or “ahhh that’s interesting. . . I wonder if. . . “.

So what is this mysterious magic potion?

Its quite simple really, in its simplest form it is surrounding your Metrics, Key Performance Indicators, Reports, Dashboards etc with other information (quantitative, qualitative, tribal knowledge) that adds a pinch of color. Context.

Here’s an example. . . . .

Undoubtedly you sent your Manager / Director / VP / Mom this month’s “performance” / site statistics for this month. Perhaps it looked this this:

What can you infer from this? Almost nothing. Even less than nothing if you are a step removed from the daily existence of your site (or even months existence).

Now let’s do what ClickTracks does best, add a touch of context. All I am going to do is add a couple of segments that might help add a color to the above web metrics.

Here it is:

Now answer the same question again: Can you infer anything from this?

A lot I am sure.your site.

For your 116,503 Visitors you know some interesting things: Approximately half came from search engines, only a tiny fraction, 5,288, did what you wanted them to, look at product pages, and, perhaps more humblingly, a tiny tiny fraction converted.

From the second set of data for Average Time On Site you get a sense for the varied distributions in time each segment spends on your site. 64 seconds might have felt like a hurtfully low number for your beautiful engaging site. Now you know that atleast some people spend more time on

Now I’ll admit the above picture might not quite be God’s gift to you, but it raises the right questions that need being asked.

It will also help focus the initial analysis effort that you’ll undertake. You’ll ask why 51,398 Visitors to your site spent 43 seconds on average on your site. Where do they enter, what keywords, ppc or organic? What can we fix? is 239 seconds the right amount of time to conversion?

Well worth the nine seconds I spent on it right?

Simple context makes data a lot more interesting, helps you focus and find some actionable insights. Reporting rule #0 in my book: Never report data in aggregate, or by itself. Always always always test to see if you are including context!

Sold?

Here are other techniques that you can apply in your quest for insights when you look at your own web analytics tool. . . .

# 1: Compare trends over different time periods.

Cheapest trick in the book. Honestly.

The question we are trying to answer is: “does this dashboard communicate anything of value?”

Its cute, I’ll grant you that. But really when push comes to shove it is not saying a lot. Especially to people who might not be immersed in your data (except for you of course!).

Now try this: choose a comparable time period, the last month or same month last year or whatever makes sense in your case.

Boom!

Ok so maybe I am getting excited about this. But look carefully insights, ideas, questions, are staring at you.

First you have had a awesome last 30 days (make sure your boss knows, she needs to look like a hero!).

Additionally for some the other metrics are coughing up insights. It is normally astounding that your traffic went up 45% and the bounce rate only went up by 3% - it is extremely rate to get that new traffic that is that qualified (quick find out what the Marketers did!).

Page views held steady as well, as did time on site, all good signs. And what’s up with those three spikes, so unrelated to other time periods that match so closely? Dig please.

Quiz for you: What does that % of New Visits number (and delta over last month) indicate? I found it to be very surprising. Add your answer to the comments.

# 2: Compare key metrics and segments against site average.

Yes, yes, yes, averages can sometimes lie. Ok ok ok many times. :)

But they can also be your friend, especially when to comes to helping you get the initial set of context that you so sorely need to make your mass of web analytics clickstream data actionable.

You are really curious about your Direct traffic (also called, default, unknown source, bookmarks etc etc). In a couple of clicks this is what you are looking at:

Hmmm….

Nice? Things are going well? Maybe? “Avinash is wrong, web analytics is hard!” Ok ok, try this… two mouse clicks in Google Analytics … choose compare to site average for this stream of traffic. . . .

Abacadabara!

Sweet! See meaningful data, closer to you than you had imagined.

For “Direct” traffic now you have a at a glance knowledge of the vital stats. Smaller % of the traffic, but astoundingly valuable, by most measures you see above (time, bounce, pages etc).

See that is totally missing from the original picture. That second picture you can send to anyone in your company, or outside, and they won’t ask you what the definition of Bounce Rate is or how Time on Site is computed. They’ll understand performance. Because you gave them context.

This is how you get beyond the bickering about definitions are numbers, you get to have a discussion about what actions to take. Priceless.

# 3: Couples Rock!! :)

You need someone. I need someone. Everyone needs someone. Why not our metrics?

A very common mistake in reporting is to simply report on the important metric you care about by itself. I call these important but lonely metrics. I feel sad for them.

Why not pair your important metric with its husband / wife / “special friend” / partner / mistress? You’ll understand performance of one and get actionable context from the other.

Its like sometimes you meet a person, and you are not sure what to make of them. Then you meet their significant other and you say “ahhhh everything makes sense now!” (Am I being a big mean here? :)

Let me explain, look at this common report, its important, I am sure you are sending it out to everyone:

Ok so that’s nice. What do I do? Buy more Google? Dump MSN?

What you see above is just data, nothing useful.

Try this simple thing, find it a friend. . .

Oh la, la, now you are cooking!

The spouse metric (Bounce Rate) gives context to your core KPI (Visits) and suddenly this metric is a lot more useful. Any lay person, or a Analyst, can see instantly that some sources are good and others maybe not so much. Interesting actions can be taken about budget spend or why is something better than other things etc.

Of course you can do this with anything you want. Keywords, pages, referrers, campaigns, whatever is important to you, and whatever tool you are using, here I am using IndexTools and its custom report feature. . . .

Nice!

One quick tip: As much as possible try to pick the spouse / mistress / friend metric to be a Outcome metric - something that helps measure success of you site.

Try it, you’ll see what I mean, insights will practically scream out at you!

# 4: Industry Benchmarks.

These are astonishingly good at helping you get context to your performance.

Your conversion rate is 2% or your time onsite is 42 minutes or your share of search is 7% for a search engine (or a keyword) or . . . . How do you know if that is great, and you should rest, or really terrible and you need a Marshall Plan to fix things?

Use external context.

We have talked about the value of using the FireClick Index so many times in the past . . . .

Put your metrics against these, or others on that site, and see get delightful amounts of context.

Now Google Analytics also has a feature where you can also get benchmarking data, and in this case quite deep into your very own industry segment so you can see increased relevance of these benchmarks. . . .

Sweet ain’t it? This site above had much higher traffic than other Apparel sites, much much higher, but they also have a much higher bounce rate and much lower time on site. Without the context of the benchmarks they could be celebrating, with the benchmarks they can start to make intelligent decisions.

[To learn more about GA benchmarking and the new data sharing settings policy please see this blog post by Brett Crosby:
http://analytics.blogspot.com/2008/03/benchmarking-now-available-plus.html]

# 5: Tap into the tribal knowledge.

If there is a “killer app” for getting context to your web analytics data it is tribal knowledge. Information about initiatives, marketing programs, website updates, changes, management re-org’s :), server outages, ppc, direct marketing and on and on and on: Things that have a impact on your website.

Web Analytics, and in turn Analysts, sit in a silo. This means that very often they have no idea about all the things that people are doing the site or to their acquisition strategies. So they look at all these numbers and metrics and trends and then like Tarot Card readers guess what the numbers mean!! A futile exercise.

There are lots of moving parts to a website and a lot of people involved in the holy exercise of creating something of value for your customers. It is a complex dance with many moving parts. . . .

The best way to get context is to seek out all the players and / or staying plugged into the various different processes to tease out vital context for your numbers.

“Ahhhh so you send out a big email blast five days ago!”

“You were running a multivariate test? Why did you not tell me in advance?”

“The shopping cart was down for nine hours! That explains so much, thank you. Kiss“

“We’ve adopted a new media mix model?”

“None of our last 6,000 campaigns were tagged! Pulling hair out!!!“

So on and so forth.

Step outside your cubicle, office, talk to people, take marketers out for dinner (if you do more than dinner please first refer to your company’s HR policy!), create information loops that are closed (and include you!), etc etc.

Often all it takes to put a trend in context is to know everything different parts of your company are doing. Go get plugged in!

That’s it, five simple easy to action recommendation.

Actually I have more that I could write about but I have six speeches in five days in NYC this week so I can’t do as much justice to this post as I would like to. But one last quick tip, another great way to get context is to understand Primary Purpose, it is absolutely awesome. As to how to get Primary Purpose: Use the 4Q survey.

Thanks, hope this was just as much fun for you as it was for me. Please share your own ideas of how to get context, what works for you and what does not, please share your own battle scars using the form below.

Good luck!

PS:
Couple other related posts you might find interesting:

• The Awesome Power of Data Visualization
• Five Rules for High Impact Web Analytics Dashboards
• Convert Data Skeptics: Document, Educate & Pick Your Poison
• Excellent Analytics Tip#4: Make Your Analysis/Reports “Connectable”