10 Fundamental Web Analytics Truths

7/23/2019 10 Fundamental Web Analytics Truths

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kaushik.net http://www.kaushik.net/avinash/ten-fundamental-web-analytics-truth

10 Fundamental Web Analytics Truths: Embrace 'Em & Win Big

Avinash Kaushik

There are more mistruths and F U Dabout Web analytics out t here than I think is

reasonable.

Part of it f ueled by Vendors . What a competitive bunch!

Part o f it f ueled by some Consultants. I suppose the rational is: self

preservation bef ore all else.

Part o f it is f ueled by a vocal minority genuinely upset that 10 years o n we are still not a statistically powere

bunch doing complicated analysisthat is shifting paradigms. They generally feel it is beneath them to use a

standard too l, they push a utopian world that is hard f or anyone t o accomplish, including themselves, even

after spending a minor fortune.

This is sad. Even a little f rustrat ing.

My problem with these mist ruths and FUD is that they result in a ton of practit ioners and companies making

prof oundly sub opt imal choices, which in turn results in not just much longer slogs but also spectacular

career implosions and the entire web analytics industry suf f ering.

Let's try to change that . If you agree to help I am conf ident we can accomplish a lot .

Web Analytics, this beautiful child, was born just t he other day in the midst of tumultuous times, quite

literally, when everything changes every day. This constant evolution means that every time it learns how to

do something the world changes around her and then it is on to learning the new things t o stay relevant.

It has simply not had a break to catch a breath and mature.

And I doubt it is going to happen soon. The web is changing too f ast. Too many new things are happening

too f ast and those of uscharged with measuring it have to change the wheels while the bicycle is moving a

30 miles per hour (and this bicycle will become a car bef ore we know it all while it keeps moving, ever

faster).

Yet. Yet. Yet, yet , yet, yet. there is so much we can do.

Now.

This instant.

We can make use of what we have. Javascript tag driven click data processed in the cloud provided through

a web based f ront end that allows you to segment and create meaningful views o f the data unique to you.

Even with the to ols we have, in the state we have them, we can be smart. In

f act smarter than you would be through any other channel on the planet!

Don't f all fo r the FUD. See through the mistruths. Don't go down rabbit ho les.

The opportunity is too big for you to be distracted.

In this blog post let me share with you some ground truths f rom my own
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humble experience. It's a bit o f black and white in a world that admitted has lots

of gray.

My hope is that it inspires you. That it helps you f ocus your precious t ime and

resources. That it results in you making fewer mistakes.

Finally, that it helps you go kick some bottay!

Here are ten web analytics ground truths.

1. If you have more than one clickstream tool, you are going to fail.

Strong words!

It is perf ectly ok to date as many people as you want. It is o k to put them in tough situations (just introduce

her/him to your parents!). It is ok to go all the way and see if t hings click.

Once you make up your mind and get married, practice monogamy. Bigamy is vast ly overrated.

Here are some reasons:

~ It is really really hard to make sure you have implemented one tool correctly. Not just javascript tags

but the ecommerce customizations, the custom variables / sprops / evars, the unique campaign tags

required by each to ol (f or search and aff iliate and email marketing etc), the internal site search

conf iguration, the insane javascript tag updates just t o make the darn segmentation work (except in

some like Google and Yahoo Analytics), the I could keep going.

You'll be hard pressed to do one right, doing two is like asking f or King Kong to s lap you. Repeatedly

~ It is really hard to get a o rganization to use one set o f numbers (and remember they are not going

to be clean or complete, no matter what you do). Why do you think introducing a completely diff erent

set o f numbers is going to make your lif e easier?

Having two to ols guarantees you are going to be data collection, data processing and datareconciliation organization. Why? Because every tool uses its own sweet metrics def initions , cookie

rules, session start and end rules and so much more.

You'll have no time f or data analysis, certainly not f or data actioning.

~ It is a bit silly to believe you can use one tool f or purpose x (say search analysis) and another f or

purpose y (say everything else).

When it comes to proving which campaigns are better and which numbers to report to the manageme

what will you do ? How will you make sure you are in every meeting where people bitch and f ight abou

getting credit?

There is nothing magical about they way clickstream data gets collected by any tool. They are all 95% the

same.

Date around, f ind the one you love, marry it, s tick with it.

If not hing else convinces you, remember that clickstream data is a small part o f the data you'll use to make

smart Web Analytics 2.0 decisions. For big success you'll need to have a Multiplicitystrategy:
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So when you s tep back and realize at the minimum you'll also have to use one Voice of Customer tool (f or

qualitative analysis), one Experimentat ion to ol and (if you want to be great) one Competitive Intelligence

tool. do you still want to have two clickstream tools?

Likely not.

2. Omniture cannot save you. Only you can save yourself.

There is a absurd belief that if you buy a paid web analytics tool that you'll bathe in milk and honey and

magically insights will be delivered.

Paid web analytics tool come with clickstream analysis t oo ls that are hobbled on two counts:

1. They come with legacy problems in their code and architecture that make it nearly impossible for yo

to do anything fas t, or even do s imple things like on t he f ly advanced segmentation you constantly

need to change the code and know everything you want to analyze up f ront .

2. They will never be as powerful as Yahoo! Web Analytics or Google Analytics because otherwise Pa

Vendors could not upsell you to, in case of Omniture toDiscover2 and Insight. In case of WebTrends

replace those terms with Marketing Intelligence / Visitor Data Martetc. In case o f Coremetrics.. well

you know.

This means when you buy a paid web analytics too l you'll be hobbled until you buy the versions o f theproduct that actually do t he job you want (and more).

Now if you decide that you don't want hobbled clickstream tools but would rather buy the complete suite on

day one this is what you buy:

A 18 month implementat ion schedule and a 12 month process of redo ing things (lif e changed in 18 months)

and no money for Analysts (you sent have $3 mil to your analytics vendor by now) and you the lone ranger

have in two and half years barely managed to deliver improvements to reduce bounce rates f or top email

campaigns.

Was that what you set out to buy?
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Know what you are buying. Not insights, as alluring as they sound. You are buying implementation with apossible future promise of some actionable data three years down the road.

Ready to use Google or Yahoo! Analytics to day to make 85% of the decisions you need to make after 3

weeks o f implementation?

If you are just starting your analytics journey does it not sound reasonable?

Let's f lip the coin.

You already have the paid analytics sof tware combos mentioned above.

It is just as absurd to believe that Goo gle Analytics is bet ter than your Omniture Site Catalyst + Genesis +Discover with a dash o f Insight. I have to bang my head on the wall when I hear that someone just replaced

Omniture Site Catalyst + Discover with Google Analytics.

Why?

You just spent two years implementing t hem! And you paid three million dollars!!

There is nothing you get with Google Analytics that you did not already have. In f act with Discover you

probably have 12 things Google Analytics can't do (that's whey you are paying an additional million dollars

plus on top of what you are paying for Site Catalyst!).

Google Analytics can't save you if you already have the set up above or CoreMetrics Analytics + Explore orUnica's NetInsight OnDemand + Custo mer Insight + PredictivInsight!

If you are still failing then the problem is not the tools.

The problem is you. Your organization. Your skills. Your budget allocation priorit ies. Your silos. Your HiPPO.

Switching to Google Analytics, in the set up above, is no t go ing to help you.

Fix what's actually broken, it's your WebTrends combo of Analytics9 + Visitor Data Mart or your CoreMetric

combo of Analytics + Explore + Benchmark + whateverelseweboughtbecuaseitsoundedgoodinthesalespitch
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Org. Skills. Structure. Process. Courage.

The only reason to switch to Goo gle Analyticswhen you have the above is that you can't f ix what's broken

(org structure, skills, hippo). You might as well save the $3 million you are sending to your web analytics

vendor.

3. It is faster to f ail and learn then wait for an "industry case study" or find relevancy in a "industr

leader white paper".

I met a small group of to p companies in Londo n recently. Post my keynote the f eedback I got was: "Yourpresentation was powerful, you made a compelling case f or how we can do the things you have outlined to

take advantage of the opportunity. Do you have some relevant case s tudies you could share with us?"

I let out a quiet scream.

In this day and age I completely fail to grasp the need f or "case studies" and "white papers".

In my of f line life I looked f or case studies because it was very expensive to try so mething new, you wanted

someone to have f ailed already. I wanted a white paper so I could convince my HiPPO (Highest Paid Person

Opinion) that some magnif icent Thought Leader pontif icated so mething so we should do it.

Most case studies were at best f rom tangential businesses. 100% of the t ime the companies did not have

the priorities that our business was currently executing, neither were they driving to wards t he same

outcome.

Yet case studies in some sense reduced risk, even if they were simply over blown marketing f luff written by

the vendor.

I don't need case st udies now, not on t he web.

Why?

If someone tell's me that vanity url's are a great way to start measuring multi channel impactthen I can just

try it for 500 times less effort than it would take me to find a case study.
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If I go to a conference and hear that doing test and control experiments is a great way to measure

cannibalization by paid search links on well ranked organic keywords, then I can just run a small test myself

and see if it works for me.

If you blog that a sho rt on-exit survey or a feedback button is a great way to collect voice of customer, I

don't have to be lazy or hyper paranoid and wait f or a convincing case study. Both o f those are available f o

f ree, I'll just implement and be my own case study.

Email campaign ideas, content improvement, behavior target ing, test ing product prices, hiring a supposedly

awesome consultant, us ing of f line calls to action, measuring impact of television o n the web, opening atwitter account of a B2B business, doing.

Anything you can think of I can do it. Usually f or f ree. Usually with a modest ef f ort . Usually at least a test .

I can f ail or succeed all by myself in my unique circumstances delivering for my unique business goals in my

own organization.

Why do I need a case study?

Neither do you.

There is such litt le risk to actually trying. You don't need no s tinking f alse comf ort that something workedf or so meone else.

Fail f aster.

[I realize f or some HiPPO's o ld habits die hard, they won't even let you run a report without seeing a case

study. Update your resume and start looking f or another job - because the o rg you are with will never be as

success f ul as it sho uld be. Meanwhile see if you can convince your HiPPO to run a small test while you look

f or a case study (and a job).]

4. You are never smart e nough not to have a Practitioner Consultant on your side (constantly help

you kick it up a notch).

The f ield of web analytics (especially 2.0) changes f ar too much in far too short a time.

That's because the web changes too fast (and vendors that don't update their software to take advantage

of these opportunities every quarter will die).

Yet companies, f alsely, believe that they can keep pace and do it all with no external help.

That almost never works. Because

1. You are f ar too busy actually reporting and analyzing to keep pace with all the wonderful evolution

2. It is cheaper to get someone to answer your quest ion at $60 or $80 or $100 or $150 an hour thanspend a week "trying to f igure it out".

Hire a Practitioner Consultant (someone who just does no t speak at conferences but actually rolls up her

sleeves and does the dirty work) on some kind of a retainer, or buy a bank of hours you can cash out say

during the next s ix months (or whatever) and get so lutions delivered to you. You f ocus o n taking action.

I recommend this blog post: Web Analysis: In-house or Out-sourced or Something Else?
http://www.kaushik.net/avinash/2006/11/web-analysis-inhouse-or-outsourced-or-something-else.htmlhttp://www.slideshare.net/vinoaj/gamc2010-09-price-testing-holy-grail-of-marketing-rachit-dayal-happy-marketer


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In it I describe four s tages into which each company f its (in terms o f its current analytics evolution) and wha

you should expect f rom a consultant in each stage.

This will help you f igure out exactly what you might need and hold your consultant accountable.

Here are three additional t ips about hiring consultants , f rom my humble experience:

1. Compute how long the person has been consulting, call this X. Compute how long the person hadactually worked as a practit ioner in a real company (hopef ully in your indust ry), call this Y.

If X > Y, it is possible the consultant might be disconnected f rom the reality o f what it really takes to

get businesses to use data (and not it is not just too l expertise). [This means I have 3.5 yrs left to be

a hands on practitioner consultant!]

If X >> Y (substantially greater :), avoid.

2. If you can try t o hire an independent external consultant.

It is no t t hat the consultants at Omniture or CoreMetrics or WebTrends are sub-st andard, they are

Abso lutely Not . But they do f ace dual pressures of selling yo u more consulting and up-sell products.you have a independent consultant they only try to sell you more consulting! :)

That is the reason I am partial to hiring authorized consultants f or Google Analytics ( GAAC's) and

Yahoo! Analytics (YWAAC's) or f or Omniture / CoreMetrics / WebTrends go ing with so meone such as

Stratigent or Zaaz.

Oh and don't forget rule #1 above.

3. Do a Google search fo r the Consultant. Read what people say about them. Read what they say

about t hemselves and others. Read how they cont ribute to the blogosphere, to f orums. Form an

opinion, then hire.

If possible hire a nice person. Life is to o short to work with jerks, no matter how skilled or

knowledgeable they are.

Good consultants will help you stay current, so lve problems f aster, deliver so lutions and not just

reports , allow you to f ocus on analyzing data and f inding insights.

5. Your job is to create happy customers and a healthier bot tom-line.

If you think your job is to analyze the "numbers" your career will be limited.

People (you? :) whose job it is to do "the data t hing" spend day af ter day af ter day in analytics to ols
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producing numbers (if they have time lef t over f rom tagging, begging IT, changing tags , turning down

vendor up-sells, begging vendor f or more svars and eprops and asi slots).

Numbers with data and tables and graphs and pivots and font sizes and automated pdf 's and. a

lifetime spent pro ducing numbers.

Here's a major reason why all that ef f ort , the numbers deluge, changes nothing fo r a company:

You / me / they never ever bother to actually go t o the website.

Never bother to search f or t heir company and look at the paid and organic results (to f ind

broken things).

Never bother to sign up f or their own email campaigns (t o see how much they stink).

Never bother to buy something on their site see live the tort ure.

Never bother to try and return the product/service purchased via the site (and see how much

that s tinks).

Never bother to visit competitor sites and f ind nice or terrible things (to take advantage of ).

Never bother to do a o nline usability study (it just cost s $20 a pop!!).

Never bother to.

Look, if you are not going to go out there and feel the heat how do you expect to get the insights yo

need about where to f ocus and what to do?

Your web analytics tools only provide you with numbers. Then its up to you. And you can only begin to

f ocus, prioritize, f ind stories and f ixes and opportunities if you actually immerse yourself in

understanding what you are supposed to analyze.

Walk in the custo mer's shoes so you'll understand how much your s ite st inks (t hen f ind the numbers

that help prove that, or not ). Email people who have placed orders, asked them f or t heir f rustrations.

Answer tech support emails f or a day.

Every single day ask yourself this question: What amongst the data I have provided today will create

happier customers tomorrow?


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If you don't have a direct line of site f rom your work to happy customers, you are doomed.

Ditto, perhaps even more so, if you are not incessant ly fo cused, every single day, to providing data

stories (or "inf o snacks") that help improve your company's bot tom-line. Every day. Wait. I said that

already. : )

If you, the "Web Analyst " don't believe that you hold in your hands the power to change your

company's existence then you are either at the wrong company or, more likely, in the wrong job.

6. If you don't kill 25% of your met rics each year, you are doing something wrong.

In ancient times we would hire Accenture or some such august consulting group to come in, spend six

months systematically going through the business and recommend Measurable Success Factors

(shorthand: metrics) and those then would be carved into s tones, handed to the Goo d Lord's

messenger and the rest o f us would f or ever f ollow the commandments unquestionably no matter

what happened.

While I am exaggerating a bit f or ef f ect, most web businesses, if they identif y key metrics, and then

never go back and revisit and revalidate.

It should not come as a surprise that af ter just a f ew months you f ind that no o ne looks at yourdashboards, no one can seem to f ind insights f rom the data and the company has reverted to "f aith

based initiatives" rather than "data driven initiatives".

The web changes too f ast f or us to believe that we can be stat ionary with 1. our measurement

st rategies 2. what to f ocus o n priorities 3. success measures.

We need to change our measurement strategies as changes occur in:

1.Marketing strategies (from forums to display to search to social to mobile to)

2.Business priorities (no we are not doing ecommerce, we want leads!)

3.Structure, purpose, audience (oh my!)

4.Available measurement technologies (ohh. sent iment analysis!)

5.Skill set available (wow we finally got someone who know what r squared is?)

6.HiPPO's bonus measurement metric (you will never succeed unless you are trying to get the

person on top promoted or a higher bonus, keep very closely info rmed as to how they get paid

f ind insights that so lve fo r that, you will have eternal love and a data driven org)

All of the above happens all the t ime to every website. So why should your repo rts, dashboard,
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measurement priorities and "Measurable Success Factors" stay stagnant?

By f orcing yourself to have a target f or killing metrics you are ensuring that you'll f ocus o n an

important activity once a quarter. You'll re-visit your assumptions and what's important to the

business . You' ll be f orced to talk to HiPPO's, Marketers and pretty much anyone who currently

consumes the output f rom you/your team.

And that, as Martha would say it, is a good thing.

[Allow me to point out that only 50% of the metrics I love exist in clickstream too ls - like webtrends oxiti or unica. The other 50%, the ones that help drive key changes to the business exist in other

places. Metrics like: Multi channel value index. Impression Share. Task Completion Rate. Keep that in

mind when you choose metrics to ensure you are not over-leveraged in metrics that don't matter.]

[Bonus Reading: Five Rules f or High Impact Web Analytics Dashboards .]

7. A majority of web analytics data warehousing e ff orts fail. Miserably.

There are few investments as overrated as building a catch all massive data warehouse to give you

the "global cross f unctional multi channel single view of the customer experience and lifetime value o

demand through a business intelligence report powered by an econometric model that takes into

account page view probabilities using the Clopper-Pearson binomal confidence interval".

Yet that is exactly how internal data warehousing projects are championed or external cloud based

data warehousing so lutions are so ld by vendors.

As of 2010 I st ill have a lot more years that I spend in the tradit ional data warehousing / business

intelligence world than in web analytics. I have personally executed data warehous ing projects f or web

data (in the broadest sense), and they have most ly been miserable f ailures. [Warning: There is a

distinct possibility perhaps I am the problem here!]

Here are some problems you face with web data (when it comes to warehousing):

1. There is too much granular data! Yes yes I have purchased the Netezza appliance, yes other

promise "massively parallel processing data warehousing appliances". The problem is not the
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hardware or the hardware company, the problem is t he amount and type of data (most o f it is

actually worthless, even if you can get much of it into the warehouse). Things o f course get

worse when you think of warehousing in traditional software only solutions.

2. The data is rarely deep (say about a person), is most ly anonymous (about a person) and f ul

of holes (cookies, scripts o f f , plugins). This goes counter to the st rengths of what data

warehousing is able to pull off so well with offline data (years and years of data too).

3. Warehouses expect logical structures and relationships, you'll be astonished at how little o f

this exists in your web analtyics data (see reaso n above).

4. It is worse than extracting all your teeth with a toothpick to try and get your of f line data

merged with your online data (even if , and it is a BIG IF, you can get the requis ite primary keys).

5. BI tools st ink at answering questions web analytics t oo ls answer with ease (how many peop

clicked on a link on our home page, how many sessions f rom keyword "avinash" came f rom

Google and abandoned products in their cart,.). This means trying to replace a WA tool with a

Warehouse only results in an organization slowing down f urther.

6. Campaigns, tags, links, meta data (if any that might exist), data relationships, metrics, websit

url structures etc cause there to be a constant demand to make changes t o the underlying

st ructure of your data warehouse every single day. Yet no dw team is organized to execute on

daily schedule, you'll be lucky to get monthly. All of the af orementioned is not a problem fo r you

web analtyics to ols.

I could keep going on. Please please please make sure you don't make a decision to invest millions of

dollars (that's what it will take by the way f or a f ortune 5000 company) based on the promise of data

warehousing, look at the reality and apply that f ilter. It will be humbling.

Oh and before you tell me that you want to build a data warehouse to store histo ry let me point you t

this blog post: History Is Overrated. (Atleast For Us, Atleast For Now.)Please give it a quick read and

make sure the traps out lined there don't exist in your case.

History, and histo rical comparisons, beyond the last 13 months are vast ly overrated, and almost nev

worth the cost t hat data hangs around your neck.

There is always one exception to the rule. :) It can be of some value to take aggregated data about

your visitors (especially those that converted) and put it into your corporate data warehouse where a

other data o f your company sits. This allows you to do st rategic analysis of you web acquisitions in

context of retail, call center, etc.

Not page level analysis type (that's tactical!) rather the cross channel purchases and returns etc (t he

real strategic kind).

Think really really hard bef ore you buy the hype of web analytics data warehousing. They tend to beexpensive multi year commitments that rarely deliver even nominal value not matter how much vendor

and consultants hype them.

It is possible that you'll be the exception and build the f irst clickst ream data warehouse where you'll

deliver positive ROI (against the Total Cost of Ownership). But even if 110% of the signs point to t ha

f irst make sure you have aggregated all the marginal gains.

It would be silly to not pick up the high ROI low cost stuf f f irst right?

8. There is no magic bullet for multi-channel analytics.
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The reason you have had a hard time f inding a multi channel (online plus of f line) analytics solution

is.. it does not exist !

And here's the thing, it won't f or quite some time. The problem is the missing primary keys, and we

won't so lve it in the near future.

Yet there are Vendors that blatantly say they provide a "comprehensive integrated multi channel

solution" and imply that they can track every interaction across any channel and help you compute

"true ROI".

It is a bunch of @#%^*

The best thing such solutions do is they sell you a campaign management so lution f or your o f f line

marketing activities with some possibility of running those campaigns (think email) online as well. In th

most opt imist ic scenario what you'll get is response rate f rom a mailer (postal) and a email campaign

because the email campaigns were auto tagged.

That's it.

They won't help you understand impact of search on store sales, they won't help you understand

impact of tv on your website (not without massive pain even after you buy the "comprehensive

integrated multichannel so lution"), they won't help you. well a lot of things.

Be wary. Be very very way of these people/so lutions.

Now make no mistake measuring multi-channel impact (non- line marketing baby!) is critically

important. You *should* do it.

But it is a long hard slog. It requires people, it demands begging many people in your company and

agency to cooperate with you, it mandates building custo m solutions, it needs lots of creative thinkin

There is also a big payof f in the end, just no easy answers.

You'll need a portf olio s trategy (f rom my book Web Analytics: An Hour A Day , Page 235):
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Here are two blog posts that comprehensively outline why multi channel analytics is important, what

the problems are and a port f olio o f 11 solutions you can deploy:

Multichannel Analytics: Tracking Of f line Conversions. 7 Tips & Best Practices

Multichannel Analytics: Tracking Online Impact Of Of f line Campaigns

Updated versions of the st rategies out lined in above posts are in Web Analytics 2.0 (starting Page

368, in case you have the book).

9. Experiment, or die.

Let me beat this dead horse one more time. Sorry.

If you don't have a robust experimentation program in your company you are going to die.

It is just a matter of time.

[I know, I know, it seems like we have been through this so many times, and I also know that secretly

you know how critical this is, sadly others stand in your way.]

In today's world there are so many quest ions t hat we can't answer with any degree of certainty (even
http://www.kaushik.net/avinash/2008/12/multichannel-analytics-tracking-online-impact-offline-campaigns.htmlhttp://www.kaushik.net/avinash/2008/07/tracking-offline-conversions-hope-seven-best-practices-bonus-tips.html


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with petabytes of data!). Here are some such questions

1. How much cannibalizat ion happens between paid and organic search f or my brand keywords

2. What is the online impact of my promotional f lyers sent in postal mail?

3. What is the opt imal price I should chargef or my product to maximize prof its?

4. Should I go f or o verwhelming, pungent, or just plain pukey for my home page design?

5. Should I show an Add To Cart link to o ur own ecommerce store or also to other places on t h

web people can buy the exact same product (o f ten cheaper, so people buy a lot more o f what

they might not have bought at all)?

6. What is t he impact of having a live twitter f eed of all mentions o n each product page of our

website?

7. Will people f rom Ireland buy that?

Your imagination is the limitat ion in terms of hypotheses and "I wonder" ideas that you come up wit

every day.

Yet Site Catalyst and Unica and Google Analytics and Indextoos stink at answering all of the above

questions.

But if only you could answer any one o r two of the above, it would dramatically alter how you do

business o nline.

Oh and when I say Experimentat ion I don't mean tes ting but ton sizes (BOO!). I mean doing big

important things t hat matter (every one in the list above, and more).

Start with something simple, try three dif f erent layouts o f your home page, the product line page and

the highest traf f icked landing page. You are on your way to A/B testing. Progress points? 20.

Next move to changing two things at one t ime on your product description pages. That 's multi-variate

test ing. Progress points 25.
http://www.slideshare.net/vinoaj/gamc2010-09-price-testing-holy-grail-of-marketing-rachit-dayal-happy-marketer


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Now you are ready f or the kind of test ing that is life changing: running contro lled experiments! [Web

Analytics 2.0: Pages 205 - 208.]

That's most of the tests above. They will help answer the almost unanswerable questions f rom

cannibalizat ion to multi channel impact to brand impact and more. Aim f or this.

Hire at least o ne or two people dedicated to experimentation (not just a/b testing, or Google Website

Optimizer / Test & Target) in your team if you are a Large company, and part of a person if you are

medium sized.

If you want to truly being data driven, if you want to crush your competition, if you want to really win

on t he web, then all roads lead through robust experimentation.

10. The single most e ffective st rategy to win over "stubborn single-minded" HiPPO's is to

embarrass them.

Finally perhaps the bane of our existence, the magnif icent HiPPO (the Highest Paid Person's Opinion

Our beloved HiPPO's bring their entrenched mindsets and loud voices (in terms of power) and

performance review writing authority to bless our projects, or more likely stand in the way of progres

Of ten HiPPO's don't impede progress / change or crush valid opinions / suggestions because o f

malice. Sometimes they don't know this interweb thing as well as they should, sometimes they know

things have worked a certain way forever and they are reluctant to try new things, and other times

they are convinced that they are right (even when they are magnif icently wrong).

Net net things are rarely as cute as this

Here is what does not work when it

comes to convincing HiPPO's:

1. Your opinion. Really, no one

cares what you or I think (notthat high in the organization).

2. Repeating yourself time and

again.

3. Data puking (though we tend

to thing as data persuasion).

Here is what does work with heavenly

precision: embarrassment.

Their embarrassment.

You just have to be nuanced (to ensure you don't make the above three mistakes).

You two BFF's in the HiPPO's nuanced embarrassment:

1. Data about your competitors (and your performance against t hat data set )

2. The voice of your customers (and your awesomeness o r suckiness that shines through that

I only know a handf ul of HiPPO's that can resist having competito rs crush t hem (especially results of

their opinions t hat were actioned!). I know only a couple of HiPPO's who once made aware of will
http://www.kaushik.net/avinash/2008/11/experiment-die-reasons-awesome-testing-ideas.html


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ignore the pain of customers.

Here are six specific st rategies you can use to move even the heaviest o f HiPPO's:

# 1: Implement a Experimentat ion & Test ing Program.

# 2: Capture Voice o f Customer. Surveys, Remote Usability, Etc.

# 3: Deploy the Benchmarks I Say, Deploy 'em Now!

# 4: Competit ive Intelligence is Your New Best Friend.

# 5: Hijack a Friendly Website (/ Earn Your Right to be Heard).

# 6: If All Else Fails. . . . .

Please check out this blog post f or additional details and examples f or each recommendation: Lack

Management Support o r Buy-in? Embarrass Them!

Next t ime you see me don't complain about how your hands are tied and your boss is a pain or how

you f eel like the loneliest person in the world and no one understands you. Your dest iny is in your

hands, use the strategies above, go af ter your HiPPO (respectf ully), and make change happen!

EOM. Phew!

If I could summarize the philosophy I have formed fro m a lifetime of bruised it would be this

The only way to succeed in Web Analytics is to : Be agile. Be f lexible. Move fast .

Decisions you make today based on data you have right now will have greater impact on your

business, than decisions you can make in the f uture based on so lutions you will implement over the

next eighteen months with data that will be so perfect it is as if God is speaking to you.

Ok now it's your turn.

What do youthink of the ten fundamental truths? Agree with 'em? Vehemently disagree? Got a #11

you would add? Perhaps no t just #11 but #11 through 16? :) Please share your thoughts / f eedback /

criticism / love via comments .

It would be fabulous to hear from you.

[A Small Contest:]

My online learning startup Market Mot iveis holding a small contest to award scholarship for a Master

Certification course ($3,500) in Web Analytics. The course starts on April 15th. Our goal is to give

someone deserving an opportunity to become a Ninja.

If you think you could gain value fro m a three month st ructured course (with exams and quizzes !) the

please contact me. Here are the rules please e m a i lme the following

1. A short (really short) paragraph on why you want the scholarship.

2. Pick a site you love and tell me three things you would change about it, and why.

That's it.
http://www.marketmotive.com/internet-marketing-training-and-certification-master-signup?topic=WebAnalytics&typ=none&utm_source=blogs&utm_medium=occamsrazor&utm_campaign=startuppromohttp://www.kaushik.net/avinash/2008/02/lack-management-support-or-buy-in-embarrass-them.html


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Please f it the whole thing in one page (6 sized f ont automatically disqualif ied! :)).

Contest close date: March 31st .

Thanks.

[/A Small Contest:]

Documents

10 Fundamental Web Analytics Truths