What happens if I was given the login and the password to a company's website analytics data and asked to "identify something interesting?" Just how would  I begin the process of web data analysis? Even without any knowledge of the organization's goals or help from clients that simply want data pukes? Can I add any business value?

A real challenge!

It turns out, astonishingly, that even with all those obstacles (no goals or objectives or teamwork or business guidance), you can spend a couple of hours and do decent enough analysis, sourced from your experience, to supply some minor data-gasms of insights.

Establishing The Right Expectations

It is almost difficult to discover earth-shattering insights that you can acton from your web analytics data in simply few hours. And yet discovering some fascinating starting points could be less tough than you may imagine.

Starting points to start valuable analysis from. (What data should I look at first?) Beginning points for a consumer centric strategy. (What are my consumers telling me?) Starting points for gaps in your online marketing efforts. (Where am I wasting money?).

Secret To Winning Web Analytics: 10 Beginning Factors For A Fabulous Start!

This article is a starter guide that outlines the steps we undertake most generally when handed the keys to the data for a website.

I want to share where in your web analytics data you can find valuable starting points, even without any context about the website/ enterprise/ priorities. Reports to look at, KPIs to analyze, inferences to make. Right here's what we are going to cover:

Step 1: See the website. Note objectives, consumer experience, flaws.

Step 2: Exactly how great is the acquisition strategy? Website Traffic Sources Report.

Action 3: How highly do Visitors orbit the website? Visitor Loyalty & Recency.

Action 4: What can I identify that is damaged and swiftly fixable? Top Landing Pages.

Action 5: What content makes us most cash? $Index Value Metric.

Step 6: Just how Sophisticated Is Their Search Strategy? Keyword Tag Clouds.

Action 7: Are they earning money or making noise? Goals & Goal values.

Step 8: Can the Advertising Budget be optimized? Campaign Conversions/Outcomes.

Step 9: Are we helping the already convinced customers? Funnel Visualization.

Step 10: What are the unknown unknowns I am blind to? Analytics intelligence.

Ready to shake the world of Marketing and Analytics? Let's go!

Step 1: Check out the website. Keep in mind objectives, consumer experience, flaws.

My biggest beef with web consultants and analysts is just how quick they are to delve into Google Analytics or Omniture or WebTrends. It's as if they have never seen reports with Visits & Conversions before. My God!

The very first thing we do, as well as I recommend you do, is visit the website whose data you are analyzing. See just how it looks. Go to the product pages. Go to the B2B videos. Go to the add  to cart page. Go to the RSS/ Email sign up page and sign up. Go check out some consumers reviews (if is an e-commerce website) or visitor comments (if a blog). Go download the white papers. Go use site search.

Get a feel for the business's ambience. Get a feel for the details architecture and cross-sells and also font size and buttons and tab framework and user experience etc. What's hideous? What's remarkable?

Bonus points for checking out one competitor's site. Do all of the above.

Pull out a note pad and list out your thoughts. What did you like? What did you hate? What frustrated you? What was apparently broken? What's the site trying to do?

At the very least your note pad should have answers to these 2 questions: What is the macro-conversion? What are two or 3 micro-conversions? Remember, those terms apply to both ecommerce as well as non-ecommerce sites.

The website owner/ client did not help you, but you've got very valuable context. You're ready for data!

Step 2: Just how good is the acquisition strategy? Traffic Sources Report.

This is the very starting point I wind up due to the fact that the very first point I wish to know is exactly how smart the firm is when it has to do with internet marketing. All other site data comes 2nd since if you are not great at online marketing then there is no much of a victory to be had by torturing website data.

No firm in the Milky Way has succeeded without having a balanced portfolio of acquisition channels (fancy word for a source of web traffic). How's yours?

I am truly looking for a well-balanced portfolio of web traffic sources. Search, Referring Websites, Straight, Campaigns. Which one is strong? Which one is missing?

Around 40% to 50% Look is normal. If the number is too big it indicates an overexposure to browse positions as well as algorithm changes (not good whatsoever). If it is too small you are simply leaving money on the table. And of the search traffic, you want a big section to be Organic so you are not simply "renting" traffic or not good at Search Engine Optimization.

20% approximately Direct Traffic. If the web analytics tool is implemented right these are all your existing consumers or people from offline campaigns. You want a healthy and balanced amount of both. If direct traffic is low, I worry if you are any good at customer care/ retention (the latter is so often just an afterthought).

20% to 30% Referring Sites. You can't simply rely on search engine or investing money on campaigns.

A healthy and balanced web strategy consists of a robust amount of site traffic from other sites that link to your product or services, and praise (or slam!) you, or promote you on Facebook and twitter as well as forums and or otherwise link to you. Free website traffic (usually) and you do want that (for numerous reasons).

10% Campaigns. Google Analytics (sub optimally) calls this Other. It is e-mail campaigns, display/ banner ad campaigns, Facebook display campaigns, social media campaigns and so on.

You want at the very least 10% of the website traffic to be the ones you invite to your site delibrately, after solid analysis and great targeting. Outside of Paid Search. It's a sign of a healthy business that has a diversified customer acquisition strategy.

What to do next:

I'll make note of where the company is over leveraged and make a note to dig much deeper with the customer. Expose the risks to them, brainstorm how to diversify.

For each and every bucket I'll check out at least the top 10 rows. Additionally, for at least one of the 4 buckets I'll dig deeper by checking out the basic report for that segment to determine some strengths or weak points. Surprising keywords, missing sources of traffic, trends in campaign vs. straight visits etc.

At the end of this, you'll understand exactly how sophisticated the client is, where you'll attack acquisition first (if you get the time and money to do more analysis).

Step 3: How strongly do Visitors orbit the website? Site Visitor Loyalty & Recency.

I have a sense for the website and I have a sense for the client's acquisition savvy. Time to focus on the Visitors !!

Most individuals develop sites simply for themselves and without obvious purpose in mind. Furthermore, the content publishing schedules, perceptions of "engagement" are all out of flaws.

So what I (and you, dear blog reader) want to do is get a sense for how strongly attached are the Visitors to the site. This is certainly crucial for any kind of content site, however, you'll be suprised at how important it is even for an ecommerce website (retention, assistance, repeat purchases).

The report I'll take a look at is the standard Visitor loyalty report. It would show how many times in a given period the same individual (persistent cookie actually) checks out the website. Or, how tightly the Visitor orbits the website!

While I love Loyalty the most, I likewise take a fast peek at Site visitor Recency. This is specific to content websites.

Site visitor Recency determines the gap in between 2 visits of the exact same visitor. Or, When was the last time you saw the same individual (cookie really). 

Segmenting this data is best (by content, source, campaign, outcomes, etc), however, a casual review will help you understand how people behave.

What to do next:

I constantly review two more reports that provide me with a sense for content consumed. Not the silly reports that show mostly pointless metrics like Average Time on Website as well as Average Pages Per Visitors.

I am talking about Length of Visit and also Depth of Visit

With Loyalty and Recency we measured visitors visiting, but once they are here what are they doing? That's what you are trying to get a sense of with these two reports. [Remember visits with just one page view, bounces,will be in the first bucket 0-10]

If you have some time segment out the bigger buckets (beyond 0-10) and analyze the data. If you don't have time just knowing Loyalty, Recency, Length, Depth tells you a whole lot about how tightly Visitors orbit this website, and understanding customers is precious.

Step 4: What can I find that is damaged and quickly fixable? Top Landing Pages.

Understand website? Check! Understand traffic sources? Check! Visitors? Check!

Time to take off the gloves and get dirty.

Companies spend lots of money acquiring website traffic, often badly, so why not find top places where that cash is being wasted and which web page might potentially be stinky? Do visitors refuse to give you a single click? That may be a useful signal.

In your web analytics tool, this is a standard report. It shows bounce rates, sweetly indexed against website average, for the top entry points to the site:

What to look for:

The red parts! See why I like "indexed against site average" feature? It is very easy to know what smells bad.

3 landing web pages (entry points to your site) are performing really well. Seven seem to be bouncing at a much higher rate than normal, some amazingly so. At this point, you don't understand why.

When you see that a page has a high bounce rate it could mean one of two things:

1. Wrong people are coming to your website (highlighting problems with campaignss, SEO, etc) or

2. The web page itself is poorly created (missing calls to action etc) or otherwise broken.

At this point, you do not know which of the two (or both) is the problem. Given that you do not have a great deal of time pick two of the biggest losers above. Click on the arrow thingy next to their name in the report and visit them. Sometimes the problem is apparent. Next click on the link itself in the above report and visit the page level report. There in the drop-down pick Entrance Sources and Entrance Keywords. That segmented view will quickly tell you which sources and/ or keywords are contributing huge bounces.

Now, at least for 2 or 3 pages of the site, you are analyzing you know that they stink and you have decent ideas of what the cause( s) could be. Give yourself a pat on the back. Great job!

[An exception: Analyzing bounce rates for a blog, or "bloggish" site? Segment and look at landing pages for New Visitors; for all other websites the method is as above.]

What to do next:

In this case, you are in a position to recommend specif fixes. You have actually looked at the web pages and sources of traffic (a proxy for customer intent). You can make use of a heuristic valuation process to tell the website owner what solutions will help in reducing bounce rates.

A clean and handy list is below: Qualitative Analytics: Heuristic Evaluations Rock!

I am telling you people are going to love you for being this awesome.

Action # 5: What content makes us most money? Index Value Metric.

Most effort on any given internet site is invested in content development, and for this reason for action five I urge you to stick to page reports, but flip the channel from an "input metric," bounce rate, to an "output metric," $Index value.

For an e-commerce (with revenue) or a non-e-commerce website (where goal values have actually been defined), $ Index value essentially computes "how much revenue" has been gained by a page ( more like contributed by a page). It is a fantastic method to assess the value of a page.

Go to any content report, in this case Content By Title and you'll see the last column 

Would your boss / client not die and go to heaven if you told them exactly what types of content they should be writing / pimping more and what less? How about pages of which product / services generate most value?  

Or my favorite report to look at: Content by Drilldown.

That report is particularly suitable for websites that are organized in clean directory structures (like/ products,/ videos,/ demos,/ blog,/ whatever else). Now you are able to recognize which groups of web content is most valuable to the company. Are videos really valuable? How about really hefty painful Silverlight demos? Wishlist work? The answer awaits!

If you don't have clean directory site structure you can still make use of segmentation to group content and do the above.

What to do next:.

This takes very little time. Use the Analytics Weighted Sort feature.

Focus not just on what's causing good stuff today, focus on hidden areas where good stuff might happen in future.  

website analytics

Step 6: How Sophisticated Is Their Search Strategy? Keyword Tag Clouds.

Pages, and valuable bits of content, done. Time to refocus on value acquisition.


It is really hard to get a "big impact" understanding of search strategy sophistication just from tables of top ten rows in Google Analytics or Omniture or CoreMetrics. Mostly because I don't want to look at the same lame obvious things.

So I like to yank the data out and create a tag cloud of all 40, 50, 100 thousand rows of data. Export as CSV. All Rows. Paste into www.wordle.net  Magic

What to look for:

Tag clouds are great at understanding the big strategic picture and understanding the sophistication, or lack there of, for any brand.

Tag clouds have limits. You don't know what the problem is. Is it people? Is it a lack of sophistication? Is it using too much cruise control? Is it bad SEO? Is it. . . you'll have to dig. But you have 1. A great understanding of the site's search data and 2. Something of incredible value to present to your boss / client.

What to do next:  

I am a big fan of internal site search analysis. Few other sources contain as much direct customer intent as this. Visitors to your site are directly telling you what they are looking for. The challenge, as always, is gathering up all that intent into something understandable.

How about downloading all that and creating a quickie tag cloud?

I can look over my pages viewed and time spent and Google'd keywords and all that. Or I could analyze the story above and at a glance understand what people are seeking.

Then, based on time available, we could analyze where people start searching, how many of them bounce off the internal search results page, what is the conversion rate/goal values for at least the top x of the above searches, etc etc.

I could even mine data above to see what other topics I could write more about (or in your case. . . what new products you could sell / stock / invent!).

Step 7: Are they generating income o Goals & Objective Values.r making noise?

With a small detour into search (always one of the biggest components of most people's acquisition strategies) we will return to my first love: End results! Ok, ok, ok it's consumers, however, End Results are close.

I can tell the sophistication of any organisation by what I see in this report, Goal Conversions & Goal Values:

What to seek:

The first thing to check is if you see anything here.

If you do not see anything here, and the business has been around for a long time, then you know you are going to struggle, in case this is a consulting job, to make any decent money off them or, in case this is your first day in your job, you are most likely to not going to get a lot of love in this business as an Analyst. I am not saying quit, I am just saying dig in 'cos it is going to be a soul-searing struggle if this report is empty.

On the other hand if macro and micro conversions are present then get down on your knees and say a silent prayer because this is going to be fun.  

Check if the actual goals & conversions are what you had noted in Action 1. If they are not then what are the visitors to the website doing of business value? Anything you noted in Action 1 that is not below (new goals to create?). What do the trends over the last 12 to 16 weeks suggest? What Goals are contributing the most amount of value?

At the end of this little exercise you must have the ability to with confidence talk to your client/ boss about how the website is fulfilling company purposes, and perhaps where it is falling short. If you did Steps 2 through 6 well then you might also have other actionable recommendations to make.

What to do next:

If there were some objectives you had determined, or your client/boss was anticipating, then take a moment to configure those in the web analytics tool.

If they do not have any kind of behavioural goals created (99% of the people don't), then create those, takes just a moment. Refer to your insights from Step 3 to set the threshold values.

If this was an e-commerce website I would typically create one segment as a little bonus for the customer. Orders where the total value was 50% higher than the average order value. Basically the "whales"– people who order way more than normal. My hope is to get particularly important insights regarding where these people come from (geographies, campaigns, keyword, etc), what they do on the website (web content consumed etc), and what they buy (shopping cart/ basket analysis etc).

You want a lot more of these people. It is great to understand them really well.

Step 8: Can the Marketing Budget be optimized? Campaign Conversions/Outcomes.

Remember the only 3 end results that are very important in web analytics? More Revenue. Decreased Price. Increased Customer Satisfaction.

In this step I concentrate on the 2nd item, reducing cost. Maybe it is surprising as this is our very first foray into the web analytics data, we have received minimal love from the client/boss, and we don't have all the company business-specific knowledge that could be essential. Yet we can help reduce the cost of marketing/ customer acquisition.

My favourite report? Goals/ Conversions by Campaign:

What to look for:

Campaigns as in Paid Search and Display and Email and also Social Media and anything really of value you'd discovered in Step 2.

Start by looking at the horribly called "Other" report in Google Analytics (or perhaps the appropriately named Campaigns report in your web analytics tool). Initially allow yourself to be guided by that column at the end Per visit Goal Value. It is a measure of efficiency.

Then work backwards and see what conversion numbers look like. After that work further back and see which individual goals may be creating that high value to be created.

At the end of this exercise, you need to have some preliminary recommendations for at the very least one or two places cash is possibly being wasted, or at the very least inefficiently spent. Killing opportunities (example: better email campaign, less lousy Facebook pages!). You should additionally have some sense for where improvement opportunities may exist.

What to do next:

Pick a couple of significant campaign strategies the company is implementing and dive deep into e-commerce analysis (if the customer is e-commerce). 

Much too often in the web analytics world, our fixation is with analyzing behaviour (visits and time on the website, and so on) or with concentrating on just how to get more visits (invest more money!). If you want significant attention (and love) from your client/ manager then you'll concentrate initially on cost reduction. 

Action # 9: Are we helping the already convinced customers? Funnel Visualization.

Ending on cost reduction was a good point. In this action we are likely to do one awesomely pleasant thing: concentrate on perhaps the fastest way to increase outcomes for the business!

The poor funnel report is so underappreciated. While unstructured path analysis is the greatest wild-goose chase you might engage in, structured analysis is literally manna from heaven.

You want people to go through a series of steps (one after another) to reach a goal (for them and you).

The funnel report will show where in your 3 or four stepped process people leave.

What to try to find:

The red bars. The bigger red bars.

I wish I could write lots and lots about this, but that is all there is to it (if the funnel was correctly created).  

Look for where the highest exits exit in the funnel. Go check out the page with your eyes, identify improvements (heuristic is okay), send them to your customer/ employer for fixes. The entirely ineffective ones you can just kill, the reasonably ineffective to "don't know if this could be an issue" things go into an A/B testing bucket.

In any case, below is the example. Somebody strolled into your supermarket. They filled their cart loaded with stuff. They line up at a cashier and get their wallet out. They notice the loooong line. They move the cart aside and leave. You do not want them to leave! It was so difficult to get them to come and add to cart and line up! Fix anything that stands in the way of the open wallet and you.

What to do next:

Oftentimes the above funnel processes occur over multiple visits (sessions). In that instance, your typical Google Analytics (or Adobe Site Catalyst or WebTrends or NetInsight) funnel won't work. Well, it will "work" but show imprecise data.

Switch to something like PadiTrack. It measures pan-session funnel conversion performance. The same Site visitor can get in and exit and ultimately convert across sessions and you'll be able to see that behaviour.

Another compelling aspect of PadiTrack is that you can view, segmented funnels! Search and Display and Email Visitors convert by means of different behaviour, as well as finally you'll have the ability to see this.

PadiTrack is free, works using the totally free Google Analytics API, and works on historical data! Most web analytics tools, including paid tools, can not do that!

Step # 10: What are the unidentified unknowns I am callous? Analytics Knowledge.

With no assistance from my boss or marketer I have gone through 9 steps of web data analysis and found a few concrete as well as significant bits of actionable insights.

But the risk of doing this without tribal expertise, or intelligent party at the other end, is that I might miss something I simply don't know due to the fact that I do not know it.

The unknown unknowns!

So before I close any analysis for a website I go take a look at the Google Analytics Intelligence reports. There I can rely on the fact that the unique intelligent algorithm in Google Analytics has done forecasting and applied control limit and statistical significance and much more mathematics to help identify abnormalities in the data. I see its soothing embrace:

What to look for:

Initially, I set the Alert Sensitivity to Low (multiple standard deviations away from the mean) and see what automatic alerts turn up. These are big events, so most important. After that, I move the slider gradually towards the right, see what other alerts pop up.

I am searching for events and activity, on the site or caused by others externally, that I (and normally even the client/ boss) would not be aware of. The unknown unknowns.

Your discoveries here are great methods for you to check your own work in the above steps (perhaps some of what you believed did not make good sense does make sense now). They are also a fantastic means to impress your client/ boss that you somehow, let's just say magically, discovered things that even they, the most data-driven of data-driven companies, could be unaware of in their own data.

What to do next:

The hard part with Intelligence (custom or automatic alerts) is to isolate the root cause. Look at the newly released Google Analytics Intelligence Major Contributors section. That has the clues about root source. Take advantage of the sophisticated segmentation feature to isolate the activity causing source/behaviour/ outcome and also dig deeper.

[For more checkout the videos on Google Analytics Intelligence.]

And you are done! Does that not feel awesome? And more importantly, achievable?

Summary:  WEBSITE ANALYTICS: Step-By-Step Guide To Website Analytics

In case you needed a handy checklist, here's what we've learned today:

Step #1: Visit the website. Note objectives, customer experience, suckiness.

Step #2: How good is the acquisition strategy? Traffic Sources Report.

Step #3: How strongly do Visitors orbit the website? Visitor Loyalty & Recency.

Step #4: What can I find that is broken and quickly fixable? Top Landing Pages.

Step #5: What content makes us most money? $Index Value Metric.

Step #6: How Sophisticated Is Their Search Strategy? Keyword Tag Clouds.

Step #7: Are they making money or making noise? Goals & Goal Values.

Step #8: Can the Marketing Budget be optimized? Campaign Conversions/Outcomes.

Step #9: Are we helping the already convinced buyers? Funnel Visualization.

Step 10: What are the unknown unknowns I am blind to? Analytics Intelligence.

The first time you go through the steps laid out in this guide it might take you more than 120 mins. However, I guarantee you that with time and experience you'll get better.

I want just reading this article (it probably took you 120 minutes just to read it!) would be enough. It is not. You'll need to go practice it on many many clients. The more you do it the better you'll get as your sense of direction, data, discovery and deduction get better and better and better.

It is optimal to start any web analysis with a clearly defined web analytics measurement model. However, if you do not have one then you no longer have an excuse not to provide something small that is incredible and of value from any web analytics tool you have access to, for any website in the world. And that I am rooting for you!

Ok, your turn now.

When you are thrown into a website's data blind what are the first few things you do? What reports and metrics do you attack first? Over time have you discovered any strategies that work across multiple clients? Do you agree with the order of the steps above? Would you do something differently?

Please share your thoughts / critique / best practices / tips via comments.