Since this change is a reality, we analysts need to deal with it and one of the first steps we can take is to calculate what percent of our Google search traffic is encrypted and thus not providing any keyword data.  This new metric can be called “Lost Keyword Data” and is something that should be tracked over time and included with your keyword reports.

To calculate this “Lost Keyword Data” in YWA we will create two custom segments that we will compare against each other.  One will show traffic generated by Google that doesn’t provide keywords and the other will show the total traffic sent by Google.

Start by creating a custom segment and adding two dimensions: 1. “Search Engines equals “Google” 2. “Search Phrases is empty.”

Then save this custom segment so that you can quickly apply it to reports across YWA:

Using the same technique we’ll create and save a segment for all Google searches:

Now I can use the “Compare Segments” functionality of YWA along with the two custom segments I created to directly compare the impact that encrypted searches has had:

Here is how these segments compare on a basic Visits report for the previous 12 week period:

Next we’ll export this table to Excel to calculate the percentages:

I have now quantified exactly how much impact this change by Google has had on my site.  In this instance I can see that the percentage of encrypted Google searches (Lost Keyword Data) has gone from a 1/2 percent to 6 percent from October to November!  This is certainly a trend I’ll be keeping an eye one and falls in line with what has been seen by other analysts on the sites they monitor.

It happens way too often and it’s painful to watch.  Extra revenue being flushed down the toilet because online marketers aren’t taking a close enough look at what their web analytics reports are telling them.  They’ve spent the time to properly implement their tracking solutions but they aren’t spending enough time in their solution looking for insights.

For online marketers, there could be a whole slew of reasons as to why they’re not paying closer attention to their web analytics data:

• Perhaps a new rep was hired and he/she didn’t realize they had the data available
• Perhaps they have a 3rd party agency managing their data for them
• Perhaps they don’t know how to analyze the data and need a consultant
• Perhaps they’re just lazy and don’t care

While there’s always reasons why one hasn’t looked closely enough, the bottom line is that you have to pay close attention to what your data is telling you so that you can capitalize on it!  Web analytics data isn’t just a bunch of numbers on a page (though it may look like it to some).  Web analytics data provides you with insights such as: who your target audience is, where your roadblocks are, whether or not you’re turning a profit, and who you should be spending your online budget with.

With that said, I want to introduce you to a good example of an online marketer who hasn’t been paying close enough attention to their search engine referral report data.  And because of this, they’re missing out BIG TIME on driving additional revenue to their bottom line.

The data provided below for this particular marketer (in the UK) was generated during the past several months…


By looking at the data from this report, we can see that:

• Google is driving 91% of the referral traffic (combo of paid and organic search)
• Google drives a higher Avg. Order Value for each sale
• Yahoo drives a much higher Conversion Rate
• Google drives a lot more Revenue
• Yahoo drives a much higher ROAS (Return On Ad Spend)
• The marketer spends (Cost) a lot more with Google versus the other three engines

Now let’s analyze the data for insights.  Do you see the glaring question that comes from this report above (minus AOL since their search is enhanced by Google)???

Yes!  Why isn’t this marketer spending more with Yahoo to drive more referral traffic when more than half of their visitors convert, the ROAS is more than double Google’s, and the Avg Order Value is nearly the same as Google’s?

Now don’t get me wrong, I’m not saying the marketer should pull budget from away Google and use it for Yahoo (because Google’s ROAS is also very good) but they should definitely be spending a lot more with Yahoo with the kind of performance data it’s showing!  Sure spending more on Yahoo is going to drive up their costs/spend but at a 6,800% return-on-ad-spend, this marketer is missing out on a big revenue opportunity!!

Also, look how much more the marketer is spending with Bing (Cost), yet look at the return they get compared to Yahoo.  Does that make sense?  No.  However, that will soon change and become even more important as the Yahoo/Microsoft alliance moves into the UK in the near future.  Using the same data above, here’s a breakdown and summary of what a Bing/Yahoo alliance currently looks like for this marketer compared to Google….

Google: 91%
Yahoo/Bing: 3%

Search Engine Spend/Cost
Google: €164,409 ($235,606)
Yahoo/Bing: €28,037 ($40,198)

Google: €1,759 ($2,521)
Yahoo/Bing: €1,662 ($2,382)

Google: .43%
Yahoo/Bing:  .52%

Google: €5,468,506 ($7,840,167)
Yahoo/Bing: €458,009 ($656,607)

ROAS (Gain)
Google: 3,326%
Yahoo/Bing: 3,914%

Summary:

While the Yahoo/Bing alliance has not yet taken place in the UK, the client should prepare themselves to take advantage of it when it does.  Even though Google refers a lot more traffic and generates more Revenue than both Yahoo and Bing combined (partly due to their 5X higher spend in Google), a combined Yahoo/Bing drives almost the same Average Order Value, drives a higher Conversion Rate, and provides a better Return On Ad Spend.  Those three metrics alone should alert the client that they should be spending more in AdCenter to drive higher revenue when the Yahoo/Bing alliance comes along.

There are world class analytics tools, available for free, from Yahoo! and Google that will get you more data than God ever intended you to have. Yet, perhaps shockingly, a vast majority of decisions website owners make are based on faith and not data.

Breaks my heart.

After wiping off my tears, and meeting with many leaders of businesses large and small, I have come to the realization that the problem is not that we don’t have enough data, or even enough of the right type of data. All that exists.

The problem is we are obsessed with data and not about the business.

And that has to change. Now. Especially if you want to take advantage of this the most glorious channel on the face of the planet, the Internet.

Here’s the secret to creating truly data driven organizations. Forget about the data!

At least at the beginning, and focus on the business and answering existential questions about your business.

There are five things you need to identify to start your journey right. In this post I’ll explain what these magical five things are, and share a concrete example with you. It is too easy to use a ecommerce website example so I’ll set myself a hard task and use as my example the website of the National Council of La Raza (NCLR). It is a non-profit website. If I can apply the framework to them, you can apply it in a jiffy to any other type of website!

Let’s rock and roll. . .  here are the first five steps. . .

#1: Identify Business Objectives.

Answer this stunningly simply question: Why does our website exist?

A variation could be: What are the three most important priorities for our websites?

Without a clearly defined list of business objectives you are doomed. Write down the answer to the above question, ensure the objectives are DUMB (Doable. Understandable. Manageable. Beneficial.).

The responsibility of identifying business objectives belongs to the most senior leader in the organization responsible for the website (the person whose neck is on the line).

There could be many objectives for the NCLR but one primary business objective is to, for example, increase attendance at immigration rallies.

#2: Specify Goals.

Here’s my definition: Goals are specific strategies you’ll leverage to accomplish your business objectives.

Since business objectives are usually strategic (“sell more stuff on the site” or “create happy customers”), goals help us drill down to something specific. Do x. Improve y. Reduce z.

The responsibility of identifying goals also rests primarily with senior leadership (in your company or at your client). Remember the people with their neck on the line? Yes, them.

In our hypothetical example, NCLR, the business objective was to increase attendance at immigration rallies and the goal would be to increase sign-up on the website.

#3: Distinguish Key Performance Indicators (KPI).

Your web analytics tool, like Yahoo! Web Analytics, has a boat load of metrics in it (hurray!).

A KPI is a metric that helps you understand how you are doing against your business goals (and objectives).

Visits and Visitors are Metrics (as an example). Conversion Rate for a ecommerce site is a KPI. Makes sense?

Be very very careful in identifying KPI’s because they are unique to every business (even between competitors) and a great way to fail quickly at this step is to do a shoddy job with steps #1 and #2 above.

The responsibility of identifying KPI’s primarily rests with the Analyst (if you have one), or the Marketer, with major amounts of input from senior leaders.

For NCLR, given our goals, there are two objectives: 1. Number of Visitors signing up for Action Alerts and 2. Number of new individual memberships. [If you don’t understand why these two then I have succeeded, they are unique to them. But if you visit their site you’ll see why I choose them.]

#4: Sweat and Set Targets!

Targets are numerical values you have pre-determined as indicators of success or failure.

You are going to love me for torturing you to come up with targets. I promise.

This is a very hard step to complete, and yet it is super important. The challenge with having access to unlimited data in under 60 mins is that most of the time the person looking at all that data (and puking it all out!) has no idea what good or bad looks like.

It is your job to solve that problem. For your KPI’s what does success look like? What number equals failure? You identify that and when the report comes out the yardstick used to judge data, and freak out about it, has already been established.

The responsibility of identifying targets is shared by the Analyst/Marketer and the Finance team (and if no Finance team then the Boss). The Analyst provides historical data and the Finance team the forecasts or just financial obligations for the current quarter / year. Together both come up with targets for your web KPI’s.

For NCLR, as an example, we could identify: 1. KPI: Action Alert. Target: 14,000 signups per month. 2. KPI: Individual Memberships. Target: 4,800 per month.

#5: Decide the Valuable Segments.

A segment contains a group of people identified by their source (where they came from), behavior (what they did on your website) or outcome (what goals were met).

A segment identifies people or their behavior that is important to your business. Either because you are spending money (paid search advertising, email etc) or it causes you to have higher revenues (all people who convert) etc. It helps focus where analysis of the data starts, what’s important to investigate first to ensure data is in service to your business rather than the other way around.

If you want to learn more about this key step check out this blog post: Web Analytics Segmentation: Do or Die, There Is No Try!

The responsibility of identifying the segments rests primarily with the Analyst, with business guidance (mostly prioritization) by the senior leader.

For NCLR we have two groups of segments to focus on. 1. Acquisition: Since search is a great way to acquire new visitors Organic Search is one segment. Since, for example, they are doing lots of email campaigns the visitors who get those emails are the second segment. 2. Behavior: Given our Goals & KPI’s we have two segment to analyze and find insights from. People who sign up for action alerts and those who start new individual memberships.

Boom! With a wink and a nod you are ready, finally, to crack open your web analytics tool and do something of business value with it.

Ok I’ll concede the above five steps are not easy. They’ll take a lot of back and forth inside the company and they’ll require asking some tough questions related to the site’s existence and business purpose. But when you are done with the five steps there will be no more data puking in your company, or decisions based on faith. There will be real analysis of the data, which will drive impactful business decisions that will increase your bottom-line and create happy customers.

Good luck, and happy analytics!

Avinash.

Essential Online Video Metrics

If you host videos using your own flash player (or stream through Windows Media Player) then many different user activities can be recorded for analytics purposes, such as pressing the pause button or sliding the video position slider bar forwards or backwards.

Some of the key video metrics (or KPIs) are:

• Online video started
• Online video core content started
• Online video positive consumption action
• Online negative consumption action
• Online video paused
• Online video ended
• Online video played, percentage of total
• Online video played, total seconds
• Online video play position slider user action
• Online video section played at 1st, 2nd through to last tenth section
• Online video time section played: 1st, 2nd 10 and last 10 seconds, etc…

These can be measured using a combination of media player events, methods, timer events and tracking code written in JavaScript or Adobe ActionScript.

Video Segmentation

For the purpose of making measurements we can choose to conceptually split the video into a fixed number of sections, say 10 segments of 10% length. These segments can be used to measure which sections of a video have particular high end user engagement activity.

We can also define another way of splitting the video into slots, where in this second method, we can choose a fixed lot length in time of say, 10 seconds “time sections” or “time slots”. These can be used to measure engagement in terms of fixed time slots of 10 seconds length. This type of measurement can also show the total playing time of groups or individual videos.

We can further group the videos into categories such as chapters, channels (yahoo, msn, etc..), types (sports, sci-fi, etc..) or any other categorization the publisher may wish to use for analytics purposes.

Video Engagement Characteristics

A video engagement characteristic is a representation of the audience’s interactions with the video. Content providers can use this characteristic to rapidly see which of their videos are most compelling to their audience. It can also be used to analyze the strengths and weaknesses of a particular video.

For the engagement characteristics we will define two types of audience video consumption:

Positive Consumption Actions

Negative Consumption Actions

Positive consumption actions are ones that associated with a positive user experience. One positive consumption action could be the act of rewinding the video to re-watch a specific section. This indicates that the user saw something that they want to see again. Therefore each time an end user rewinds the video a positive consumption action is recorded for the section that is rewinded to.

We can also decide that certain activities constitute a negative consumption action. One such example can be the act of fast-forwarding the video (or moving the slider bar) to a position further forward in a video. This can indicate that the audience is bored with the current section they are fast-forwarding from, and so for this case of fast forward, we use the section of video moved from, and not the video section moved to, as the grouping for negative consumption action.

The positive consumption action reported by the analytics system then be used indicate which sections of a video are particularly compelling. Conversely the negative consumption action sections can be removed, reworked or edited to make them more positive.

Videos and Links

Another type of video analytics could be the correlation between video sections and clicks to links for product information.

It could be deemed useful to measure at which stages in a video your audience was compelled to actively seek extra textual information sales or specification information about a product. This may also be considered as positive consumption as it shows active interest in the product, and such data can be gathered about audience behavior.

Conclusion

We’ve just scratched the surface of the types of data content providers can mine from their online videos and why it can be useful. In our next post we will show the nuts and bolts of how to implement online video analytics using Yahoo! Web Analytics.