I'm Trying Out Hittail - Part 2

I wrote a couple of weeks ago that I had installed Hittail on this blog, in order to get a better sense of what subjects my readers are interested in. I wanted to see which topics the Hittail engine would recommend that I focus on.

Well, after a week, I took the next step and installed it on several higher traffic blogs.

So far, the results are encouraging....and somewhat addictive for the compulsive web-analyst. (Did I mention I'm thinking of starting a support group for marketers who feel compelled to while away their nights studying emerging user trends?)

At the office, we've taken a couple of (I think) exciting steps to align our editorial and marketing efforts, and the Hittail application is playing a role in that process. It is helping us to determine which stories to feature, allowing us to craft more targeted headlines (both to improve SEO and the user experience), and increasing our awareness of which keyword phrases we should be monitoring position and optimizing for.

A Word on the Hittail Suggestions Tool

Hittail provides suggestions as to which keywords your website should focus on optimizing for. As a self-professed metrics junkie, I've wasted a few thoughtcycles pondering the algorithm that identifies words.

Hittail is about the longtail strategy, so the recommendations are not based on keyword volume. Some of the words it has selected are pretty obscure, so it doesn't seem to be any kind of keyword clustering. From what I can hypothesize, it seems to select words for which your site appears fairly low in the rankings, but for which you still managed to attract a visitor (implying that those who ranked above you provided unsatisfactory results for the motivated searcher). Presumably, I guess, if you could improve you rankings on these phrases, you would attract much more of this type of motivated/previously unsatisfied traffic to your site.

I have no real idea if this is how it works. I'll be posting to the forums at hittail.com to see if I can ferret out an answer. Meanwhile, I can recommend the tool, and report that it is proving useful for me on numerous levels. You can download it



Anyone else out there using hittail? How are you implementing its recommendations?

Predictive Versus Descriptive Modeling with Analytics

I wanted to post about approaches to using web analytics data that recognize its limitations, and its power.

Many organizations use historical analytics data as a basis for forecasting future growth, and establishing performance goals and budgets. This applicaton for analytics data can blur the distinction between predictive and descriptive data. Understanding this difference is critical to an effective analytics program. It generally falls to the analytics professional to ensure that the difference is clearly understood within the organization.

I'm going to start out with a couple of definitions. What do I mean when I say predictive versus descriptive modeling?

Predicitive modeling refers to a mathematical model that can accurately predict future outcomes. For instance, I know that if I apply sufficient heat to water, the water will reaach 100 degrees celsius and begin to boil (barring slight variations for altitude which are also predictable). The rate at which this happens and the amount of energy required can be mathematically described.


Descritive modeling refers to a mathematical model that describes historical events, and the presumed or real relationship between between elements that created them. For instance, yesterday when I went to the store to buy milk, it cost me $1.00 a litre, last month it was 95 cents, last year it was 80 cents.. Based on historical events, I assume it will cost me roughly $1.05 to buy a litre of milk next month.

Web analytics falls in to the latter category. It is a set of descriptive, historical statistics.

Past Versus Future Performance

I direct marketing activities for a division of a financial publisher. The company has an outstanding track record for identifying and recommending market-beating stocks. Historically, they've made recommendations that represented a lot of money for a lot of investors worldwide.

But at the end of each financial report that we send out....and those of virtually any financial advisory service or market report is a warning to readers something like:

Past performance may not be indicative of future performance.


***Web Analytics reports should carry the same user warnings***


Have any of you ever sat in a management meeting in which company representatives have said something like, "We have the data to demonstrate the relationship between ad spending and revenues, so if we want to grow sales by 20%, we just need to ratchet up our ad spending accordingly."?

This kind of thinking fails to recognize the rate of change in markets, technologies and the competitive landscape, and fails to factor in the concepts of resource scarcity and the law of diminishing returns, as well as the potential from economies of scale. That's without even considering the inherent flaws in any data gathering and processing system.

So, if the operation of complex markets can not be accurately predicted by simplified analytics models, what are the more tangible uses of historical analytics data?

1. To identify broken systems. A significant change in performance data can often indicate a technical problem, overloaded systems, broken links, faulty logic etc.

2. To select between alternatives. Analytics is particularly apt for testing market responses to different offers, creative, or sales processes with A/B or multivariate testing. It can also provide a guide as to which channels or markets tend to be most lucrative or most cost effective among existing channels. (The challenge, then, is often to find ways to expand the more lucrative channel).

3. To flag new market opportunities. A careful study of web analytics data can reveal new opportunities for cost savings, revenue generation or operational improvements.

4. To extablish a meaningful dialogue with existing and potential customers. Web analytics data can help us to learn about customer needs, desires and propensities. It can teach us the language that the customer uses to articulate their needs, so that we can respond meaninfully. It also can give us parameters to personalize the user experience to better meet their needs and create loyalty, trust, and ultimately customer satisfaction

One final VERY POPULAR use for historical analytics data

And hey,...IF your company persists in falling in to the infinite resources analytics model trap. IF they continue to hold fast to the belief that past performance predicts future performance, you can always use your historical analytics data as a roadmap to all of the external factors that caused your company to veer off its charted course.

My Other Blog is Spam?

A few days ago, as I found myself writing here, and trailing off in to other subjects, I decided to set up another blog on a favourite subject of mine: offer strategy.

I went and set up the url http://offerstrategy.blogspot.com, and over the next few days, wrote a total of three articles on the subject of creating sales premiums that make sense. Designing offers that help to close sales.

The blog has a total of three external links:
1 to this blog.
1 between two articles
1 to an article on my company's website about the mortgage crash in the US (which is topical to the article, since I think it can be argued that the crash is the result of flawed offer strategy)

This morning I receive mail from blogger informing me that my blog has been flagged as a potential "spam blog"

I went and read about the defininitions of a spam blog, and it cited pirated content and volumes of nonsensical links as the general offenders. I am a little stunned to discover that my three little articles, and three little links could somehow have set off alarm bells someplace. I am curious to know how it could possibly fit the criteria, and if so, do the criteria make sense?

Anyways, I have put the blog up for review by the humans at Google. At least someone will be reading it now, as I hadn't gotten around to publishing it in any way...I was going to wait until there was a little more content.

Has anyone else had their blog unjustifiably locked as potential spam? Please share your story with me. Meanwhile, I'll climb back down off my soapbox now. Sorry for having strayed from the subject matter. To get back to analytics...I am currently working on an article for the WAA Blog about User Generated Content. Hope to share that next week.

I'm Trying out Hittail

A couple of days ago I installed the the Hittail real-time search hits application on this blog. You can register and get the code for your own site at http://www.hittail.com. I am running the freebie version of the application, for now.

I learned about Hittail on the Web Analytics Association site blog. If you are not a member, and you are interested in Web Analytics, I suggest you join the Association.

• the community is very helpful and supportive
• they organize educational events
• the forums are very active, and provide a good mix of practical information along with insights on where the industry is heading

Anyways, I installed Hittail here on this blog, and then, when everything seemed to go well, I also installed it via the wordpress plugin on http://www.moneyweekes.com. So far...no data on that site. Now, I am not panicking yet, because it took a couple of days for the stats to register for this blog. But when they appeared, all the historical data was there.

As a surprise bonus, in addition to reporting keyword traffic, the system informed me that my blog had been stumbled (I had been meaning to submit this blog to stumbleupon, but I'm delighted that someone else found the site and gave me the thumbs up), and received linkedin visits and traffic from the WAA today.

While all of those are great to know, I'm not sure how they will play in to the software's stated objective to help me identify which longtail keywords I should be optimizing for.

Ambar Shrivastava from Hittail described the primary benefit as follows:

"The idea is to provide actionable data that helps webmasters and bloggers better connect with their existing readers as well as attract new readers interested in similar topics to what you already have on your website. This differs from other analytics tools that mainly describe what is happening on your site with little information on how to improve it."

I ran into a couple of snags along the process of installing (what can I say, I'm tired...it's easy, but I was firing on half cylinders). And I can tell you that the team over at Hitbox fairly jumped at the chance to help me out. They get double thumbs up for customer service.

I have shared the application around the office, so I'll have more to report back shortly, I expect. We are all anticipating good things. I work for a publisher, so our sites are very original-content rich, which seems like a good fit for Hittail. However, the moneyweekes.com site is i Spanish. Not sure how the application will handle other languages.

One of our programmers looked unimpressed and muttered "um, you know you can get that data from your log files, right?"... Yeah, I know. But Hittail does digest the information for me and highlight key points...and theoretically it provides optimization suggestions based on my words. I say theoretically, because my search volumes don't merit any suggestions as yet. . And most exciting of all....it does it in almost realtime. So I can start getting a sense of when people are visiting the sites...what is the best time of day to publish my newsletter? How often should I be posting here? I read on their website that I should have about 100 pages minimum.

So if you found me through a searchengine (or maybe even if you didn't) chances are tomorrow I'll be thinking about your keyword search, and how I might better address the issues you seem to be searching for online.

Anyone else out there installed the Hittail code on their site? How is it working for you?