Tag Archives: software

Agenda At Once PIM just became freeware

Agenda At Once Free PIMWe have decided that our Agenda At Once PIM software, previously priced at $39.95, will be completely free from now on. No cut down features, no Premium offers, no special upgrades – simply free.

Agenda At Once PIM is a full-featured Personal Information Manager with powerful and complete hierarchical To-do list, Schedule/Calendar, Contacts and simple Notes management. Some of main features include:

  • Grouping tasks in a tree-style manner
  • A bunch of task fields and configurable columns (like assignees, projects, categories, color, …)
  • Manually and auto-calculated percentage based completion
  • Flexible and saveable filters
  • Easy planning by drag and drop between to-do and schedule
  • Multiple simultaneous users sharing same data
  • Portable installation
  • And much more

In addition, the latest update solves the problem with saving settings on 64-bit Vista+ computers and also adds a support for Windows 8.


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Web Log Storming 2.6 and discount opportunity

As mentioned before, in 2009 we switched to subscription based upgrade policy. By buying a license or subscription extension you get free updates for one year. After that, you can continue using the last version you own (forever or for time being) or extend subscription right away. Because we wanted you to get used to this idea, we prolonged an implementation for a while, but now it’s time: version 2.6 won’t work if you bought your license before Sep 27, 2010.

If you update to v2.6 accidentally and you don’t wish to extend subscription, please bear in mind that this wasn’t our intention at all and that we took all reasonable measures to avoid such misunderstandings (blog, newsletter and a warnings throughout the application). In that case, you can download latest “last free for all v2.x customers” version from here.

Most important tangible change is introduction of Bounce rate metrics; now you can see how much visitors leave after visiting just one page. This metrics is included in the Overview report, but also on pages, referrer and search keywords reports. This way you can easily see how well specific page or referrer is performing.

Another important change is eliminating problems with Windows 7 64-bit. The problem didn’t happen on all systems and it was related to a third-party software protection system that we were using in combination with some anti-virus/firewall software. Well, it shouldn’t happen anymore, and if it does, by all means, please let us know. If your old registration data isn’t automatically updated, please try to enter your key again.

We also updated Operating System and Browser lists and fixed some cosmetic and minor bugs.

Facebook page and a discount

Several days ago we finally created a Facebook fan page. It still doesn’t contain much information and we are now awaiting more “Likes”. So, if you already like Web Log Storming, why wouldn’t you make it official? 🙂 In return, you will get a 20% discount for any of future purchases related to Web Log Storming (which includes new licenses and subscription extensions). This offer probably won’t be here forever, but once you get your coupon you will be able to use it anytime, so make sure you don’t miss it.

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How to track AdWords campaign without using cookies

People often think that it’s not possible to track successfulness of marketing campaigns without using cookies and/or JavaScript, which isn’t true. I will explain how it can be done with our Web Log Storming, but maybe the similar results could be accomplished with some other web log analyzer. Also, even though the example shows AdWords, you can track any other advertising results in a same way.

Setting up an AdWords campaign

The goal is to somehow differentiate visitors that came from different AdWords campaigns, groups and/or ads. It’s quite easy, actually, as only thing you need to do is to append some query text to Destination URL like this:

If you append “?anything” to URLs (including question mark, without quotes), this information will be included in server log files, while visitors will see the same content as if query is not there. For different campaigns and ad variations append slightly different query, for example:

  • https://www.mywebsite.com/?adw=test1
  • https://www.mywebsite.com/?adw=test2

Use it in Web Log Storming

After traffic starts coming in, Web Log Storming will be able to analyze this information and include it in reports. Easiest way to this is to enter “adw=*” into Parameters | File | Query field (note there is no question mark here). You can also use Lock button to keep this filter active as you switch reports.

Custom variables in Web Log Storming

While this parameter (filter) is active, any report that you select will be based on AdWords visitors only, making it easy for you to see how they perform.

Another tool that you might want to use is View | Based on IP only main menu option. If you select it, sessions from the same IP will be grouped as one, allowing you to examine it as a returning visitor.

Going further – using Goals

If you use Professional edition, you can also define Goals important for your business. Please read this article to learn how to do that.

With two Goals defined, this is what you’ll get if you choose Queries report:

Query Count Goal1 % Goal2 %
adw=test2 68 45 66.18% 8 11.76%
adw=test1 27 3 11.11% 27 100%

As you can see, for each defined AdWords destination URL (campaign, group or ad), you get metrics that show how they perform against specific goals. In this example, campaign Test1 works perfectly for Goal2, while Test2 works better for Goal1.

How accurate is this?

As you might know, identifying visitors by IP might not be perfect. There is no guarantee that visitor will have same IP next time he visits website, and there is no guarantee that he’s the only one using this IP (proxies). However, I must argue that cookies are not perfect for this job either. For example, visitors can allow session cookies only, automatically clear cookies after closing a browser or block cookies and/or JavaScript completely.

Anyway, we are all probably sure that less people use proxies these days than few years ago, more people are on a broadband with fixed IP addresses and more people intentionally block cookies and analytics scripts. In other words, try this and you might be pleasantly surprised.

Conversion tracking in Web Log Storming

Recently, a topic of conversion tracking came up in the professional forum. Specifically, one member asked how to include Google Analytics tracking code into third-party order pages to track conversions and original referring websites that bring customers to him. After that, another member complained that only about ~5% of purchases were registered by Google Analytics system, so he gave up. This means that ~95% of customers were completely ignored by stats, and you will agree that those couldn’t be spiders.

Now, 5% seems a bit too low and probably varies from case to case, but nevertheless, we shouldn’t be surprised. There are several reasons why this type of analytics isn’t accurate, and it only gets worse over the time. As global awareness rises, more and more users set up their browsers to reject third-party JavaScript and/or cookies (those that are not hosted on the website they’re visiting), and some even block them all. Moreover, there seems to be a lot of interest on how to deliberately block Google Analytics, by various browser add-ons or some other ways.

Goals in Web Log Storming

Setting up Goals to track conversion ratios in Web Log Storming is pretty much straightforward:

  1. Identify the page that represents your goal, type something like “/my-goal-page.html” into File parameters wildcard and hit Enter (or F5) to refresh report.
  2. Now click “Add this as goal” link at the bottom of File parameters pane, set additional options if you wish and click OK button.

That’s pretty much it. From now on, you will see conversion percentages on most reports available in Web Log Storming. You can watch this video or screenshots to see how this looks like.

Tracking when goal page is on another website

If you are partnered with third-party payment services to process your orders, you won’t be able to get raw log files to analyze them in Web Log Storming, but there’s a rather simple solution. Usually, partner services provide means to include some custom HTML into their standard order page.

  1. Create 1×1 pixel transparent .gif image and upload it to your web server (for example, /goals/my-goal.gif). You can right-click and save this one, if you wish.
  2. In partner’s custom HTML include this code:
<img src="https://<www.mywebserver.com>/goals/my-goal.gif" />

From this point on, set up Web Log Storming similarly as in previous example. Each time visitors hits the goal page on the partner’s website, this small image will be requested from your web server, which means that you will get this information in your raw log files, and the image itself will be practically invisible for users.

What if the other website is secure (https)?

If your partner’s order pages are located on the secure server (which they are, I hope 🙂 ), browsers could show a not-so-nice warning about mixing up secure and non-secure elements. In this case, you will need to host this transparent .gif on a secure server too. If you don’t already have one, you can create a SSL certificate yourself or buy a cheap one here (under $10/year). Note that for this purpose it doesn’t have to be a super-secure server. You won’t transfer any of sensible data to it, so a formal SSL certificate will suffice.

Obviously, in this case, the HTML code should be changed to:

<img src="https://<www.mysecurewebserver.com>/goals/my-goal.gif" />

As your main website server and secure one will probably write log hits to different files, depending on your original configuration, you might need to add another Log file location in Web Log Storming’s File properties window.


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How to Track Custom Variables in Web Statistics

Recently I found few interesting questions about how to track custom variables with Google Analytics. The question well makes sense, even if your website is not a complex web application that your visitors log in to. “Simple” showroom websites could benefit from such kind information too, providing that you want to learn more about visitor behavior grouped by data not already included in stats. Here’s an example of how you can do this with Web Log Storming, but you might apply similar steps if you use some of other tools too.

Let’s say that you run online shoe-shop. At some point, you decide to present a simple survey to your visitors and put results into cookie information. In this case, you would probably be interested in demographic information such is gender, age, marital status, etc.

Disclaimer: I’m completely ignorant about selling shoes (Al Bundy would probably know better), so don’t mind if I completely missed what matters in this business. 🙂

Setting up a website

Step 1. Building a survey

Real shoe storeFirst thing you need to do is to actually build a survey. How to do that is beyond scope of this article, so I’ll leave it to you. But all surveys have something in common: they contain questions. Let’s say that questions for this example are:

  1. Gender (Male / Female)
  2. Age (20-ies / 30-ies / 40-ies / 50-ies / 60-ies…)
  3. Marital status (Single / In relationship / Married / …)

You get the picture. Put answers into a cookie and you’re ready for the next step.

Step 2. Logging this information

If these individual answers stay in visitor’s local cookies, you won’t be able to use them. It’s actually easy to “trick” a web server to write them down for you, and here’s how.

First, create a transparent 1×1 pixel gif image and upload it to your server (for example: myvars.gif). For your convenience, you can get one from here (right-click on link and save image).

Now change your web pages (or just one of them, depending how your website is organized) to include code into header or footer, similar to this:

<img src="/path-to/myvars.gif?g=<?php $_COOKIE['gender']; ?>" />
<img src="/path-to/myvars.gif?a=<?php $_COOKIE['age']; ?>" />
<img src="/path-to/myvars.gif?s=<?php $_COOKIE['status']; ?>" />

You would probably want to replace $_COOKIE[ ] parts with your functions, but we’ll keep it as simple as possible here.

These images will be invisible to visitors, but your log files will from now on contain lines like these: [18/Oct/2009:22:20:06 -0600] "GET /myvars.gif?g=female HTTP/1.1" 200 ... [18/Oct/2009:22:20:06 -0600] "GET /myvars.gif?a=40 HTTP/1.1" 200 ... [18/Oct/2009:22:20:06 -0600] "GET /myvars.gif?s=married HTTP/1.1" 200 ...

Note the emphasized parts behind question marks. Instead of placing an image for each variable separately, you can combine them into one request, so your get ?g=female&a=40&s=married. It’s up to you how you want to track them later.

Now we only need to extract these into a meaningful statistics.

Extracting and analyzing custom variables

As I said before, it might be possible to analyze this info with other products (although often with limited possibilities), but here we’ll show how you can do that with Web Log Storming. For purely selfish reasons, of course. 🙂

Custom variables in Web Log StormingFirst, you can use Queries report to see how popular each survey option is. If you define your Goals in this report you’ll also be able to see how well each of visitor groups convert.

Next and even more important, you can set up a Query parameter to focus on specific groups and analyze them separately. With Web Log Storming it’s really easy to do that (see the screenshot):

  1. Type a filter into Query parameter (for example: “a=40”) and hit Enter. Whatever report you have active at this moment, it will now be based on visitors in forties only.
  2. Optionally, click Lock button to base all other reports you select on the same set of visitors, until you explicitly remove this filter.

It’s simple as that, but there’s more possibilities for advanced filtering by combining more than one group, comma separated. Here are few examples as an illustration:

  • s=married, s=relationship
    All visitors either married or in a relationship
  • s=married, s=relationship, +g=male
    All male visitors either married or in a relationship (note the “+” sign)
  • g=female, -s=divorced
    All female visitors who are not divorced (again, note the “-“ sign)
  • +a=30, +s=divorced
    All divorced visitors in their thirties

There are numerous combinations and possibilities, and for more info how wildcards work in Web Log Storming, check this page in the user manual.

Note: if you decided to combine all variables into one request (ie. ?g=female&a=40&s=married), you’ll need to enclose filters in wildcard (asterisk) character, like this: *a=40*, +*g=male*.

How to use these insights or “Why should I care”?

Common sense tells us that our website should “push” male shoes to males and female shoes to females, right? But is it possible that it’s not the best choice? What if your analysis show that married middle-aged males often buy shoes to their spouses as a gift? You would definitely want to make it easier for them to do so.

Or maybe you discover that divorced people, regardless of age, are more likely to buy more expensive shoes, so shouldn’t you present them an appropriate offers? Or maybe this doesn’t apply to divorced people in their sixties? Maybe people in sixties are generally not interested in expensive shoes, regardless of marital status?

There is lot of questions which all make sense to me, but I’ll just stop – if someone told me month ago that I will spend this much time thinking about shoe market… 😉 Besides, I’m sure you understood the importance of visitor segmenting buy now and that you know what questions relate to you business.


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