We’ve been on the investor tour for the last month and a half at Loggly. We spent about a month working on the investor presentation, executive summary and revenue model to prepare. Based on the better feedback we’ve received, we’ve continued to refine the pitch and plan.

We’ve heard everything from “you need to show me how this is a billion dollar company” (lol wut?) to “move the team slide just below the problem statement”. Bad advice aside, I remain focused on our market size and, in particular, the user conversion assumptions that go along with it.

I’ll be transparent here. I expect Loggly’s model to yield a 10-20% conversion rate to paid customer from a signed up freemium account. While I have good justifications for those numbers, posts like this, by Derek Haynes of ScoutApp, would appear to contradict my assumptions, especially with comments like “The 1% rule is the Pi of freemium web apps!”. In all fairness he has an excellent point about focusing on retention optimization, but should we so blindly ignore our conversion pipe just because of the 1% rule says we’ll get the users?

Theories != Rules

As it turns out, the “1% rule” is based on observations on other websites and expected conversion from a site visitor to a paid user. Coincidentally enough, this assumption echos the controversial content creation theory and smacks of Chinese Math.

The main problem with this approach is it completely and utterly ignores the remainder of a given site’s user pipeline. Pipelines, or funnels, are the bread and butter of any sales driven organization. While sites like YouTube may have simple funnels, sites like Loggly are a bit more complicated, and a missed assumption somewhere along the way can turn your assumed 1% conversion into a .1% conversion fairly quickly. To illustrate, here’s a short list of what we’ll be tracking at Loggly (per month):

• number of ad views on ad network
• number of visits
• uniques
• % visits and uniques from ads
• bounce rate
• content consumed (price sheets/videos)
• participation in the demo (low friction getting started)
• freemium signups
• use of a freemium account
• use of certain features in the freemium account
• conversion rate to paid accounts
• use of paid account
• logging rates
• upgrades from one paid tier to another

It’s within this pipeline that we focus our attentions to help maximize conversions from visit to paid user.  Not surprisingly, the devil is in the details.

Care and Feeding of Your Pipeline

Portions of a pipeline need to have estimated percentages assigned to them, and then you need to actively monitor those conversions from step to step when the site goes live. I’ll start with the expectation of 1 conversion from 100 unique visits to a paid account and then project assumptions about the other portions of the pipeline:

• 10,000 ad views yields 100 unique visits (1%)
• 100 unique visits yields 20 content consumers (20%)
• 20 content consumers yields 10 demo participators (50%)
• 10 demo participators yields 5 freemium signups (50%)
• 5 freemium signups yield 1 paid account (20%)

Notice this gives us our 1% conversion from unique visit to paid user, but still shows a 20% conversion from freemium to paid account. Now we do a breakdown for the intermediate steps, and find places we can optimize. Your mileage may vary, so make sure you understand your steps, and measure the effects of changes on your conversion numbers when you are able to do so!

Content is King

Based on prior experience, we know the subject material of Loggly should yield decent conversions from a visitor to content consumer, where the parties are interested in the offering. At previous engagements we were able to get 10K unique video views a month off 100K visits per month. Add in another 10% viewing pricing, examples, etc., and 20% starts to seem reasonable. By driving viewing content, we increase stickiness, educate the users about the service, and increase conversions to freemium signup.

Once the user is viewing content, we want to convert them to using the demo, and then on to creating an account later. Loggly’s demo will actually be a live demonstration of the service using the user’s own content, but it won’t require the user to sign up in the traditional sense. By flipping the signup process on it’s head, we get the user using the features first, then ask them for account information after they’ve decided they like the service. All in, and based on the frictionless signup, we expect 25% of users who viewed advanced content to convert to a freemium account.

Get Out of the Way!

Remember, your signup form is a HUGE barrier to users. If you require them to provide 12 fields of data to fill out, it’s that much less likely you’ll get a signup out of the deal. Just look at this signup form – I gave up after 5 minutes of trying to fill it out properly (picky password, clearing fields on submission, etc.), even though I’m highly interested in IBM’s offer. Most people won’t spend more than a minute or so filling out your signup form. The lesson here is to get out of the way so a user can start using your service quickly.

Finding Cash in the Pipe

Remember, freemium accounts are not the same as free trials. A free trial expires, but may contain all the features of a paid account. A freemium account doesn’t expire, and usually contains a subset of features of the paid account. By keeping the freemium account active for a longer period of time than the trial (and by keeping the cost of providing services to it low) you extend the amount of time a freemium user can convert to a paid user. While this may not show up in the first few months, over time it will have a compound effect on your conversions as users desire more features from the service.

At this point in the pipeline we are at a 5% conversion rate from visitor to freemium account, which so far seems to be a reasonable assumption. If we take the 10-20% estimated conversion rate to paid assumptions, then we arrive at a .5% to 1% conversion rate from visitor to paid account, which is within striking distance of our 1% goal.

In the next segment of this post, I’ll discuss analyzing how users use their accounts, and steps you can take to maximize conversion from freemium to paid.

Edit (11/12/09): Fixed my bullets in the second list.

I’m delighted to announce Jon Gifford as the new addition to Loggly’s founding partners. Jon will be taking on the roll of CTO at Loggly, and will acting as Chief Architect for the project. Jon hails from New Zealand, by way of Australia, and did stints at LookSmart, Technorati, Scout Labs, and recently his own startup, Minimal Loop. Jon is a search technology guru who is capable of accelerating search far beyond that of mere mortal men. If you don’t believe me, just try to go search for him on Google. Frankly, I have no clue how he does it. Trust me folks, a bunch of those those results are not him.

As for the rest of the team, Raffy is now officially our COO and Chief of Product (BTW, Swiss PMs rule), and I’ll be serving as our Geek CEO and Chief Evangelist. All three of us will be coding on Loggly over the next few months, and with a dash of a soon-to-be-announced designer, we’ll be assembling the framework needed for getting Loggly up and running in private beta over the coming months.

I’m really excited to be working with such smart and capable individuals. I can’t wait to start working with equally smart and capable partners and customers.

See you in your logs!

I’ve been talking about coolcams for years as a way to help quickly show off a product’s features. Coolcams aren’t meant to be useful – they exist simply to entertain and engage your audience. It’s like an elevator pitch for your product demo.

Last year I did a coolcam mashup based around Poly9’s Flash Globe and events from my web server’s log files. I never did get around to publishing the code, but the URL was accessed 100s of times by the sales guys I worked with. If it ever was down, or broken, I’d get an email from then in minutes. As it turns out, a lot of them used the globe to start conversations with their customers.

Loggly Globe
Flash forward to present day. I’ve completely rewritten the code and put it up on Loggly’s site to share with everyone. The way the globe works is pretty simple. Using the web.py framework, it starts a web server which does two things. First, it serves up the HTML to your browser, which includes the Poly9 globe object and the jQuery library. Second, it serves up a JSON object to the page which is parsed and sent to the globe object. The code that serves up the JSON object does a few magical things for you:

• tails yor web access log file for visits
• parses out the ip address, timestamp, etc. from the log event
• takes the ip address and does a geoip lookup on it
• removes duplicate visits from a single ip address
• wraps the whole thing up in a JSON object

While Loggly Globe is hard coded to parse our logs, it should be fairly easy to use it yourself. To get started, download the tarball for Globe 1.0, and then extract it somewhere on your server:

kord@loggly> tar xvfz globe_1.0.tar.gz

You may need a couple of Python libraries installed. Assuming you have easy_install installed you can run:

kord@loggly> easy_install web.py
…
kord@loggly> easy_install httplib2

You’ll want to edit the globe.py file and modify the location of the Apache log file to point to your local log file. You’ll also want to edit the regular expression extractions to match your log file format. Here’s a line out of our logs for reference, and the corresponding extractions, most of which were pulled from Random Encounter. Make any changes you need to match the regex up with your logs.

75.101.142.96 - - [11/Sep/2009:09:19:17 -0700] "GET / HTTP/1.1" 200 6196 "-" "collectd/4.4.2" 195546

parts = [
   r'(?P\S+)', # host %h
   r'\S+', # indent %l (unused)
   r'(?P\S+)', # user %u
   r'\[(?P.+)\]‘, # time %t
   r’”(?P.+)”‘, # request “%r”
   r’(?P[0-9]+)’, # status %>s
   r’(?P\S+)’, # size %b (careful, can be ‘-’)
   r’”(?P.*)”‘, # referer “%{Referer}i”
   r’”(?P.*)”‘, # user agent “%{User-agent}i”
   r’(?P[0-9]+)’, # stuff at end
]

Now you'll want to start the server. You can specify a port number to listen on if you want:

kord@loggly> cd globe
kord@loggly:/globe> python globe.py 8001

http://0.0.0.0:8001/

Try hitting http://yourserver:8001/json and see if you get a response back. Here's an example of what you should see: http://www.loggly.com:8001/json. Here's the demo again, if you just want to skip to the good stuff. Additional work could be done to integrate the code into an Lightty or Apache install to make it more permanent. You can read more about doing that on Web.py's cookbook page.

Once we get the beta launched, you'll be able to make mashups like these with your own log files. We're looking forward to doing more coolcams like this with Loggly!

The first pass of the audio for the Loggly intro video was finished today. The clip will be used to further refine the wording of the script and start assembling the various visual elements we’ll need for shooting the video. What we should end up with is something similar to the works by Common Craft.

Not surprisingly, it took a TON of work to get the clip to its current state. Most of that work involved writing and editing the ’script’ to sound like the actor was talking to an audience. I’m no script writer, so it took a fair amount of work with Brenda (the voice actor to whom I’m married) to nail down what sounded natural when spoken, and what didn’t. There are still some rough spots, but here’s the final version of the first draft if you want to take a listen. The script is here, less some final edits.

Back in the day, when John Leestma and I were involved in producing the Splunk Videos, we would do outtakes of the different developers doing their thing during filming. You had to do something to keep things entertaining – a 5 minute video would take all day to film and occupy 1/3 of the available conference rooms. It’s really too bad we didn’t publish them, some of them were side splitting.

Speaking of cracking up, the wife and I have always enjoyed a good laugh together. Here’s hoping you get a hoot from our silly outtakes. All your logs are belong to us!