“Just when I thought I was out… they pull me back in…”
– Michael Corleone
This site is split between the worlds of business and technology: this page officially marks the business section of the site, where we delve into the murky world of web analytics, revenue models, and traffic generation.
I drifted into this space by accident earlier this year as part of the word game solver project I did earlier this year. Once I addressed the technical challenges of building the site, I set up Google Analytics (and later Google Adwords) and started getting real-time feedback about how the site was doing. Once I started getting feedback on usage, that kindled an interest in “improving it”… Granted, an economically absurd use of my time. Helping people cheat at word games is not exactly a high profit space! But yet – fun….
The fact that about 90% of the available material on these subjects is either rubbish, hopelessly outdated, or self-serving (buy my Frauduct!) only makes things more fun!
At this point, my cornerstone piece of content in this area is our website revenue study and the supporting calculators. There are a few other things I may finish off this winter: until then, keep an eye on the blog for relevant articles…
The Website Revenue Study
Like many small website owners, we implemented AdSense and tested a few other things. I got curious about two things: How are we doing? How does that compare to other sites?
Welcome to the murky fog of website revenue model analysis.
We started by consulting the oracle of Delphi (aka Google) and got a confusing set of answers. Between Google’s gag rule about sharing Adsense RPM statistics and biased affiliate marketing reports, finding good website revenue data was difficult. So we took a shot at building our own data source.
Data Collection Challenges
The first issue is separating online marketers from individuals with a “web presence”. Consultants and developers are the poster child for this activity. While they may have a blog with ads / offers, the blog primarily helps generate consulting opportunities and facilitates their career growth. While the blog clearly creates value, it’s hard to measure.
The second challenge was building context around the statistics. As we started digging deeper into advertising and affiliate marketing, it became clear there are significant differences in the types of traffic. Advertising RPM numbers only make sense in context. For example, I’d be shocked to see a $15 RPM earned for a general purpose news site (these sites perform much worse). I’d be horrified to see a $15 RPM for a collection of niche medical content (this often performs much better).
Next you get the outright liars. Take 90% of what you read on the open webmaster forums with a grain of sale. Program promoter speak with forked tongue. ‘Nuff said…
The final challenge was understanding how results are affected by economies of scale. For example, selling banner ads to targeted sponsors works well in the offline world. The large Internet companies do this regularly. But does this work for a small site? Setting up these deals takes time – and we have a relatively small number of potential impressions. So the incremental revenue from a deal may not be worth the selling cost. Thus, many programs that drive the economics of a big site don’t work for small ones.
We wound up developing our own data source, an analysis of 100 recent website sales. They represent a cross-section of small commercial sites, ranging in sale price between $2,000 to $400,000. The average valuation was $15,000.
In selecting these sites, we replicated the screening process of a small investor. Each sale profile was individually reviewed, claims validated using external sources, and the underlying business model parsed. Questionable sites were eliminated from the sample and replaced with the next most recent eligible site.
This study will give you a feel for what similar small websites make from their traffic and how they accomplish this. Performance by industry / niche was trumped by more fundamental factors such as website type, audience intensity, and revenue model. This dataset will give you an idea of the magnitude of your expected results. This will help you estimate the potential revenue and resale valuation of your website or idea.
We have also used this data to build our Website Value Calculator. The website value calculator is a business valuation model. You can tweak the assumptions to get a feel for possible outcomes. This calculator takes some basic financial data about a website (revenue, expenses, traffic) and it’s operating profile and determines a price. It will also share what our data suggests you should be earning from your site under your current revenue model and traffic/audience assumptions.
Favorite Blog Articles
Here are some additional articles from the blog you might enjoy:
Disclaimer: Results are for discussion purposes only. If you’re putting your own money in the deal and don’t feel comfortable with doing your own valuation work, seek help from a good business broker, accountant, or banker.