After the Techcrunch Bump
I see many consumer Internet pitches these days where the basic marketing strategy is to (1) get covered by Techcrunch, (2) get tens of thousands of users from the "Techcrunch Bump", and then (3) "grow virally". While a positive Techcrunch review has the potential to send thousands of consumers your way, it does not represent a marketing plan. Munjal Shah at Riya found this out after the launch of Riya back in 2006, when he wrote about "the cocaine like high and subsequent crash of the Techcrunch effect":
The Techcrunch article got put on Digg and read in thousands of feed readers and viola... the Techcrunch effect begins. Michael's blog is the single more effective vehicle to get the word to the online blogosphere about new technology companies on the planet..The unfortunate fact was that the initial hammering [our servers] took was just not the reality we would see later. The number of photos uploaded per hour began to fall and then stabilized near the end of the 22nd at around 25,000 photos per hour and would continue to fall for weeks to come. - Munjal Shah
So while a positive reception from the blogging community is valuable -- and can generate a lot of initial activity/interest and a nice looking Alexa chart -- it is not the only ingredient in your ultimate marketing success. When I see a post-launch consumer Internet startup, I basically look for a few simple things:
1) Usage Growth -- how many unique users are visiting/engaging with your site and product, and how is the rate of growth evolving over a several week period of time. I also look at the source of this growth -- is it scalable, repeatable and systemic? Is it event-driven (ie, PR)? Is it organic or driven by marketing (ie, is the company buying growth via Adwords, etc)?
2) Virality -- So many people misunderstand virality. Virality is not "word of mouth". And having a product go viral is not easy -- nor is it something you can just "sprinkle on a product" after creating it. If making a product viral was as easy as adding a "share with your friends" button, there would be no reason for the $100 Billion advertising industry. (I can see companies asking themselves -- "let's see, should we spend millions on advertising...or should we just add virality...Hmmm"). I believe a viral product is one where a consumer's basic usage of a site/product brings new users (and therefore additional utility) to the site/product. Facebook, LinkedIn and Paypal are all great examples of viral products. If you're pitching your business, you should know your viral coefficient. That is, how many new users get added virally from each additional user. And if you can get your viral coefficient greater than 1.0, then you've built something really special.
3) Engagement Level -- Do your visitors actively engage in your site? How long are they there for? How many pages do they view? What is their user experience like? One of the easiest ways I've found to evaluate a company's engagement level is to have them (temporarily) share access to their Google Analytics account -- this gives us the ability to get the data/insight we'd need without having to bother them to run each and every report.
4) Repeat Usage -- User retention tends to be an area where people pay the least amount of attention, but I think is one of the most important to monitor. Specifically, how often do people come back to your site. While there are a lot of different ways to measure retention, my preferred way is to look at a cohort analysis. Say you've had your site running for five months -- you now have five "first month cohorts", four "second month cohorts", three "third month cohorts", two "fourth month cohorts" and one "fifth month cohort". And you can see, what percent of your users come back in each subsequent month. A simple chart is below.
You can also plot it out graphically -- I've attached a generic Cohort Analysis Excel document. From this data you can learn a lot. Not only do you see how many people are returning this month, but you can see the trends over time. For example, in this model spreadsheet you can see that while the site is still just retaining a small percentage of their overall users, the rate of retention has gone up by over 250% over the course of the year. And while this example cohort analysis is shown by month, immediately post-launch I'd recommend that you create and track cohorts by week.