So what exactly is Keyword Competitiveness (KC)? It’s only the feature within Long Tail Pro that completely changed the game and made keyword research so ridiculously simple that even a dumb truck driver like me could become an expert! It basically works like this. As soon as you click the button in Long Tail Pro Cloud to retrieve keywords, it automatically calculates a number for each keyword (between 1 and 100) based on several different SEO factors. Lower numbers mean the keyword is easier to rank for and higher means it is harder to rank for. More on that below…
I was going to post screenshots here showing my numbers for the past year – but the dashboards in the old affiliate platforms (Clickbank and JVZoo) don’t provide the best visuals – so I’ll just show you my total affiliate income for the past year. In one year (March 13, 2015 to March 13, 2016) I earned $3867.60 in commissions for promoting Long Tail Pro. Not bad for having just a mildly popular ‘passive income blog’ and only a small email list!
Keyword Researcher is an easy-to-use Keyword Discover Tool. Once activated, it emulates a human using Google Autocomplete, and repeatedly types thousands of queries into Google. Each time a partial phrase is entered, Google tries to predict what it thinks the whole phrase might be. We simply save this prediction. And, as it turns out, when you do this for every letter of the alphabet (A-Z), then you're left with hundreds of great Long Tail keyword phrases.
Earlier, I wrote a post about the use of long tail keywords. Focusing on long tail keywords could be a good strategy, especially when trying to rank in a highly competitive market. But how do you decide on which (long tail) keywords you want to rank? This post will give you some handy tips and keyword research tools to make your keyword research a bit easier.
Unlike similar tools, Serpstat is a page-oriented platform for in-depth competitive analysis. You can find competitors and define missing keywords for a single URL or even entire domains. You can also view historical position data for a range of pages organized by phrase, as well as see which pages have dropped in rank and their rank distribution as a percentage, which is very handy if you want to compare data from two different time periods or observe changes over time based on algorithm updates and other factors.
The final sales price was based on a multiple of trailing 12 months net income (i.e. The average net income over the most recent 12 months). I feel like I got a very good multiple. I had talked to the brokers at FEinternational, Quiet Light Brokerage, and had viewed sale history of other similar companies, so I know the price I received was very competitive.