- Blogging Tips
- Data Analytics
_aioseop_keywords: Adsense, Earnings, Monetize, Blogging, Adwords, Costs, Revenues,
Marketing, Advertisement, DataMining
If you've read my Build Your Blog Traffic Using Excel & Data Mining post, then you should be able to figure out what your busiest day is, what your most popular category is, and your optimal posts per day by now. If you haven't read it, I highly suggest that you do because what you learn here today builds on that information.
In this post I want to talk about how to maximize your Adsense earnings and at the same time minimize your marketing costs in the event you use Adwords or a similar web advertising vehicle using Data Mining. Data mining let's you find that perfect relationship between your marketing dollars spent and your revenues collected.
Finding out this relationship is as simple as adding two more columns to your spreadsheet from our previous post, just create a Marketing and Revenue column and paste in your marketing costs and your Adsense earnings. Re-run the model when your done and view the results!
To highlight this simple but powerful data modeling, I did a quick analysis of this blog's current Adword marketing costs and Adsense earnings and found out that certain type of posts yield more Adsense earnings. Interestingly enough, the second category example would benefit from more marketing dollars spent.
Our first example is a category 5 post, which are posts related to Quantitative topics such as Data Mining, Yale, and Excel. From the chart on the left, I should spend no more than $2 a day to max out my Adsense earnings.
Conversely, for any topics related to Mutual Funds (category 8), I could spend anywhere in excess of $3.50 per day to maximize my Adsense earnings!
From these two examples I can fine tune my marketing costs, build a stronger reader base, and make some money to boot! As always, if you have any questions on how to do this, please feel free to leave me a comment.
[tags]Adsense, Earnings, Monetize, Blogging, Adwords, Costs, Revenues, Marketing, Advertisement, DataMining[/tags]