Nope, no editor. I only read the first couple of articles that each writer sends me. Beyond that, they get sent straight to my VA for uploading to Wordpress. I then do the final formatting touches. If there's anything really wrong, it will stick out and I can fix it then.
That's a very interesting way to think about content value.I spent a total of $495 to increase my monthly revenue by $90/mo and added $19,470 valuation to my site when it comes time to sell (using 33x valuation multiple).
Indeed. Same with PBNs. Most buyers aren't going to care. Earnings are what matters because it shows Google likes the site. That's the hardest part about SEO.That's a very interesting way to think about content value.
I used to think content quality would add a large premium on a sale, but judging from the offers I've gotten, buyers don't really care too much. Earnings are far more important.
I personally wouldn't buy a site with crap content and PBN links though, because I would consider it too volatile and risky.Indeed. Same with PBNs. Most buyers aren't going to care. Earnings are what matters because it shows Google likes the site. That's the hardest part about SEO.
Your idea's good, but several variables might mess with your numbers big time:This allows me to quickly see which pages have been underperforming for a time period. I chose 90 days to get rid of variance, but I suppose 60 days, might be a better measurement. The goal is to find that middle position, between obsessing over stats and just letting things ride. I sacrifice some earnings on some pages, for scaleability, but I still get alerted of serious declines.
Good points, particularly about seasonality.Your idea's good, but several variables might mess with your numbers big time:
For seasonality it might be worthwhile to plot performance per month of year, while you might (partly) solve for variable #2 by grouping content based on age i.e. what is the avg. performance of 30 day old content, 90 day old, etc. You'll probably have to play around with the buckets (groups) so things don't get too granular.
- Seasonality (e.g. products that are HOT in summer, but dead in winter)
- New & low traffic pages will skew numbers (no performance, high % because of 10 visits with 1 sale while that's not reliable statistically, etc.)
- Cookie period etc.
I'm also trying to tackle this issue ATM, thinking through what kind of data I really need, what's just useless data p*rn, etc.