When an impression isnt made (say 50% in view for 1 second) then no one is getting billed. This is the standard practice for internet advertising.
As far as I know Facebook does the same thing. I haven't read the Facebook advertising documentation in a long time but know that they outline many of their metrics in detail. People haven't been getting overcharged and it hasn't effected billing. From the article: "... it did not impact billing, and we have notified our partners both through our product dashboards and via sales and publisher outreach. We also renamed the metric to make it clearer what we measure. This metric is one of many our partners use to assess their video campaigns."
What are the implications of this? "Due to the miscalculated data, marketers may have misjudged the performance of video advertising they have purchased from Facebook over the past two years."
The other part about making it difficult to compare against competitors is true regardless of having the same metric due to site and user differences. Maybe facebook users spend more on average than twitter users after clicking on your ad for an ecommerce site? A/B tests towards the goal you're interested in is much more fruitful from a business perspective then say comparing click thru rates.
I currently spend $X,000 per day in advertising on facebook. Their reported clicks barely match up within an order of magnitude.
I've spent 4 days investigating this, so it's worthwhile to share the data.
For every 100 clicks I purchase, at a strong CPC ($0.10 - $2.00 CPC), I have found:
- GA tells me i got between 40-60 sessions
- piwik tells me ~70
- server logs show that page was requested ~400x (not indexed, a FB-only lander). I have IP and UA recorded, and both are rotated. My guess is that FB preloads the HTML LP when the impressions shows from mobile, so the browser is primed to quickly load assets (w/o sig resources to d/l images/etc -- just request the page that initially loads all that)
My point is attribution for conversions and link clicks is hard.
Any marketer worth their salt avoids the thought of "I paid for 10 clicks but GA only shows 6".
A better marketer thinks, "I paid $660 to acquire 2 customers. Is that acceptable?"
>A better marketer thinks, "I paid $660 to acquire 2 customers. Is that acceptable?" //
You're right, but that doesn't have a bearing on whether the advertising you bought was fraudulently presented though. Yes you should be wise, but we should still imprison people for fraudulent acquisition of other people's money, even if you still thought you ultimately got a good deal.
This. Experienced marketers know analytics sources will never fully match. That's why you look at things directionally and focus on measuring bottom line impact.
Source: someone who has had to deal with clients who insist that all our various js-based tracking methods should 100% match backend data and each other.
Literally every form of fraud ever is detectable and preventable if the victim is willing to dedicate her life to dissecting every metric and cross-referencing with a billion other metrics. How is this an argument? They lied, and it induced people to give them money.
As far as I know Facebook does the same thing. I haven't read the Facebook advertising documentation in a long time but know that they outline many of their metrics in detail. People haven't been getting overcharged and it hasn't effected billing. From the article: "... it did not impact billing, and we have notified our partners both through our product dashboards and via sales and publisher outreach. We also renamed the metric to make it clearer what we measure. This metric is one of many our partners use to assess their video campaigns."
What are the implications of this? "Due to the miscalculated data, marketers may have misjudged the performance of video advertising they have purchased from Facebook over the past two years."
The other part about making it difficult to compare against competitors is true regardless of having the same metric due to site and user differences. Maybe facebook users spend more on average than twitter users after clicking on your ad for an ecommerce site? A/B tests towards the goal you're interested in is much more fruitful from a business perspective then say comparing click thru rates.