Thread by @Heispe

/Thread about possible #ad_fraud and how I analyzed it.
I am a big fan of twitter and until now I thought it is a great marketing platform to reaching a good target audience - but I seem to be wrong. But read yourself

For this analysis I used the @newrelic telemetry data platform and the data analyzed are access logs from @fastly where I got some excellent support from.

So our access logs told us: 138k visits in the past week from @Twitter - wow. NOT BAD !!

My motivation in the first place was to help our #marketing team getting more insights into the success of our paid #socialmediamarketing campaigns to make them more successful - getting faster in removing those who don't perform and allow them to experiment.

But this turned out to be a tough task. With a very very worrying result at the end. Because the first look a the last week traffic from twitter looks like this.
(all traffic filtered by utm_source=twitter over the last week - redacted)

It seems that our employee marketing is working well. We use @postbeyond and all employees are invited to post prepared content on the internet. The other campaigns are paid #socialmarketing campaigns - top ten. (whatever buffer is...)

So I was keen to see where the traffic is coming from and to look for other attribues @fastly 's access logs provide. Such as country, city, Bot classification, client proxy information. (the proxy description and proxy type ? are not classified = probably real user)

By looking at the charts recognize a weird city and country distribution (given that most campaigns are EMEA campaigns) but also - it is clear that most of traffic is orignated from clients already classified by @fastly as bots.

@newrelic allows me to narrow the results down to where I expect real user to be. So I filter out the bots (click on false), concentrate on real users (proxy type = ? and proxy description = ?) which brings me down to 51k clicks - sure - with that many clients classified as bots

Now I gotten rid of the bots in my charts look at the geo distribution again. Uh....so much traffic from Singapore? And so much traffic from Singapore on the @Postbeyond campaign and our EMEA campaigns...weird - isn't it. Let's dig deeper

A nice feature in the logs from @fastly is that they provide a "client_as_name" attribute that I ingested to @newrelic as well - and it shows me that most of the Singapore originated traffic comes from a single ISP.

Ok....this is strange - so I wanted more details from the data. And narrowed the traffic down to this provider. So I look a the user agents of the clients requesting our page from a Twitter Marketing campain - not classified as bots.

And here is the result of those "users" requests from Singapore. Hey Singapore people - didn't you know that Chrome has a version 103 out there? Look at the distribution - clearly you can see - these are bots. Lets kick them out for further analysis.

So, we are now down at 13.2k Traffic from our investment into twitter. 10% of what we'd seen in the first place. And we have 4 filters applied only.

our @Postbeyond campaigns are no longer in our top ten. And we see a pretty equal distribution of the traffic coming from our #digital Marketing campaigns with an expected dip today (Saturday).

But...looking at the distribution per geo I appear not to be completed with my mission - why are our EMEA marketing campaigns clicked from South Africa? I was not aware that there is so much interest in #o11y . Let's dig deeper..

Honestly now things get a bit weird. I focussed on the ZA traffic, I repeated the 'look for the user Agent play' and I checked further things and the only thing worrying me is the equal traffic that coming from the cities and that campaigns generated equal interest clusters.

Would it be a fair question @TwitterMktg to ask why South Afrika has such an interest equally distributed over 4 Campaigns meant for EMEA and equally distributed over the cities in ZA ? If I had to guess:

There are real people motivated by whatever clicking on #DigitalMarketing campaigns.
But why? I hope this is not for *making it appear* as if the Twitter campaigns are successful and generate traffic.

I walked done the road a bit further and identified a couple of other countries with exactly (!!) the same pattern: high distribution of client agent, equal interest in every campaign, weird distribution over cities. And filtered all out. Plus some obvious bots.

I know for sure I excluded maybe 20 or 30 Real Real user clicks with this filter but...now I am down to ....

1.6% of what showed up as Traffic from Twitter originated by Twitter campaigns - or roughly 5% after excluding pre-identified bots.
And if I had to guess: Out of these 2.64k "visitors" > 50% are human bots.

Oh, and whom it might interest. During the same time frame we have identified 4164 organic clicks from @Twitter

/end

@sweetlew @ry_veitch @dionsis ;-)