how i went from zero to 22.93% conversion rate on twitter ads in 1 wk.
How i went from zero to 22.93% conversion rate on Twitter ads.
Twitter is great. It dominates the real time space and that can make it a very effective test bed for marketeers in the social space.
Twitter also provides very powerful tools in-built with the Twitter advanced search feature.
Twitter is also very powerful for the quick and cheap advert test with very highly targeted advertising.
However, twitter is NOT like any of the other social media and can easily be abused.
Twitter ads are a form of content marketing on their own and need to offer value for the reader as well as harmonize with their interests.
How I went from 0.0% to 22.93% conversion rate on Twitter ads.
There were a total of 7 tests performed from Aug 12th onward.
The best conversion rate of the first 6 was 2.47% which was actually pretty good as I am now informed. Our cost per conversion on our best test was at .31 each.
Our 7th test results were achieved at a cost of .03 each! Yes, 3 cents each. At that cost, cheap to experiment and tune the results!
The 7th test I used the software from my predictive linguistics work, the 'emotive reduction engine', and ran the twitter-feed through it for about a half an hour, isolated by an advanced search targeting specific words. I then used the results to tune my LP and my tweet. Then I launched the campaign and went to over 20% within the first few minutes. I knew I had the formula at that point. Conversions were also analyzed against follow-on behavior by visits to an amazon store I had set up for the test.
Test number 7 was profitable within a few hours.
The emotive reduction engine approach harmonizes with the underlying emotional tones of the tweetees such that we arrive at this initial level of the mid 20's in conversions.
Our next goal will be for a 50+ % conversion off Twitter ads.
Come and see what else I do with the emotive reduction engine at....
For more information on the current and past ALTA future forecasts please visit
http://www.halfpasthuman.com/#alta_sales_area
http://www.halfpasthuman.com/#timetalks for the latest 'timetalks' discussion about all things time...
http://www.halfpasthuman.com/#chemies for How to Breathe Free in a Chemtrail World! This was the LP site for the twitter advert campaign! As you may imagine, not an easy sell at any level, so well chosen to be my LP for this experiment. Our conversion rate was here, at this level in SPITE of the nature of the content, and entirely due to the emotional qualifiers/quantifiers in our lexicon. The attractant line on the Twitter advert is
How to Breathe Free in a Chemtrail World!
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clif high | web bots | predictive linguistics | future forecasts | halfpasthuman | ALTA reports | web bot reports | trends | web bot hits |social media marketing | twitter ads | twitter marketing| social marketing |
So stepping outside of my usual line of work here, which is all future-based and focused on making forecast using predictive linguistics, which is basically a science I invented in 1993 and have been working on ever since to step into the world of social network marketing.
Not a social being.
I wouldn't know how to network if I dripped over them and don't do marketing worth crap, which is why I'm poor.
So, but the good news about this is that I know how to research.
I'm not stupid, and I can teach myself so I can educate myself around all of those, and I've gotten some pretty good results so far.
And thus this quick little video about how I went from very little to greater than a 22% conversion rate on Twitter ads.
And it wasn't that hard.
I only did seven experiments, and it didn't cost hardly any money at all.
So, a quick bit of background because I'm going to be drawing in some non-woo-woo people from the social marketing realm due to how this will be labeled.
A bit of info about myself.
My name is Cliff High.
You can look me up, C-L-I-F, H-I-G-H.
I invented predictive linguistics.
I'm a software engineer, a programmer.
I wrote a lot of code that I call the emotive reduction engine that runs my predictive linguistics forecasting.
I make predictions of the future that have had a pretty good hit record, especially recently, and put these out on a site called halfpastuman.com.
You can go there and check it out.
You can also follow me on Twitter at Cliff underbar H-I-G-H.
Only 1F in Cliff for real-time updates that I drop out on Twitter.
And that's pertinent.
We'll get to that in a second.
The subject of this video is how I went from zero to 22 plus percent conversion rate on Twitter ads in only seven easy steps.
And you don't even have to do the first six.
So anyway, I mean to get to this.
So continuing about that real quick, though, my emotive reduction engine was a great deal of software engineering that I did around converting words into emotions, or rather how to extract emotion out of the language such that you can store a representation of it in the computer and program against it to do other things with words.
And we'll let it go with that.
Let's get into our subject right at the moment about Twitter and Twitter ads.
Twitter is great.
They say there's been a billion people that have gone through Twitter and 400 million of them have stuck.
What's perhaps even more interesting is 283 million, something like that.
People go through Twitter and are active on it in any given week.
Twitter is an interesting vehicle for myself because I deal in future and time and that sort of thing.
Twitter is really interesting because it's real time, or as near real time as you can get in a large aggregated database matching algorithm.
And it's very interesting.
That way, because it's real time, marketers can use it to do incredible searches such as I've done, which led to my achieving this 22% conversion rate on this Twitter ad.
And also, by the way, the conversion rate was at 3 cents a hit.
Staggering.
It's like, whoa.
Not only greater than 1 out of 5, people seeing the ad went right to my link and jumped into that engagement with me on Twitter, but it was only costing me 3 cents a pop to get them to see the ad to begin with.
And this was only my seventh ad experiment.
I like Twitter because it's real time, because it's real time, you can put together a little structure quickly.
I did my entire testing campaign for Twitter in about four hours.
I even built a back-end Amazon store as a secondary tracking mechanism for follow-through, for actual commitment to the conversion by spending money.
All of this took, as I say, about four hours to construct the website, do the landing page, do the back-end Amazon store, and do the advanced searches for the Twitter campaign.
Now, the Twitter ad campaigns that I did, I did the first six based on information that I found on the net from social marketeers who were telling me, you know, basically how to structure large-scale SQL queries because underneath all of these engines is structured query language and use those queries to get vast quantities of people and try and match them up against interests and so forth.
I did this on my first six campaigns.
My best hit record on my first six campaigns was 2.47% conversion rate and the cheapest, and it was not the cheapest, and the cheapest one I'd gotten for that out of those six campaigns was about 31 cents per conversion.
So again, very expensive conversions.
Some of them went as high as 98 cents.
And it was a question of how I was doing it relative to the supposed quality of the conversion targets.
And I say supposed because there's a tendency to put value that may not be pertinent to you.
We look recently at Procter Gamble, for instance, having left Facebook because they were not getting value for their money.
And so in my first six campaigns, I was not getting value for my money as an advertiser.
And this is my first go-round on advertising.
Never really done this before.
And so in the seventh campaign, I decided, well, what I would do is to ignore the standard marketing mindset towards reaching into clients, even though they were basically aiming towards a content marketing, as I was, and express it in a different way.
And that is to allow my work to find a self-selecting audience based on the words in which I was interested in using as this vehicle.
So I ran my predictive linguistics spider algorithms against the Twitter feed in real time again, maybe 28 minutes, something like that, to get a good base, and tagged off a bunch of emotive words around certain keywords, tagged those to tweets, and investigated the context manually.
That is to say, I went and looked at the tweets individually after they were highlighted by my software, aggregated into a collection, and then I took those collections and made some subtle changes to the lexicon I normally use for my predictive linguistics and changed it into sort of like ad conversion linguistics.
And then I went back to the content used for that's backed by the Amazon store and adjusted the wording, the preferences, the word order, and the statement types and some of the grammar to reflect the stated intent so that we have integrity, right?
Because your thoughts, actions, and words all have to be tight in order to have integrity.
And you've got to be integritist to what you're putting out there.
And so I went back and did that and adjusted my landing page for that, adjusted the content, came back to Twitter and ran an advanced search to come up with a slightly finer degree of keywords.
And then I built some demographics that would shock you because I was dealing with 16 keywords, two behaviors, one area, and two interests, I believe.
I'll have to go back and double check that.
And that was my seventh test.
And within Twitter's real time, it was near real time.
They have to digest your query, get it all set up, translate it into SQL, and then fire it off, wait for it to fill into TempDB a bit, and then start spitting the results back to you.
And all of that took probably about maybe a couple of minutes.
I went out and made myself a little bit of tea while it was happening.
I came back and watched the results spit out.
And the results were very impressive.
Almost instantly, I was about 12 to 15% conversion rate.
And I have, as I say, the Amazon back-end store that tracks the commitment to the conversion.
Plus, I have my own demographics and logs and analytics on the web page.
So, and then, because I was tracking for engagements, I was also able to track it on Twitter relative to the analytics that they had there.
Relatively simple process, didn't cause me too much mind meltdown.
A lot of marketing speak usually does because I don't understand it.
But at this level, I certainly do, obviously, to go from 2.47% up to over 22%.
And it actually reached 22.93% that evening before I went to bed.
And that's when I stopped worrying about the numbers.
I'd achieved what I was after with that particular test.
And so to do that, obviously the predictive analytics approach works, where I allow the minds to be self-selecting is basically what I'm doing.
I find subjects that the mind is interested in.
I don't care so much about the body that the mind is associated with at that stage or what's in the pockets of that body.
That's kind of immaterial.
But we all have to admit that the point of the conversions is to allow for the expression of energy, which frequently comes in the form of purchases, cash, donations, or whatever, in order to be able to tie into that, which is what my point was with this.
We have to have our conversions provide value for the individuals that are being converted.
I mean, it's a quid pro quo in universe.
You get value for the value that you offer.
And so my landing page for this was a very good landing page.
It provided a lot of information that these people had never seen before.
And it was a success as well because I was able to instantly go back, not instantly, I think it was like six hours later I was able to get some information out of Amazon and their analytics.
Indeed, we had had a successful number of sales relative to the conversion rate and in fact had made a greater amount of fees or whatever they call them.
They're not commissions, they're affiliate fees or whatever Amazon calls them.
We'd made slightly more than twice the cost of the Twitter ad to that point.
So at that point that I was doing the analysis on the Twitter ad, we'd spent $43.96.
We'd converted 1,247 people, something like that, at a cost of, according to Twitter, we were paying 3 cents per conversion.
And the Amazon store had taken in about $80 at that stage.
It was like $79 or $78, something like that.
And so it was running ahead of the cost of the advert.
And so a very profitable little test there.
Now, I've shut that down and I'm working with my lexicon to retune this such that I can hopefully achieve a better than a 50% conversion rate and retarget for a wider number of audiences and for a different kind of landing page and a different level of conversion tracking on my own.
So it's a very interesting process to, for us anyway, and so far, small but profitable test to abandon the usual way of thinking about marketing and allow our customers to be self-selecting around the language and the emotional component of that language and the objects and the context in which those objects are being referenced.
Not trying to be obtuse or oblique here, it's just that this predictive linguistics, the emotive reduction engine is complicated.
It reduces emotions that are tied up in words down to quantifiers and qualifiers, and then we make some assumptions based on those.
So it does get a little bit technical.
But at this stage, it's also a little bit profitable.
So this is cool.
I'll keep you guys updated as I go forward with this because it's quite fascinating.
And I have other motives for releasing videos on the social marketing part of it, obviously.
Seven experiments took about a week.
I started on the 12th learning about this stuff, read up about how the 12th of August read up about how Twitter and so forth works.
It's fascinating, fascinating.
And also much maligned and not well used by most of the people that are marketing on it.
They just spam it.
They just don't understand what it's all about.
And they're really better off on the other more static social media.
But Twitter is quite fascinating with its real-time dominance and for marketers that have an inquiring mind, real-time is where it's at.
So this was basically a little video on how I got from zero to 22% conversion rate in only seven small ad experiments with Twitter ads.
And you can follow me at Cliff Underbar, C-L-I-F, underbar H-I-G-H.
On Twitter.
I dump my real-time updates from our predictive linguistics on Twitter when I know they're going to be stale by the time I can get them into a report.
