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I recently discovered a web based Twitter account management analytics tool that really opened my eyes to what works and what does not when it comes to developing an effective base of Twitter followers...

Find out which of your Twitter updates made people follow or leave you. Simply enter your Twitter ID in the following form.

Your Twitter user ID: @RalphPaglia
And we're done, here is your results summary:

(Example) You are Ralph Paglia (RalphPaglia) and you have 2960 followers.

In the last 183 updates you lost followers 6 times and got new followers 5 times. Overall you lost 143 and gained 136 which means that in total you lost 7 followers.


The TweetEffect social media marketing tool shows automotive marketing professionals exactly which tweets caused them to pick up followers, compared to which tweets caused them to lose followers... The following chart shows exactly which Tweets I sent out over the past few days that have caused me to gain followers and likewise, which tweets (and retweets) caused me to lose followers. Including how many followers I gained or lost based on the tweets i sent out:

(click on the image to view the full sized chart)


In my opinion, the usefulness of the TweetEffect tool could be extended far beyond simply manage a dealership's various Twitter accounts... It could also be used to assess which types of information resonate with dealership customers within a given local market area.  Anyway you look at it, being able to see which tweets triggered either a "Follow" or an "Unfollow" amongst a dealership, manager and automotive professional's Twitter followers is a fascinating and useful insight into what makes people want more, versus what makes people want to shut you out!


What's YOUR opinion on this interesting automotive marketing analytics tool?

Tags: Media, Most, Social, Tool, TweetEffect, Twitter, Useful, World, marketing

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Replies to This ADM Discussion

What is all this then?

Twitter is a great way to keep in contact, distribute news and generally tell people what you are up to. The success of Twitter users is generally measured in the amount of people that follow your updates.

You get information on your Twitter profile as to how many people follow you and you get notified when someone follows you. However, there is no notification when someone stops following you and you generally don't have any insight into when people follow or leave you.

This is where the TweetEffect comes in - simply enter your twitter name and we analyze your 200 latest updates and flag those up that made people follow or leave you.

Of course there are more factors that make people come or go, but it is an interesting indicator about the effect your tweet might have had on the world.

TweetEffect is a test - you could call it a hack to try out some of the Twitter API functionality mixed with free Yahoo and Google services. Maybe this will go places, maybe it won't.

Frequently asked questions

How to use the TweetEffect

Using TweetEffect is easy as pie: simply enter your Twitter user name in the form above and hit the "tell me more" button. It might take a while to retrieve and analyze your data but soon you should know about the impact you had on the world.

We list all the Twitter updates that had an effect on your follower numbers. Updates that made people leave are displayed in red, others in black.

TweetEffect is showing my protected updates to the world! How dare you?

TweetEffect is not making your protected updates available to the world - this is a misconception as you are logged into the Twitter API when you use it. Protected users can test that your updates are still safe by logging out of twitter and then trying TweetEffect. You will see an error message that your data is not available and *not* your updates - this is what the world sees, too.

As a general rule it is a bad plan to stay logged in - maybe an Air client like Twhirl or Snitter might be a better solution for you as you don't want your data to be available to the world.

That is a lot of information, are you storing that? What about my privacy?

Nothing here is being recorded or stored. All the information you see is something you entered in Twitter and made available to the world. All we do is analyze it and re-print it here when someone (probably you) asks for it.

The data seems random and doesn't match my email notifications or other "quitter" services. Are you in reality not psychic at all?

All we use is the data we get from the last 200 Twitter updates (this is an API limitation) and you may have other tools that tell you about the people who left you that tell you differently.

Without asking for your login data or storing your information this is all we can do. And we don't want to do either at this point as you giving out your information to a third party is simply wrong and we should have other ways (oAuth anyone?) to get there.

Is there a way to store this information?

Right now there is no way to generate reports to be saved, which is partly due to Twitter API limitations (traffic restrictions). We are considering options to offer that functionality though.

Is the service free?

Yes, this service is totally free. We're happy about any support if you want to have more functionality or bespoke services though.

Contact Us

As this is a monitoring service for twitter the easiest way to contact us is via twitter. Simply make an update with #tweeteffect in it and we will contact you.

Ralph:  Looking over the headlines of the tweets to see if there is a correlation between those and whether they lose followers or gain them might be a bit speculative at this point.  You notice that some of your losing headlines are not all that different from your winning ones.  As an example, however, you are being somewhat sarcastic with the headline about failed BDC managers becoming speakers at conferences.  You lost on that one.  I would think you would have to see if sarcasm was a factor or not by using similar sarcasm in other headlines to see how that does.

The tool could be very effective, but you need to test variations against it and develop some sort of matrix to do an analysis on a continuing basis.  I'd be interested to see what patterns evolve.  I do see your facination with it, however.


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