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Kelari's Ultimate Strategy (0.74 - 0.77 Average)

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Kelari: 2015/06/13 08:12
Hello to all Neobux users!

Just thought of writing something about my current recycling strategy which might inspire other Neobux users.

I tried a few in the past, but with not much success and decided to run everything on autopilot untill I find something that works. And I did. My average gone up. From a typical 0.64-0.69 to a current 0.74-0.77, recycling cost is pretty low and most importantly profit went up as well! I'm still tweaking a few things and trying to improve if possible. But for now, I'm pleased.

I spent a lot of time reading diffrent strategies and stats on the forum from a lot of users and learned quite a few things. So, first I would like to thank reggen666, he really inspired me and a lot of other users as well, then magnet5674 for he's Referral Activity Breakdown Report in his stats (it's quite informative), yahiatnt for his excellent software, and of course Neobux for making all this possible.

Now, this strategy works for ultimate users, so I don't know how it would work for other golden packs. All standard and other golden members will probably have to tweak it, if it's possible. I don't know.

How it works?. Really simple. I just search for the worse referrals that I can find, the auto-recycle avoiders. Referral who clicks just before the auto-recycle would get him. I search for first time avoiders, second time avoiders, third... and so on. To easily spot those bad referrals I use yahiatnt's software and I've set the filter to only show me referrals which last click was made 4 days ago (3 full empty days) and are sorted from the oldest to a minimum age of 11 days (to see 10 full days). I check the whole clicking behaviour prior to that last click of every referral. If I see a 6-7 days gap before his last click, I recycle him. Or sometimes I'll recycle even if I see only 5 days gaps if he's doing that for a while. Golden members clicking this way are profitable so I lock them and monitor them.

Example of first time avoiders




Example of continuous avoiding

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