Understanding the Exported Rented Referrals Data

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In this section, we have some common question about the exported rented referrals data, and we will know the answers shortly.


What information we get from this data?


So, what is really inside this data? Let's have a look on this data, we can see that it is text, and the number of lines equals the number of the rented referrals we own.




Then let's focus on one line from these lines, we can see a rented referral's ID, referrals since date, last click date, and total number of clicks. This data is same for each of your rented referrals on their corresponding lines in the exported data.



Why do we need to export this data daily?


That's great, we now understand what is in the exported data, but how we are going to use it to see the clicks history and why do we need to export it daily? To tell you the truth, we can't use only one exported data, because it doesn't have the clicks history information. We need to use more than one exported data to see the clicks history information. I will describe this in the following paragraph.


Let’ assume we have exported the data every day for 7 days, and let's focus on only one referral to explain how we can build clicks history information from such data. Our selected referral as an example will have the following lines in the exported data of the 7 days in order from oldest to newest.


R650234363,20150105,20011231,0

R650234363,20150105,20011231,0

R650234363,20150105,20011231,0

R650234363,20150105,20150112,4

R650234363,20150105,20150113,8

R650234363,20150105,20150114,12

R650234363,20150105,20150115,16


Now, for the above referral data lines, let's interpret his information from his exported lines above into a table as shown below.


Data Date

Last Click Date

Total Clicks

09/01/15

05/01/15

0

10/01/15

05/01/15

0

11/01/15

05/01/15

0

12/01/15

12/01/15

4

13/01/15

13/01/15

8

14/01/15

14/01/15

12

15/01/15

15/01/15

16


We will add now extra column to our table and in this new column we will calculate the difference between the total clicks of a day and the total clicks of its previous day. This way we can read the information of how many clicks a referral made on a day. Right? This is shown in the table below.


Data Date

Last Click Date

Total Clicks

Clicks Difference

09/01/15

05/01/15

0

0 = 0 - 0

10/01/15

05/01/15

0

0 = 0 - 0

11/01/15

05/01/15

0

0 = 0 - 0

12/01/15

12/01/15

4

4 = 4 - 0

13/01/15

13/01/15

8

4 = 8 - 4

14/01/15

14/01/15

12

4 = 12 - 8

15/01/15

15/01/15

16

4 = 16 - 12


Also, to view the above table in graphical format, we can plot the days’ dates on the horizontal axis and the number of clicks on a day on the vertical axis. We can see our clicks graph now as shown in the figure below.


What happens if we don't export this data daily?


In the previous section, we have understood how to read the clicks history information from more than one exported data. So, let us see what will happen if we missed to export data on some days. We will explain using the same referral we focused on previously, but this time we will remove one of the 7 exported data for the 7 days duration to simulate that we have missing some of the days in the 7 days as follows.


R650234363,20150105,20011231,0

R650234363,20150105,20011231,0

R650234363,20150105,20011231,0

R650234363,20150105,20150112,4

R650234363,20150105,20150113,8

R650234363,20150105,20150114,12

R650234363,20150105,20150115,16


Now, we do the same, we will interpret the above exported lines to build clicks history table for our 7 days. Then we will plot the clicks history graph as shown below.


Data Date

Last Click Date

Total Clicks

Clicks Difference

09/01/15

05/01/15

0

0 = 0 - 0

10/01/15

05/01/15

0

0 = 0 - 0

11/01/15

05/01/15

0

0 = 0 - 0

12/01/15

12/01/15

4

4 = 4 - 0

13/01/15

13/01/15

4

0 = 4 - 4

14/01/15

14/01/15

12

8 = 12 - 4

15/01/15

15/01/15

16

4 = 16 - 12



As you can see, because we have missed exporting data on particular days, our clicks history table and graph were different from the table and graph in the previous section. This clearly proved why we need to export the data daily, but note that still the total number of clicks is correct, so the overall statistics is the same. Only the clicks history graph is different from the real history.


IMPORTANT! For the best and most accurate results, you must export the rented referrals data from Neobux website everyday and immediately after 12:00 mid night your local time. This will ensure that all the clicks performed by the referrals are exported end of day and will be included in the data, else, the clicks will be included in the exported data of the following day.


Now, we understand how to export the rented referrals data from Neobux, how to read it and build the clicks history information, and why we need to export this data on daily basis. These concepts are used in any tool or Excel sheet you might think of using if you need to manage your rented referrals.