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What do you want to track but think you can't?

Discussion in 'General Affiliate Marketing Forum' started by Graybeard, May 5, 2019.

  1. Graybeard

    Graybeard Well-Known Member affiliate

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    Pretty much what the title says: Most the so called tracking and optimization I see being done here really doesn't help much IMHO.

    So what could you track on the person's interaction with your funnel that you think would help you to succeed more often (convert that person [that you keep referring to as 'traffic']).

    What data do you need for your 'formula' (traffic algorithm)?
    Do you make your own smart links -- and based on what?

    I am not talking about 'tools' per se I am talking about finding and utilizing (what) attributes?
     
    Karolina Voluum likes this.
  2. Voluum
  3. Graybeard

    Graybeard Well-Known Member affiliate

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    Do you even know what to track other than what you are offered?
     
  4. Graybeard

    Graybeard Well-Known Member affiliate

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    Does your offer (or affiliate program) allow you to add a key/value pair to the landing page URL? &k={value}

    PHP:
        $dottedFormatAddress $ip;
            
    $ipv4address sprintf("%u"ip2long($dottedFormatAddress));
            
    returns 185.136.156.195 now equals 3112737987 ID val
    I haven't had time to 'pretty up' that code snippet I found -- it's part of a longer script I am going to be using for traffic recording, selection and redirection.

    so k=$ipv4address
    in the url's query string:
    &k=3112737987​

    You database that number along with the campaign ID of the ad, the user country_code, the landing page of yours(id) and any data that is posted back with that ID.

    Now you can track that individual (IP) all of its interactions with your ads and websites, emails etc.

    If he buys from more than one campaign/or offer; that ID 3112737987 in that offer's stats.

    This is not an "invasion of privacy" I am just tracking with information given (broadcast) publicly. As long as I never resell that person's data without his permission it is also GDPR compliant.

    This is rather simple to program or to add to tracking tools (IMO).

    Note: I did not set or rely on a HTTP Cookie, tracking pixel (or other arcane method) :)
     
    Last edited: May 7, 2019
  5. Sajjadur Rahman

    Sajjadur Rahman Affiliate affiliate

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    I am not talking about 'tools' per se I am talking about finding and utilizing This is not an "invasion of privacy" I am just tracking with information given (broadcast) publicly
     
  6. Sajjadur Rahman

    Sajjadur Rahman Affiliate affiliate

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    Now you can track that individual (IP) all of its interactions with your ads and websites, emails etc
     
  7. Graybeard

    Graybeard Well-Known Member affiliate

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    That's a given -- the easy stuff ...
     
  8. Graybeard

    Graybeard Well-Known Member affiliate

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    My head hurts but I can see the people (70%+) behind the IP 'mask':
    mysql> SELECT DISTINCT * FROM usa_adx_traffic_sort
    -> ORDER BY count DESC limit 0, 10;
    +-------+-------------+-------+--------------+----------+
    | count | city | state | AVG_WealthRt | AVG_Algo |
    +-------+-------------+-------+--------------+----------+
    | 264 | Santee | CA | 1.31899432 | 3.23750 |
    | 165 | Los Angeles | CA | 1.03985455 | 2.42727 |
    | 147 | Chicago | IL | 1.38563265 | 3.75578 |
    | 129 | Woodland | CA | 1.32191783 | 2.36357 |
    | 112 | New York | NY | 1.77877143 | 3.95625 |
    | 109 | Los Angeles | CA | 1.00678532 | 3.09174 |
    | 94 | Bellaire | TX | 1.20100957 | 2.18085 |
    | 91 | Brooklyn | NY | 0.95858681 | 1.07363 |
    | 84 | Seattle | WA | 1.46963452 | 2.52262 |
    | 81 | Miami | FL | 0.87216049 | 1.74568 |
    +-------+-------------+-------+--------------+----------+
    10 rows in set (0.00 sec)

    *Santee, Bellaire, and the 1st Los Angeles are Mobile and have a larger zip code radius ... causing statistical inaccuracies when sorting this way. In app GPS is used for mobile "GEO Fencing" the exact location +-30m

    mysql> SELECT DISTINCT * FROM usa_adx_traffic_sort
    -> ORDER BY AVG_WealthRt DESC limit 0, 10;
    +-------+-------------+-------+--------------+----------+
    | count | city | state | AVG_WealthRt | AVG_Algo |
    +-------+-------------+-------+--------------+----------+
    | 3 | Hoboken | NJ | 2.80000000 | 7.70000 |
    | 1 | Chappaqua | NY | 2.63640000 | 9.50000 |
    | 2 | Aldie | VA | 2.59550000 | 14.50000 |
    | 3 | Sammamish | WA | 2.58940000 | 15.20000 |
    | 3 | Chevy Chase | MD | 2.50910000 | 15.00000 |
    | 1 | Larchmont | NY | 2.36360000 | 5.90000 |
    | 3 | Westfield | NJ | 2.34090000 | 4.60000 |
    | 2 | Scarsdale | NY | 2.32270000 | 6.00000 |
    | 2 | Bethesda | MD | 2.29550000 | 11.60000 |
    | 1 | Chatham | NJ | 2.28640000 | 4.10000 |
    +-------+-------------+-------+--------------+----------+
    10 rows in set (0.01 sec)

    mysql> SELECT DISTINCT * FROM usa_adx_traffic_sort
    -> ORDER BY AVG_Algo DESC limit 0, 10;
    +-------+-----------------+-------+--------------+----------+
    | count | city | state | AVG_WealthRt | AVG_Algo |
    +-------+-----------------+-------+--------------+----------+
    | 1 | Kapolei | HI | 1.36360000 | 33.20000 |
    | 2 | Folsom | CA | 1.71360000 | 20.00000 |
    | 1 | Lenexa | KS | 1.32270000 | 18.50000 |
    | 3 | Sammamish | WA | 2.58940000 | 15.20000 |
    | 3 | Chevy Chase | MD | 2.50910000 | 15.00000 |
    | 2 | Aldie | VA | 2.59550000 | 14.50000 |
    | 1 | Manhattan Beach | CA | 2.21360000 | 11.90000 |
    | 1 | Shepherdsville | KY | 1.05910000 | 11.90000 |
    | 2 | Bethesda | MD | 2.29550000 | 11.60000 |
    | 1 | Potomac | MD | 2.25910000 | 11.20000 |
    +-------+-----------------+-------+--------------+----------+
    10 rows in set (0.00 sec)

    mysql> SELECT DISTINCT state
    -> ,city
    -> ,SUBSTRING(zip,1,4) as zipx,
    -> AVG_PerCapAGI,
    -> WealthRt, Algo
    -> FROM usa_algo_test
    -> WHERE city REGEXP 'Los Angeles'
    -> ORDER BY Algo DESC;

    +-------+-------------+------+---------------+----------+------+
    | state | city | zipx | AVG_PerCapAGI | WealthRt | Algo |
    +-------+-------------+------+---------------+----------+------+
    | CA | Los Angeles | 9001 | 89585 | 1.0500 | 17.8 |
    | CA | Los Angeles | 9002 | 154141 | 1.4136 | 7.8 |
    | CA | Los Angeles | 9007 | 134035 | 2.0045 | 6.4 |
    | CA | Los Angeles | 9002 | 118646 | 1.5318 | 4.5 |
    | CA | Los Angeles | 9001 | 93160 | 0.7182 | 3.4 |
    | CA | Los Angeles | 9006 | 86217 | 1.3591 | 2.9 |
    | CA | Los Angeles | 9001 | 72312 | 0.8818 | 2.3 |
    | CA | Los Angeles | 9003 | 72996 | 1.4000 | 2.1 |
    | CA | Los Angeles | 9004 | 57318 | 1.5500 | 2.0 |
    | CA | Los Angeles | 9003 | 58826 | 1.3318 | 1.9 |
    | CA | Los Angeles | 9004 | 88371 | 1.2545 | 1.8 |
    | CA | Los Angeles | 9001 | 80557 | 0.7636 | 1.5 |
    | CA | Los Angeles | 9004 | 47240 | 1.1227 | 1.4 |
    | CA | Los Angeles | 9006 | 58957 | 1.2818 | 1.4 |
    | CA | Los Angeles | 9003 | 58896 | 1.1591 | 1.3 |
    | CA | Los Angeles | 9002 | 79177 | 1.0273 | 0.7 |
    | CA | Los Angeles | 9004 | 45948 | 0.8636 | 0.6 |
    | CA | Los Angeles | 9001 | 44137 | 0.7500 | 0.5 |
    | CA | Los Angeles | 9001 | 52609 | 0.8045 | 0.5 |
    | CA | Los Angeles | 9002 | 58682 | 0.8318 | 0.5 |
    | CA | Los Angeles | 9002 | 73741 | 0.6455 | 0.5 |
    | CA | Los Angeles | 9002 | 80437 | 0.7909 | 0.5 |
    | CA | Los Angeles | 9004 | 40073 | 0.7682 | 0.5 |
    | CA | Los Angeles | 9004 | 43910 | 0.8136 | 0.5 |
    | CA | Los Angeles | 9003 | 40906 | 0.7727 | 0.4 |
    | CA | Los Angeles | 9001 | 47433 | 0.6818 | 0.3 |
    | CA | Los Angeles | 9003 | 71418 | 0.7273 | 0.3 |
    | CA | Los Angeles | 9005 | 22979 | 0.6045 | 0.3 |
    | CA | Los Angeles | 9006 | 69246 | 0.6545 | 0.3 |
    | CA | Los Angeles | 9000 | 43194 | 0.6182 | 0.2 |
    | CA | Los Angeles | 9000 | 67327 | 0.7045 | 0.2 |
    | CA | Los Angeles | 9002 | 54293 | 0.7000 | 0.2 |
    | CA | Los Angeles | 9002 | 64999 | 0.6045 | 0.2 |
    | CA | Los Angeles | 9003 | 45389 | 0.6727 | 0.2 |
    | CA | Los Angeles | 9004 | 41994 | 0.5864 | 0.2 |
    | CA | Los Angeles | 9000 | 22111 | 0.5500 | 0.1 |
    | CA | Los Angeles | 9000 | 40585 | 0.5773 | 0.1 |
    | CA | Los Angeles | 9000 | 43742 | 0.5909 | 0.1 |
    | CA | Los Angeles | 9001 | 63922 | 0.5409 | 0.1 |
    +-------+-------------+------+---------------+----------+------+
    39 rows in set (0.01 sec)
    Sorting by GEO is a fool's game as you can see by the charts above ;)
    Image was too big

    Algo reflects the costs of living and the general lifestyle/livability and disposable/discretionary income of those that reside there.
     
    Last edited: May 15, 2019
  9. Graybeard

    Graybeard Well-Known Member affiliate

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    And then there is the POOR people :p
    in this traffic batch
    **this study was selective to adult traffic popups in May 2018
    your results will vary of course.

    mysql> SELECT DISTINCT * FROM usa_adx_traffic_sort
    -> ORDER BY AVG_WealthRt limit 0, 10;
    +-------+-------------+-------+--------------+----------+
    | count | city | state | AVG_WealthRt | AVG_Algo |
    +-------+-------------+-------+--------------+----------+
    | 2 | Laredo | TX | 0.53180000 | 0.40000 |
    | 5 | Camden | NJ | 0.56724000 | 0.40000 |
    | 14 | Detroit | MI | 0.56946429 | 0.41429 |
    | 2 | Brownsville | TX | 0.57500000 | 0.45000 |
    | 4 | Pontiac | MI | 0.57845000 | 0.27500 |
    | 4 | Jackson | MS | 0.58182500 | 0.37500 |
    | 1 | Harvey | IL | 0.58640000 | 0.50000 |
    | 2 | Edinburg | TX | 0.59775000 | 0.40000 |
    | 2 | Albany | GA | 0.60225000 | 0.35000 |
    | 1 | Ecorse | MI | 0.60450000 | 0.40000 |
    +-------+-------------+-------+--------------+----------+
    10 rows in set (0.01 sec)

    mysql> SELECT DISTINCT * FROM usa_adx_traffic_sort
    -> ORDER BY AVG_Algo limit 0, 10;
    +-------+------------------+-------+--------------+----------+
    | count | city | state | AVG_WealthRt | AVG_Algo |
    +-------+------------------+-------+--------------+----------+
    | 2 | Lakewood | NJ | 0.80450000 | 0.20000 |
    | 4 | Pontiac | MI | 0.57845000 | 0.27500 |
    | 1 | Bronson | FL | 0.72270000 | 0.30000 |
    | 1 | Corona | NY | 0.63180000 | 0.30000 |
    | 1 | Freeport | TX | 0.84550000 | 0.30000 |
    | 1 | Hawaiian Gardens | CA | 0.66360000 | 0.30000 |
    | 1 | Lincoln City | OR | 0.80450000 | 0.30000 |
    | 1 | Louisville | GA | 0.64550000 | 0.30000 |
    | 1 | Lynwood | CA | 0.65910000 | 0.30000 |
    | 1 | Maxton | NC | 0.63180000 | 0.30000 |
    +-------+------------------+-------+--------------+----------+
    10 rows in set (0.01 sec)
     
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