{"id":13377,"date":"2018-05-02T15:00:48","date_gmt":"2018-05-02T22:00:48","guid":{"rendered":"https:\/\/www.kochava.com\/?p=13377"},"modified":"2022-08-18T15:03:07","modified_gmt":"2022-08-18T22:03:07","slug":"get-the-right-signal-from-media-partners","status":"publish","type":"post","link":"https:\/\/www.kochava.com\/ko\/blog\/get-the-right-signal-from-media-partners\/","title":{"rendered":"Get the Right Signal From Your Media Partners"},"content":{"rendered":"[vc_row type=”in_container” full_screen_row_position=”middle” scene_position=”center” text_color=”dark” text_align=”left” overlay_strength=”0.3″ shape_divider_position=”bottom”][vc_column column_padding=”no-extra-padding” column_padding_position=”all” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_link_target=”_self” column_shadow=”none” column_border_radius=”none” width=”1\/1″ tablet_width_inherit=”default” tablet_text_alignment=”default” phone_text_alignment=”default” column_border_width=”none” column_border_style=”solid”][vc_column_text]Marketers work under the assumption that their efforts influence user engagement. But is there evidence to support that assumption?\r\n\r\nThe answer lies in the quality of the datastream\u2014the signal\u2014sent to us as a measurement provider. By analyzing its quality, we can make better observations on the relationship between marketing and user engagement.\r\n

A typical signal<\/h4>\r\nIt\u2019s reasonable to believe that there is a correlation between your marketing efforts and the effect of those efforts – meaning, your signal (clicks) should correlate with the effect (attributed installs).\r\n\r\nWe oftentimes see there is little to no correlation between the signal (clicks) and attributed installs. This makes it difficult to infer causality between paid media efforts and the attributed effect.\r\n\r\n[\/vc_column_text][vc_row_inner column_margin=”default” text_align=”left”][vc_column_inner column_padding=”no-extra-padding” column_padding_position=”all” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_shadow=”none” column_border_radius=”none” column_link_target=”_self” width=”1\/6″ tablet_width_inherit=”default” column_border_width=”none” column_border_style=”solid”][\/vc_column_inner][vc_column_inner column_padding=”no-extra-padding” column_padding_position=”all” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_shadow=”none” column_border_radius=”none” column_link_target=”_self” width=”2\/3″ tablet_width_inherit=”default” column_border_width=”none” column_border_style=”solid”][image_with_animation image_url=”13379″ alignment=”center” animation=”None” border_radius=”none” box_shadow=”none” max_width=”100%” margin_top=”50″ margin_bottom=”50″][\/vc_column_inner][vc_column_inner column_padding=”no-extra-padding” column_padding_position=”all” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_shadow=”none” column_border_radius=”none” column_link_target=”_self” width=”1\/6″ tablet_width_inherit=”default” column_border_width=”none” column_border_style=”solid”][\/vc_column_inner][\/vc_row_inner][vc_row_inner column_margin=”default” text_align=”left”][vc_column_inner column_padding=”no-extra-padding” column_padding_position=”all” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_shadow=”none” column_border_radius=”none” column_link_target=”_self” width=”1\/6″ tablet_width_inherit=”default” column_border_width=”none” column_border_style=”solid”][\/vc_column_inner][vc_column_inner column_padding=”no-extra-padding” column_padding_position=”all” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_shadow=”none” column_border_radius=”none” column_link_target=”_self” width=”2\/3″ tablet_width_inherit=”default” column_border_width=”none” column_border_style=”solid”][image_with_animation image_url=”13378″ alignment=”center” animation=”None” border_radius=”none” box_shadow=”none” max_width=”100%” margin_top=”50″ margin_bottom=”50″][\/vc_column_inner][vc_column_inner column_padding=”no-extra-padding” column_padding_position=”all” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_shadow=”none” column_border_radius=”none” column_link_target=”_self” width=”1\/6″ tablet_width_inherit=”default” column_border_width=”none” column_border_style=”solid”][\/vc_column_inner][\/vc_row_inner][vc_column_text]If we plot a trendline for the data, we get a correlation (R Squared) of 0.37\u2014if the volume of clicks and installs attributed to those clicks were perfectly correlated\u2014we\u2019d see an R-squared of 1; and completely uncorrelated would be 0. Unfortunately, the graph above represents what we typically see: showing there is a poor but NEGATIVE correlation between clicks and attributed installs. We don’t believe that is reasonable.\r\n\r\nThis kind of discrepancy makes it difficult, or impossible, to plan media spend. We should be able to extrapolate the clicks required to obtain a certain amount of installs. With data like this, how do you budget your ad spend?\r\n\r\nTo rectify this, the data needs to be cleaned up. Attribution relies on a good signal; If you can\u2019t trust your signal, you can\u2019t trust your attribution. And if you can\u2019t trust attribution, you can\u2019t trust measurement.\r\n\r\nWith a poor signal, you\u2019re at risk for attribution fraud as a result of click injection. Think of the industry we work in; There are many incentives for fraud because of the last-click attribution model.\r\n\r\nA poor signal may also be reflective of an overly broad lookback window that inaccurately reflects cause-and-effect between advertisements and user engagement.\r\n\r\nLastly, it may be the result of media partners sending a mixed signal (impressions as clicks).\r\n

Signal clean-up<\/h4>\r\nAnalyze each of these areas in cleaning your attribution signal to improve your campaign results:\r\n