Issue link: https://hub.uberflip.com/i/1359949
what content marketers do and what results their activities get. As usual, most of our results show correlations in the data. The notable exception to this e dcvey: ce placement. For all other results, the sophisticated reader can feel free to adhere to the old maxim: correlation does not necessarily imply causation. Just because we see a correlation in the data, this does not mean that we have deed e cae f c- ea Hweve, a a a- tempt, it is important to identify these correlations, because they may point at what the best prac- tices can be. Observing correla- tions is still a step above simply looking at what other content marketers are doing. Content creation and place- ment stands apart in this man- ner. Instead of simply looking at a correlation, we observe the dynamic response of items to being placed in a "stream." This is a causal impact analysis. We eyed a xedeec regression analysis to see if the views of content pieces increased after placing them in additional streams. The re- sults show us that even in the same domain, by carefully organizing content, and mar- keting to relevant audiences, it is possible to increase the viewership of existing content. This is in contrast to the well- known SEO practice of hav- ing content in one copy only. We present evidence that it is good to have multiple copies of the same item, even on the ae da, ceae de- e exeece f dee audiences. Thankfully, instead of boring you with the details of this analysis, we are able to express the results with a helpful visual. We hope that you have found it interesting, relevant, and convincing. APPENDIX LETTER FROM THE DATA SCIENCE LEAD