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KNN Classification Model for an advertisement campaign built on customer demographics, web impressions, and clicks.

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Facebook-Ads-and-Sales-Conversion

What can we learn about about an anonymous company's social media ad campaigns? What will this analysis tell us about their sales conversions?


PURPOSE AND CONTENT

This project's aim is to garner a deeper understanding of the anonymous company's Facebook ads based on customer demographics, impressions, clicks, and sales conversion. More specifically, what qualities and trends correlate with better sales? To answer this question and more, an exploratory analysis and a KNN classification model will be conducted on the dataset.

1.) ad_id: the unique ID for each ad.

2.) xyzcampaignid: an ID associated with each ad campaign of Company XYZ.

3.) fbcampaignid: an ID associated with how Facebook tracks each campaign.

4.) age: age of the person to whom the ad is shown.

5.) gender: gender of the person to whom the add is shown.

6.) interest: a code specifying the category to which the person’s interest belongs (interests are as mentioned in the person’s Facebook public profile).

7.) Impressions: the number of times the ad was shown.

8.) Clicks: number of clicks on for that ad.

9.) Spent: Amount paid by Company XYZ to Facebook, to show that ad.

10.) Total conversion: Total number of people who enquired about the product after seeing the ad.

11.) Approved conversion: Total number of people who bought the product after seeing the ad.

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KNN Classification Model for an advertisement campaign built on customer demographics, web impressions, and clicks.

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