I need a 12-page, single-space paper that assesses/analyzes how social media, se

I need a 12-page, single-space paper that assesses/analyzes how social media, search engines (e.g., Google), and firms use advertisement tracking methods, technology, and algorithms to collect data on current/potential customers. And how it relates to privacy concerns, ethics, and public policy in the US and how it compares to other countries. This was a based on a business seminar that I participated in, and here are the following notes and sources that can be used:
In this seminar, I learned how marketers use tracking to collect customer information and how it has evolved. The ultimate goal of tracking is to better serve the customer by aligning them with products and services that best fit their preferences and needs.
Tracking is used to satisfy the core marketing principles of the 5 C’s, STP, and the 4 Ps of marketing. Tracking’s primary emphasis is on segmentation by identifying key target markets to promote their products. Common segmentation approaches included user characteristics (demographics, lifestyles, zip codes, etc.), benefits sought, and behavioral targeting in the past. In the past, tracking was done primarily through physical observations, surveys, focus groups, along with other tactics. However, this approach was limited because it generalized groups of people. Also, sample sizes, like when using focus groups or surveys, are only a tiny window in the whole population and cannot factor in variances in customer behavior. Now in the digital age, companies can use technology to implement microtargeting strategies. Microtargeting has become the most powerful segmentation tool that can build a unique individual profile on a 1-to-1 basis. Microtargeting comes in clickstreams, tracked behavior across multiple websites, targeted ads, and social media ads.
Microtargeting has become a powerful tool for companies; however, it has raised many privacies and ethical concerns among the public. One example from the seminar that I found a bit disturbing was that machines are learning human biases. Algorithms can be helpful but can also have unintended consequences, like in the case of Airbnb. In Airbnb’s case, its algorithm found that renters preferred not to rent from black landlords; therefore, it recommends that they rent their properties at a low price. Thus, the main question posed here is what companies and individuals are doing to correct algorithms when implementing biased actions?
Another interesting question posed in the seminar is whether the algorithms engage in social engineering? I don’t have an answer to this question; however, I know that there needs to be better policies to protect consumers and companies to manage machine learning and its impact better. Overall, I enjoyed this seminar and learned how we as future managers need to consider the best pays to market ethical, and practical, and not push people towards bubbles and negative emotions.
Here are some resources presented in the seminar:
Investigation: How TikTok’s Algorithm Figures Out Your Deepest Desires (Links to an external site.) (Video)
Mark Zuckerburg Response
I Used Google Ads for Social Engineering. It Worked. (Links to an external site.)
Google to Stop Selling Ads Based on Your Specific Web Browsing (Links to an external site.)(Article)

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