blonded

2y

op crowdsourcing his job application homework to ktt2 im crine

that company is f***ed

scoop

2y

to be fair, that company is probably outsourcing their work through this hiring process to begin with

this company got ktt in the sweatshop working for free

vayL4

2y

For real. Those non-data set questions feel like they want OP to twerk for them in his responses

scoop

2y

ive joined companies before where some of the stuff being worked on came up in interview settings where they were asking for ideas lol. s***s crazy

props to you though for helping op out tho. the job hunting game can be tough af

vayL4

2y

@op

1. Purchases - View Based Post Exposure to the Ad

One of the key assumptions I made is that since there is no column for "revenue", all purchases are of the same dollar value. So the goal is to maximize the number of purchases which will lead to the highest revenue possible.

2. You will want to make a pivot table with the dataset, the key columns being E and O. Your final table should look like this, but with the real numbers:

From there you'll be able to determine if there's anything notable from the results.

3. You will want to make separate pivot tables for each combination and performance metrics (impressions, clicks, purchases).

These combinations will come from the ad name (Column C). Pay super close attention because the descriptors can trip you up. Check out this example below:

I filtered the ad name column (C) by the word "Merch" as I found that it directly correlates with "Ubiquity" as the value proposition. You will want to find similar correlations between terms. Here are some that I quickly found:

SSI = Speed
LFF = Simplicity
Merch = Ubiquity
Uni = All 3: Speed, Simplicity, Ubiquity

If you want to be extra, you can also factor in the amount spent (Column L) to determine what were the best/worst performing combinations based on investment. Will show you went the extra mile.

4. The three variables are "speed, simplicity, ubiquity". You'll want to find which variables are best across performance metrics (impressions, clicks, purchases).

5. I would use a correlation matrix. Assuming you can find one online.

6. Use pivot tables to figure out which test cell (from column D) has the worst results across the performance metrics.

Figure out the worst two, then do the rest.

7. Use pivot tables to figure out how well the A55-64 group (from column I) is performing across those metrics.

If metrics are good = sure, allocate more budget towards A55-64
If metrics are bad = the goal is maximizing revenue, it would be an inefficient use of budget

8. Leverage the previous pivot tables you've made for the earlier questions to figure out which audiences and creatives are most efficient

9. Dependent on #8

vayL4

2y

@op

1. Purchases - View Based Post Exposure to the Ad

One of the key assumptions I made is that since there is no column for "revenue", all purchases are of the same dollar value. So the goal is to maximize the number of purchases which will lead to the highest revenue possible.

2. You will want to make a pivot table with the dataset, the key columns being E and O. Your final table should look like this, but with the real numbers:

From there you'll be able to determine if there's anything notable from the results.

3. You will want to make separate pivot tables for each combination and performance metrics (impressions, clicks, purchases).

These combinations will come from the ad name (Column C). Pay super close attention because the descriptors can trip you up. Check out this example below:

I filtered the ad name column (C) by the word "Merch" as I found that it directly correlates with "Ubiquity" as the value proposition. You will want to find similar correlations between terms. Here are some that I quickly found:

SSI = Speed
LFF = Simplicity
Merch = Ubiquity
Uni = All 3: Speed, Simplicity, Ubiquity

If you want to be extra, you can also factor in the amount spent (Column L) to determine what were the best/worst performing combinations based on investment. Will show you went the extra mile.

4. The three variables are "speed, simplicity, ubiquity". You'll want to find which variables are best across performance metrics (impressions, clicks, purchases).

5. I would use a correlation matrix. Assuming you can find one online.

6. Use pivot tables to figure out which test cell (from column D) has the worst results across the performance metrics.

Figure out the worst two, then do the rest.

7. Use pivot tables to figure out how well the A55-64 group (from column I) is performing across those metrics.

If metrics are good = sure, allocate more budget towards A55-64
If metrics are bad = the goal is maximizing revenue, it would be an inefficient use of budget

8. Leverage the previous pivot tables you've made for the earlier questions to figure out which audiences and creatives are most efficient

9. Dependent on #8

vayL4

2y

i’m gonna clean my bathroom and shoot up some H. will be back here in like 45 minutes and hopefully i’ll be able to answer a few of the questions

blonded

2y

op crowdsourcing his job application homework to ktt2 im crine

that company is f***ed

vayL4

2y

The only reason why I helped OP is because of the heroin. If I was sober, I would've just went to G&G instead.

SauceMane

2y

They're asking too much for an entry level job that pays between 50-65k

vayL4

2y

i’m gonna clean my bathroom and shoot up some H. will be back here in like 45 minutes and hopefully i’ll be able to answer a few of the questions