Web Science/Part2: Emerging Web Properties/Web Search Ecosystem/Metrics for (online) advertisement/quiz

'''An advertiser (online shop) runs an ad campaign to increase his sales. The campaign runs with a CPC of 0.50 Euro and will successfully deliver 2000 Clicks. After the campaign is over he receives the report stating that he had a conversion rate of 2% and a click through rate of 1%.'''

{Which of the following statements are true? - 100'000 people saw the advertisement - the ad received 100'000 views - 200'000 people saw the advertisement + the ad received 200'000 views.
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 * no we don't know if every view was by a unique person
 * no we don't know if every view was by a unique person
 * correct you have to work with the click through rate $$\mathrm{VIEWS} = \tfrac{\mathrm{CLICKS}}{\mathrm{CTR}}$$ which translates to $$\mathrm{VIEWS} = \tfrac{2000}{0.01}$$

{What was the CPM of the campaign from the above mentioned setting? - The CPM was 1 Euro - The CPM was 2 Euro + The CPM was 5 Euro - The CPM was 10 Euro - The CPM was 20 Euro - The CPM was 50 Euro - The CPM cannot be determined from the given data.
 * type="[]"}
 * The total cost was 1000 Euro. 200'000 views have been generated from the campaign cost per view = $$CPV = \tfrac{TOTAL COST}{TOTAL VIEWS} = \tfrac{1'000 Euro}{200'000} = 0.005 Euro$$ Now CPM = CPV * 1000 ==> 0.005 Euro * 1000 = 5 Euro

{What was the Bounce Rate of the campaign from the above mentioned setting. - 1 % - 2 % - 5 % - 10 % - 20 % - 50 % + The Bounce Rate cannot be determined from the given data.
 * type="[]"}
 * Bounce rate Rb is defined as $$R_b := \frac{T_v}{T_e}$$ where 1.) Tv = Total number of visitors viewing one page only and 2.)Te = Total entries to page. We know the number of entries is 2000 but we don't know the number of people who only viewed one page.

{In the above setting what was the cost for the shop owner to acquire a new customer? - 0.5 Euro - 10 Euro + 25 Euro - 50 Euro - 1000 Euro
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 * This can be known by applying the formula acquisition cost = $$\frac{\mathrm{CPC}}{\mathrm{CR}}$$. Another way would be to know that the campaign costed 1000 Euro (= 2000 Clicks *0.5 Euro / Click) and that the Campaign brought 40 new customers (2000 Clicks * 2% Conversion rate). 1000 Euro/ 40 Customer = 25 Euro / customer

{map the formulas to definitions -+-- $$ \frac{\mathrm{Number\ of\ Goal \ Achievements}}{\mathrm{Visits}}$$ +--- $$ \frac{\mathrm{Clicks}}{\mathrm{Views}}$$ $$ \frac{\mathrm{Clicks}}{\mathrm{Unique\ User}}$$ +--- $$ {\mathrm{Clicks} \over \mathrm{Impressions}}$$ ---+ $$R_b := \frac{\mathrm{T_v}}{\mathrm{T_e}}$$ where 1.) Tv = Total number of visitors viewing one page only and 2.)Te = Total entries to page
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 * CTR | CR | CPM | BR

{select the players that benefit from the following statements in a given CPC campaign -+ low Bounce rate -- high Bounce rate -+ low CPC +- high CPC -- low click through rate -+ click click through rate -- low conversion rate -+ high conversion rate -- low CPM (not sure to include this) -- high CPM (not sure to include this)
 * type="[]"}
 * Publisher (content owner) | Advertiser (some brand)
 * one could argue that this would benefit the advertiser as a low click though rate result in more views for the advertisement. But there is at least the counter argument that customers don't seem to find the ad interesting

{Which of the following statements about relevance and metrics are correct? + If users believe the ad is relevant for them the Click through rate will be high - If users believe the ad is relevant for them the Click through rate will be low - If users believe the ad is relevant for them the Bounce rate will be high - If users believe the ad is relevant for them the Bounce rate will be low - If the ad is relevant for the users the Bounce rate will be high + If the ad is relevant for the users the Bounce rate will be low - If the ad is relevant for the users the Click through rate will be high - If the ad is relevant for the users the Click through rate will be low
 * type="[]"}
 * The user does not know what the product is but if he thinks the offer is relevant he will click to find out.
 * Statements about the bounce rate can only be made after the user really knows if the ad was relevant to them.
 * If the ad really was relevant the bounce rate will be low since the user is satisfied with the offer and likely to stay on the site.
 * Click through rates are only correlated to the belief of the user and not his real perception of the offer