Our experts have gathered these Marketing Analytics Fundamentals MCQs through research, and we hope that you will be able to see how much knowledge base you have for the subject of Marketing Analytics Fundamentals by answering these 60+ multiple-choice questions.
Get started now by scrolling down!
A. your target audience and goals
B. the campaign ad size
C. the attribution model of the campaign
D. the projected cost of the campaign
A. # of clicks / # of emails delivered
B. # emails delivered / # of clicks
C. # of clicks / # bounces
A. Exponential
B. Direct
C. Derivative
D. Causal
E. Inverse
A. measuring
B. doing
C. searching
D. building
A. Marketing Channels
B. Funnel Starters
C. Message Delivery
A. None of the above.
B. Pageviews and site visits are the same thing
C. A pageview is a visit to a page on your site. One site visit will always have at least one pageview.
D. The number of site visits will always be higher than the number of pageviews in your analytics
A. Display
B. Organic
C. Affiliate
D. PPC
A. turn of the funnel
B. top of the feed
C. top of the funnel
A. Percentage of people who landed on your site, purchased, and left
B. Percentage of people who click your ad but close the browser window before landing on your site
C. Percentage of people who landed on a page and immediately left
A. most people who unsubscribe do so on accident
B. many users who unsubscribe actually intend to mark your email as spam
C. many users who are fatigued by your mailings won't go to the trouble to unsubscribe
A. Return on Analytic Statistics
B. Repeat Organic Active Search
C. Return on Ad Spend
D. Ratio of Accounts Served
A. % of users who took desired action
B. % of returning visitors to your site
C. % of users who hit your site and leave immediately
D. % of visit your site < 1 time
A. Daily Analytical Users
B. Daily Active Users
C. Direct Active Users
D. Dedicated Annual Users
A. relationship of ad strategy
B. return on ad strategy
C. recency of ad spend
D. return on ad spend
A. industry standard marketing metrics that allow you to track your performance compared to others
B. measurements that indicate M/M changes in your campaign performance
C. the practice of comparing metrics from two companies during a co-marketing campaign
D. blue lines that appear in Google Analytis when you are comparing two time periods
A. marketing CEOs
B. marketing competitors
C. marketing spendings
D. marketing ROI
A. Cost Per Impression
B. Costly Personal Impression
C. Conversion Per Initiative
D. Calculated Personal Interest
A. ROHS
B. SME
C. VBA
D. BRB
E. ROI
A. the practice of attributing 50% of successful marketing outcomes to firs- touch and 50% to last-touch
B. the practice of attributing all successful marketing outcomes to two touchpoints
C. the attempt to attribute successful outcomes across multiple marketing touchpoints
A. # of soft bounces / # emails sent
B. # of hard bounces / # emails sent
C. (# of emails sent – # of bounce backs) / # of emails sent
A. number of favorites per tweet
B. number of retweets per tweet
C. number of impressions per tweet
A. A computer virus
B. A subliminal message on a website
C. A marker that tracks a user over time.
A. High engagement
B. Increased conversions
C. Funnel fallout
A. All of these
B. Spreadsheet software
C. marketing analytics software
D. Web analytics software
E. CRM software
A. how good you are at getting the same person to come back to your site
B. the percent of users who like your Facebook page
C. how good you are at getting people to share your site
D. the percent of users who purchase during a visit to your site
A. How much to charge your customers
B. Which marketing channels produce maximum return
C. Which organic search keywords you should target
A. True
B. False
A. Key Prospect of Interest
B. Key Performance Indicator
C. Key Purchase Interest
A. Number of prospective new names
B. Number of losses
C. All of these
D. Number of new names
A. A/B testing
B. Apples to Oranges testing
C. This/That testing
D. Top down testing
A. perform searches on twitter for the number of people who have mentioned your brand
B. this cannot be measured
C. compare new visitors month-over-month for the same time period, segmenting out users who were referred from other known campaigns.
A. Cost per click
B. Cost per conversion
C. Cost per cookie
D. Cost per characteristic
A. CTR
B. Brand Perception
C. Reach
D. Mentions
A. implies that one action is related to the occurrence of another
B. implies that one action explicitly drove the occurrence of another
C. implies a marketing relationship between two companies
A. Great Rating Points
B. Gross Rating Points
C. Gross Return Points
D. Gross Rating Problems
A. subtracting, from
B. multiplying, by
C. dividing, by
D. adding, to
A. Undeliverable address
B. Unsubscribe
C. Soft bounce
D. Hard bounce
A. number of comments per post
B. number of shares per post
C. number of likes per post
A. bid on your brand name on adwords
B. write guest posts about your brand on third party blogs
C. spend more time on SEO to target traffic from non-branded terms
D. use display ads to increase your brand awareness
A. viewers who clicked your email without purchasing divided by total emails sent
B. viewers who opened your email without clicking divided by total emails sent
C. undelivered emails divided by total emails sent
A. Brand Awareness
B. Revenue
C. GRP
D. Impressions
A. False
B. True
A. How many promotions you've run in a certain amount of time versus how many you planned to run
B. How many different outlets you're currently promoting your product or service on
C. How likely a customer or client is to refer a product or service to a friend
D. How much free PR you've been getting
A. Departed Users
B. Total Users
C. New Users
D. Revenue
A. # single page visits to your site / # conversions
B. # single page visits to your site / # visits
C. # single page visits to your site / # unique vistors
D. # single page visits to your site / # purchases
A. new monthly email subscribers - opt outs and hard bounce divided by original list size
B. new email subscribers this month divided by total email subscribers last month
C. total subscribers this month divided by total subscribers last month
A. Dividing the number of unique opens by the number of emails delivered
B. Dividing the number of emails sent by the number of unique opens
C. Dividing the number of unique opens by the number of emails sent
D. Dividing the number of emails delivered by the number of unique opens
A. Dividing the number of emails delivered by the number of unique clicks
B. Dividing the number of emails sent by the number of unique clicks
C. Dividing the number of unique clicks by the number of emails sent
D. Dividing the number of unique clicks by the number of emails delivered
A. (# of subscribers this month - # subscribers last month) - bounce backs
B. # of subscribers this month / # subscribers last month
C. # subscribers – bounce backs – unsubscribes / # subscribers
D. # of subscribers this month - # subscribers last month
A. &
B. *
C. %
D. +
E. ^