Exam study material Digital Marketing & Analytics, UVA MBA Business Administration
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Course
Digital Marketing and Analytics
Institution
Universiteit Van Amsterdam (UvA)
This is a coherent and complete summary of all relevant study materials for the exam. It includes both lecture and tutorial slide information and short additional information about the articles.
Week 1 - Platforms, Data Types, Metrics & Conversion-Attribution I
“Half the money I spend on advertising is wasted; the trouble is, I don’t know which half.”
Main Challenge: Measuring the real IMPACT –no speculation, no wishful-thinking –we need to know what
really matters
--> 10% increase in profit, but where does it come from? The right keywords, the right influencer chosen or the
something else?
Digital Landscape: Expanding
• Online data getting more and more complex and challenging now
• But the data is also getting rich and diverse to have a better understanding and then, predict and
manage customers’ behaviour
Digital: Distinct with personalization & User generated Contend
Definiton UGC = original, brand-specific content created by customers (at no cost to you) and published on SM
or other channels, including images, videos, reviews, and testimonials
Personalization (Individualisation) and UCG what make today’s digital platforms substantially different than
traditional offline marketing
• TV, Radio, Newspaper: (non)digital traditional media (same message to all);
• New Digital media (unique-personalized messages and more information exchange between customers)
• Customers actively generate content and impact/shape-up other customers and firms’ behaviour
• UCG more and more influential, can be even more influential than ad itself
o Reviews of past users more influential for new customers than advertisements
Digital Marketing. Customer Journeys & Touchpoints
All these goals and benefits can be achieved through designing and managing seamless customer journeys on
digital platforms by using right digital touchpoints synchronized with offline platforms & touchpoints.
• Everyone's journey is different but 5-10 key journey profiles, need to analyse potential customer's clicks,
website visits etc. in order to provide/ offer most effective customer journey design --> choose right
touch points
,Touchpoints: Paid-Owned-Earned Media
• Most widely used classification in marketing & advertising practice.
• Know and used by most marketeers
• NOTE: This is not a must-use & universal recipe, but easy to understand and implement
Paid Media: where you pay including advertising, search engine advertising and promoted social media
content.
Owned Media: i.e. your web site, your app, your social media platforms – so where you can post your own
information for ‘free’.
Earned Media: is the most difficult, yet a valuable type of media. Word of mouth, conversations, comments,
likes and shares. (can also be negative)
à Thus a vlogger or influencer is by definition Paid Media (NOT Earned) since it practically is a paid medium.
However –going one step beyond – the customer-to-customer sharing stimulated by influencer, then is an
earned activity.
Why do we need such classifications or why don’t we handle each touchpoint in a granular way?
Hundreds of online (and offline touchpoints) –hard to make managerial decisions for each touchpoint
--> POE helps decision making whether the firm should focus on advertising (paid), content & service (owned)
or engagement (earned)
Extension through media:
Category Media: relates to the category that do not mention the advertiser’s brand neither published by the
focal brand.
Captures 1. competitors’ own, paid, and earned media and 2. independent publications related to the product
category.
Motivation: Control Level on Earned (Individuals) and Category (publications, competitors different
Control: Earned> Category
,Digital Data Types
Classification 1 - Structure
Data could be structured vs unstructured in nature. The management and analysis of the data depends on this
structure accordingly.
Structured Data: Mostly Quantitative (numeric).
• Examples: Sales in Euro, Click/No Click (0-1), Session time, Number of Likes etc.
Unstructured Data: Mostly Qualitative: Textual or Visual Data: Photos/Video
• Examples: Instagram Videos, Online Reviews, Social Media Posts
Example of same information
• Importance of unstructured data rapidly increasing --> 80% of all business-marketing data
Classification 2 - Data Source
(a) On-Site Data: what you see on website: available and visible to anyone. extracted through: data/web
scraping
(b) Clickstream/Session Data traffic on website-app: what, when and how people do online –not visible to
visitor (i.e: Google Analytics)
(c) Online CRM data > customer’ online history with the firm (i.e.: purchases, demographics, etc.)
1. On-Site Data - Web Scraping
• What you see on the website (product lists, comments, reviews etc.) –visible to all viewers & visitors.
• Could be structured (i.e.: number of likes) or unstructured (i.e.: user reviews in text)
• COLLECTED BY WEB SCRAPING: Collecting data from web sites, social media platforms
o i.e.: such as product information/listings, customer reviews, ratings, comments, posts through
scraper-software and importing to local data base in xls, sql or other format
, 2. Clickstream-Session Data
Clickstream = behavioural data
• This is NOT data on what is visible on the website, but what customer do/ what they click on the
website!
• COOKIE : Tiny text file in your web browser storing information about your browsing experience (e.g.
login information, user preferences, shopping cart) > SOURCES: Google Analytics, Double Click etc.
1 Individual Level Data: recording each visitors’ individual behaviour with a time-stamp. i.e what each customer
does step by step.
2 Aggregate Data: total numbers. not focusing on individual level behaviour instead > total number of visitors
etc.
3. Online CRM & Complementary Data
• Mostly Backoffice data (online) of the company encompasses historical-retrospective data on customer
relational history:
o Purchase/relation history with firm (# number of purchases, customer service contacts)
o Campaign history, Feedback / Support queries, demographic information, address, location
4. Emotional and Behaviour Data
• Emotions and Attitudes are non-observable
• Surveys + reviews, emojis used on Social media etc.
5. First, Second, Third (and Zero) Party Data
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