extra Flashcards
TOFU
awareness
MOFU
consideration
BOFU
conversion
digital marketing funnel and or journey 5
awarensess, consideration, conversion, loyalty, advocacy
TOFU what to do 4
SEO, Social media marketing, Pay per click ads
click throughs
prospects
(50%) of leads. people who respomnd
MOFU what to do
bounce rate, content readers, leads
BOFU what to do
prospects, conversions, repeatss, advocates
leads
people who opt in via form
Rule Based Techniques: Calculating Attribution Value
deze oefenene
) On-Site Data
what you see on website: available and visible to anyone. extracted through: data/web scraping
Clickstream/Session Data
traffic on website-app: what, when and how people do online – not visible to visitor (i.e: Google Analytics)
Online CRM data >
customer’ online history with the firm (i.e: purchases, demographics, etc.)
what is #1 priotity for marketing professionals and has the most gaps=
multitouch attribution
A TOUCHPOINT can have three roles in a customer journey
NTRODUCTION, ASSIST, AND CONVERSION
Loyalty-Loop
Shorter-Faster journeys with a shorter search-consideration stage where customers know what and how to do – maybe not at the first time but when you are back again for a repeat-purchase
stages customer journey Hedonic purchases
consumers use social media and on-site product pages as early as two weeks before the final purchase.
stages customer journey; utilitarian products
consumers use third-party reviews up to two weeks before the final purchase and make relatively greater usage of search engines, deals, and competitors’ product pages closer to the time of purchase
Touchpoint shape up hedonic products 3
(1) embrace social media and (2) monitor on-site product page views. (3) on-site product pages are leveraged extensively at the beginning of the journey and start to reduce before the purchase
touchpoint shape up utilitaraian poducst 2
(1) benchmark price and product, due to intensive use of third-party reviews and (2) prioritize search engine marketing (SEM)
cannibalistic cross-channel effects example
IN STORE SALES stops due thugh online salee
mixed mode journeys
combination of offline jurney and online jourey
example advertising spillover effect
ad impession zorgt voor more searchs
social sales effectiveness berekenen
number of sales from soical channels / total sales
website placement
digital media placement is the process of choosing and purchasing placements for ads on digital channels, such as websites and apps.
virality rate percentage berekenen
shares/impressions x 100
Unstructured Data: Concurrent Representation:
each facet respresetns a differen phenomena at the same time. a review represents a valence and a topic
amplification rate
shares/posts
2 examples of how to cluster images
Example 1: Clustering of social media images based on different dimensions (dichotomies)
- healthy / unhealhty
Example 2: McDonalds Social Data: Images are clustered (through visual processor) for further analysis.
- plaatjes lijken op elkaar
if u want to know the active engagement of your social media, you should use 3 etrics
conversation rate, amplification rate, applause rate
Tekst Data Analysis: classifiers
group or tag data into a defined category (by sentiment, emotion, topic, etc.). voorbeeld: super fast service = positive
Tekst Data Analysis Extractors
: retrieve pieces of information (like keywords, entities, phrases, numbers, etc.)
difference supervised and unsupervised learning
Supervised learning uses labeled datasets, whereas unsupervised learning uses unlabeled datasets. By “labeled” we mean that the data is already tagged with the right answer. unsupervised does itself
The Impact of Image on twitter and instagram 3
(Mere) presence of an image has a positive impact on customer engagement on Twitter
High-quality and professionally shot pictures lead to higher engagement on Instagram and Twitter
Presence of human face and image–text fit can lead to higher user engagement on Twitter but not on Instagram.
The Impact of Social Media Images on Consumer “Likes” results feature complexity and design complexity
Inverted u-shape between feature complexity and consumer liking
Regular u-shape relationship between design complexity and consumer liking.
textual data: multi-layered based tools look at 3 factors
1 Valence positivity-negativity
2 Subjectivity (Emotionally) to what extent the tekst is factual or subjective: emotion-opinion based
3 Polarity (Extremity) how strong the positivity in (1) is expressed
Textual Data Auditory Non-Verbal Communication: example
tempo: looooong, emphasis: happy!!!! ryth,: i, gues, ill, go
textual data: Visual Non-Verbal Communication: example
emoticns :), thumbs up emoi, dancing lady emotie
Textual Data: 3 Tactile Non-Verbal Communication: example
bodily/haptic touch: slap, punch, kiss, hugs. tactile eoji: people hlding hands
Topic Models waht do they do?
s extracts and classifies (clusters) the prominent TOPICS mentioned in a textual data (reviews, social media posts etc)
They are also used to segment-cluster the essential topics in Social Media, Customer Service Lines and Online Reviews.
Which factors do have the most impact on perceived helpfulness of a customer-user review?
Central/Latent (Content) factors such as: argument quality, reviwe valende
Ad group: Definition
An ad group contains one or more ads that share similar targets.
Ad Rank Score formule
A
(CPC Bid X 0,5) X (Quality Score X 0,4) X (Ad Extensions Score X 0,1)
why would a firm do a exact keyword match?
exact match gives the firm the most control over who sees their ad.
Google Quality Score 3 factors
Expected CTR: Ad Relevance: Landing Page Experience:
SEA: Effect on Customer Lifetime Value and why? (2)
Customers acquired through paid search has HIGHER Customer Life Time Value than other customers not-acquired by google paid search.
1 Extremely/Knowledgeable – Targeted
2 The opposite: Less tech-savy. I.E. Senior people with less online experience
why would a firm choose for borad match keyword option
atract more visitors, less time buildign keyword lists
SEA limitations 4
A
not effective for raising awareness in genral. 2. depending on potential customers to inititate search
restricted for cases who are new 4. SEO is potentially costly and less flexible
when is SEO most expensive and when least?
SEO is also associated with higher costs at the initial stages (website building, development, content creation etc) – but then when the website has its content & traffic these costs sharply decrease in further stages.
Perceived Reviewer Effort is highest for
> Highest for moderate arousal and utilitarian products.
: Search Stage consist of
all pre-purchase activities a customer is engaged with while searching for a product but also whilecomparing the products, obtaining and collecting information about products and services.
Rankbrain chooses rank for seo by 3 factors
Click through rate
Bounce rate
Dwell time
keywords and click behavior
click actvity after keyword search is low and heavilu concentrated on the organic list
searches of less popular keywords are associated with more clicks per search and a larger fraction of sponsored clicks–> customers more effort and closer to a purchase so more targetable for sponsored search adveising
Meta Path based approaches
combine content (item) filtering and collaborative (user) filtering
why would people download app?
best platform controlled mobile app variable
free:
paid
appearance in top chart
free: whole life cyccle
paid: early in life cycle
what is critical for the early stages of an mobile app?
gaining attention –> app platform users very critical
example drives for downloading app
platform:
user:
developper:
platform: featured lists, top apps charts
user:wom valence and volume
developper: updates, price/discutn
WOM apps
importatn for paid and free but more importatn for paid
logistic regression output waar op letten (2)
Sig values as in multiple regression shows which are significant
ii) Exp(B) –Odds Ratio shows us what is the most influential touchpoint
Y: outcome variable is metric we use
multiple linear regression
Y: outcome variable is discrete/nominal
logistic regression
Linear regression: output understanding 4 steps
1: significant
2: unstandardized beta: absolut impact of eacht touchpoint
3: standardized beta: to compare x variables: who has strongest impact
4 interaction effect
Unstandardized Beta coefficients example
: One more (increase) click on our Facebook ads is likely to increase our sales per person 17,683 € per year.
standardized beta coefficients example
Being a GOLD member of the Loyalty Program seems to have the STRONGEST impact on sales:
logistic regression: odds ratio tells us:
expB: Organic Search results are X 365 times more likely to convert (buy) in comparison to
