mops at Universität Münster

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5 ways to optimize the performance of marketing action 

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5 tools/approaches to answer the MROI question

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Explain the A/B testing
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Exemplary flashcards for mops at the Universität Münster on StudySmarter:

Contrast the Pros and Cons of the AB/ testing

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Explain the Reach-Cost-Quality

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Contrast the Pros and Cons of the Reach-Cost-Quality

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Explain the Marketing-Mix-Models
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Contrast the Pros and Cons of the Marketing-Mix-Models

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Congrats the Pros and Cons of the multi-touch-attribution (MTA)

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Different approaches to determine attribution from simple to complex 

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Limitations of the current model along 5 dimensions
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What are aligned MMM/MTA models

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Exemplary flashcards for mops at the Universität Münster on StudySmarter:

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5 ways to optimize the performance of marketing action 
1) Strategic resource allocation
-> allocate the marketing budget across brands, market and products
2) Relevant messaging
-> select the best performing content/creative/message for a target group or indiviual
3) Effective instrument mix
-> optimize spend allocation towards the highest performing instruments and channels
-> how are they mixed together
4) Excellent execution
-> running tv campaigns efficiently
5) Smart sourcing
-> ensure most efficient sourcing of content, media, tools and services

-> Marketing performance is a combination of all!

mops

5 tools/approaches to answer the MROI question
  1. A/B testing
  2. Read-Cost-quality (RCQ) [pragmatic heuristic]
  3. Consumer survey
  4. Marketing/media-Mix-Model (MMM)
  5. Multi-Touch-Attribution (MTA)

mops

Explain the A/B testing
Tests allow to understand incremental impact via a test and control enviroment

Cycle:
  1. Set our goal
  2. Decide what to test
  3. Create variations
  4. Run test
  5. Analyze results
  6. Repeat

most frequently used approach to compare different instruments
expensive on mass media

mops

Contrast the Pros and Cons of the AB/ testing
Great for:
  • testing all marketing parameters incl. content/creative/messages
  • agile test & learn approaches to continuously improve performance
  • proving superior MROI in a controlled environment

Limitations that remain:
  • only relative superiority of options
    • no absolute MROI assessment
    • difficult to derive
  • complex decisions require large series of A/B tests
  • only applicable to tactical choices
    • limited guidance on budget sizing and overall mix/strategic priorities

mops

Explain the Reach-Cost-Quality

  • measure on how many people i could reach
  • how much did it cost
  • quality of reading

derive a score: Reach/(cost * quality)

mops

Contrast the Pros and Cons of the Reach-Cost-Quality
Great for
  • optimize marketing mix based on "pples test apples" comparison

Limitations that remain
  • no fully objective/analytical approach
    • subject to scoring bias for quality does not give euro-for-euro
  • hard to automate
    • "manual" work

mops

Explain the Marketing-Mix-Models
helps to understand the incremental impact of all marketing instruments
  • linking advertising to scales

mops

Contrast the Pros and Cons of the Marketing-Mix-Models

Great for:
  • right-size marketing spending (media and beyond)
  • trade-off investment types (e.g. digital vs. offline)
  • support annual budgeting and media guideline setting

Limitations that remain
  • Lack of granularity and "in-campaign" view
  • Backward looking, limited use for new products, instruments, messages, etc.
  • hard to capautre impact on creative/message

mops

Congrats the Pros and Cons of the multi-touch-attribution (MTA)
Great for:
  • Understand the digital customer journey 
  • Overcome „last click wins“ bias in digital ROI assessment 
  • Granular and near-time steering of digital spend 
Limitations that remain
  • Focus on attribution not incrementality - digital sales 100% attributed to digital channels
  • Tends to overestimate the impact of digital 
  • Hard to capture offline touchpoints, offline sales and long term impact 

mops

Different approaches to determine attribution from simple to complex 
  • Rule-based attribution 
    • Last touch, linear
    • First touch, position-based
    • Time decay, custom attribution
  • Algorithmic attribution
    • Data-driven multitouch attribution

mops

Limitations of the current model along 5 dimensions
  1. Backward looking
    • No real-time feedback for in-campaign optimizations for omni-channel ROI
  2. Creative and message ROI not understood 
    • Focus on media spend only while largest impact comes from right message  and good creative
  3. Lack of granularity
    • Aggregate data sets per media channel-with granular information only within digital silo
  4. Short-termism
    • Focus on bottom of the funnel (sales) disregarding the relevance of brand effects
  5. Insights to action gap
    • Lack of adoption of ROI analytics insights for actual decision-making

mops

What are aligned MMM/MTA models
  • They only partially address the short-comings of each model
  • Integrating both models adds incrementality to MTA but only allows for sequential optimization 
What it is great for:
  • Adding incrementality to MTA
  • Increasing (digital) granularity of the omnichannel MMM
  • Combine strategic and tactical optimization
Limitations that remain
  • Still 2 different models with only sequential optimization 
  • Still lack of upper funnel and content/creative view
  • Brands complain about complex implementation 

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MOOC at

Université Paris Sud (Paris XI)

Molek at

ZHAW - Zürcher Hochschule für Angewandte Wissenschaften

Mofu at

Hochschule Fresenius

Modul 3.3 at

Fachhochschule für öffentliche Verwaltung, Polizei und Rechtspflege

Modul 2 at

Charité - Universitätsmedizin Berlin

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