This document summarizes a presentation on new approaches to measuring brand imagery. It discusses limitations of current rating scale approaches, such as flat responses across brands and statements. A new approach called brand-anchored max-diff is proposed to address these issues. The presentation outlines several variations of brand-anchored max-diff, including those using positive and negative direct binary responses. It then summarizes a case study comparing rating scales to max-diff approaches. The max-diff methods showed better inter-brand discrimination, predictive validity, and eliminated scale usage bias. Methods using negative direct binary response performed best. The document concludes by discussing using analytics to reduce the number of required max-diff tasks.
Hen or egg – DoE-factors or -responses first?
In the context of design of experiments, many start directly with factor selection, although a definition of the target functions seems almost more important. Discussions on this topic resemble the "chicken or egg" problem that Popper once analyzed. In an effort to shed some light on the methodology, I have repurposed this QBD-DoE learning unit. How do you get started with a DoE? Feel free to write it in the comments.
Data mining for causal inference: Effect of recommendations on Amazon.comAmit Sharma
As an increasing amount of daily activity---ranging from what we purchase to who we talk---shifts to online platforms, it is only natural to ask how those platforms impact our behavior. Take, for instance, online recommendation systems: how much activity do recommendations actually cause over and above what would have happened in their absence? Without doing randomized experiments, which may be costly or infeasible, estimating the impact of such systems is non-trivial. In this talk, I will argue that careful data mining can help in answering relevant causal questions in a more general way than traditional observational approaches.
Taking recommender systems as an example domain, I will show that data mining can be used to augment a popular techniques such as instrumental variables, by searching for large and sudden shocks in time series data. Applying this method to system logs for Amazon's "People who bought this also bought" recommendations, we are able to analyze over 4,000 unique products that experience such shocks. This leads to a more accurate estimate of the impact of the recommender system: at least 75% of recommendation click-throughs would likely occur in their absence, questioning popular industry estimates based on observed click-through rates.
Finally, this shock-based approach can be generalized to derive a data-driven identification strategy for finding natural experiments in time series data. This method too reveals a similar overestimate for the impact of recommendation systems.
This is the presentation that was delivered at BCS-IRSG ECIR 2018. This work proposes an extension to the Complex Searcher Model (CSM), enabling us to model user interactions on a Search Engine Results Page (SERP). Grounded by Information Foraging Theory (IFT), we propose a new stopping decision point within the CSM. Results of simulations show that this new stopping decision point improves the realism of searcher models, and suggests that models and measures used in Information Retrieval research need to be u
Hen or egg – DoE-factors or -responses first?
In the context of design of experiments, many start directly with factor selection, although a definition of the target functions seems almost more important. Discussions on this topic resemble the "chicken or egg" problem that Popper once analyzed. In an effort to shed some light on the methodology, I have repurposed this QBD-DoE learning unit. How do you get started with a DoE? Feel free to write it in the comments.
Data mining for causal inference: Effect of recommendations on Amazon.comAmit Sharma
As an increasing amount of daily activity---ranging from what we purchase to who we talk---shifts to online platforms, it is only natural to ask how those platforms impact our behavior. Take, for instance, online recommendation systems: how much activity do recommendations actually cause over and above what would have happened in their absence? Without doing randomized experiments, which may be costly or infeasible, estimating the impact of such systems is non-trivial. In this talk, I will argue that careful data mining can help in answering relevant causal questions in a more general way than traditional observational approaches.
Taking recommender systems as an example domain, I will show that data mining can be used to augment a popular techniques such as instrumental variables, by searching for large and sudden shocks in time series data. Applying this method to system logs for Amazon's "People who bought this also bought" recommendations, we are able to analyze over 4,000 unique products that experience such shocks. This leads to a more accurate estimate of the impact of the recommender system: at least 75% of recommendation click-throughs would likely occur in their absence, questioning popular industry estimates based on observed click-through rates.
Finally, this shock-based approach can be generalized to derive a data-driven identification strategy for finding natural experiments in time series data. This method too reveals a similar overestimate for the impact of recommendation systems.
This is the presentation that was delivered at BCS-IRSG ECIR 2018. This work proposes an extension to the Complex Searcher Model (CSM), enabling us to model user interactions on a Search Engine Results Page (SERP). Grounded by Information Foraging Theory (IFT), we propose a new stopping decision point within the CSM. Results of simulations show that this new stopping decision point improves the realism of searcher models, and suggests that models and measures used in Information Retrieval research need to be u
Data Science Project on Brand Health Track.
o Primary Objective: To measure the Health of Leading Fashion Brands.
o Secondary Objective: To identify the key drivers that make a difference in Consumers Brand Choice and Purchase Behavior.
o Brands: WESTSIDE, SHOPPERS STOP, LIFESTYLE, PANTALOONS, CENTRAL, FBB.
o Questionnaire Preparation and Conduct Survey to collect Primary Data for analysis. (In Progress)
o Final Outcome: Represent Brand Health Data and Key Research findings using visualization and Shiny App.
Presentation delivered during the Introductory Course to Big Data in Agriculture. 29/11/2013, NCSR Demokritos, Athens, Greece.
The presentation is heavily based on the report titled “Big Data Now: 2012 Edition", by O’Reilly Media, Inc.
More info about the event: http://wiki.agroknow.gr/agroknow/index.php/Athens_Green_Hackathon_2013
[UPDATE] Udacity webinar on Recommendation SystemsAxel de Romblay
A 1h webinar on RecSys for the Udacity NanoDegree Program "How to become a Data Scientist" : https://in.udacity.com/course/data-scientist-nanodegree--nd025.
The link to the ipynb : https://www.kaggle.com/axelderomblay/udacity-workshop-on-recommendation-systems
ACM ICTIR 2019 Slides - Santa Clara, USAIadh Ounis
Talk entitled "Unifying Explicit and Implicit Feedback for Rating Prediction and Ranking Recommendation Tasks" presented at the ACM ICTIR 2019, Santa Clara. 2019.
Reference:
Jadidinejad, A. , Macdonald, C. and Ounis, I. (2019) Unifying Explicit and Implicit Feedback for Rating Prediction and Ranking Recommendation Tasks. In: 5th ACM SIGIR International Conference on the Theory of Information Retrieval, Santa Clara, CA, USA, 02-05 Oct 2019
URL: https://dl.acm.org/citation.cfm?id=3344225
A 1h webinar on RecSys for the Udacity NanoDegree Program "How to become a Data Scientist" : https://in.udacity.com/course/data-scientist-nanodegree--nd025
Business Applications of Predictive Modeling at Scale - KDD 2016 TutorialQiang Zhu
Predictive modeling is the art of building statistical models that forecast probabilities and trends of future events. It has broad applications in industry across different domains. Some popular examples include user intention predictions, lead scoring, churn analysis, etc. In this tutorial, we will focus on the best practice of predictive modeling in the big data era and its applications in industry, with motivating examples across a range of business tasks and relevance products. We will start with an overview of how predictive modeling helps power and drive various key business use cases. We will introduce the essential concepts and state of the art in building end-to-end predictive modeling solutions, and discuss the challenges, key technologies, and lessons learned from our practice, including case studies of LinkedIn feed relevance and a platform for email response prediction. Moreover, we will discuss some practical solutions of building predictive modeling platform to scale the modeling efforts for data scientists and analysts, along with an overview of popular tools and platforms used across the industry.
Business Applications of Predictive Modeling at ScaleSongtao Guo
Tutorial delivered in KDD 2016 San Francisco
Abstract
Predictive modeling is the art of building statistical models that forecast probabilities and trends of future events. It has broad applications in industry across different domains. Some popular examples include user intention predictions, lead scoring, churn analysis, etc. In this tutorial, we will focus on the best practice of predictive modeling in the big data era and its applications in industry, especially sales and marketing. We will start with an overview of how predictive modeling helps power and drive various key business use cases. We will introduce the essential concepts and state of the art in building end-to-end predictive modeling solutions, and discuss the challenges, key technologies, and lessons learned from our practice, followed by a case study. Moreover, we will discuss some practical solutions of building predictive modeling platform to scale the modeling efforts for data scientists and analysts, along with an overview of popular tools and platforms used across the industry.
Target Audience and Prerequisites
This tutorial is suitable for researchers, students, and practitioners of predictive modeling who are interested in the industry applications. Advanced techniques in data mining and statistical modeling are not required but some background in statistics and big data is expected.
IAB Rising Stars Study - January 30th 2015 - Topline ReportRomain Fonnier
L’IAB USA publie une étude intitulée «Rising Stars Ads and Brand Equity» et réalisée avec C3Research, qui compare l’efficacité des formats display de type «Rising Star» (voir archive) à celle des formats traditionnels («Universal Ad Package»).
Les conclusions chiffrées indiquent que :
- les formats Rising Star génèrent 4 fois plus de souvenir publicitaire brut que les formats traditionnels,
- ils engendrent 3 fois plus d’interaction avec la publicité (34% vs 11%),
- les effets des formats Rising Star sur l’évolution des indicateurs de capital de marque sont 30% supérieurs à ceux des formats UAP,
- les analyses eye-tracking montrent que 62% des impressions Rising Star sont regardées vs 38% des impressions des formats traditionnels,
- les impressions Rising Star sont regardées en moyenne pendant 4,5 secondes versus 0,9 secondes pour les formats UAP,
- elles génèrent une attention et un intérêt plus élevés, et sont également plus engageantes et plus persuasives,
- elles sont perçues comme moins ennuyeuses et provoquent moins l’envie de les éviter,
- une grande majorité des répondants estime que les formats Rising Star apportent plus de personnalité à la marque (65%), sont plus engageantes (64%), laissent plus de contrôle à l’internaute (60%), donnent davantage d’informations (60%) et sont plus divertissantes ou attirantes (58%).
Influencer marketing isn't just for big brands or consumer products anymore. In 2024, marketers face hurdles like escalating paid channel costs, diminishing organic reach, and building trust in their ideal customer accounts. This session offers practical ways to bring influencer marketing into your organization, to provide cost-effective access to niche audiences, countering budget constraints and rising CPMs. We'll discuss the impact of social algorithms on reach, the trust deficit in traditional advertising and how influencer partnerships offer genuine connections with audiences. Attendees will gain actionable insights to integrate influencer marketing into their strategies, leveraging influencers for impactful campaigns in both B2B and B2C environments. Join us to unlock the potential of influencers in navigating the evolving marketing landscape of 2024 and driving meaningful business growth.
Key Takeaways:
- Educate on the various types of influence we can use as marketers
- Establish the problems that make influencers a priority
- Walk through some practical tactics on HOW to run a program leveraging several of these influence channels
Most small businesses struggle to see marketing results. In this session, we will eliminate any confusion about what to do next, solving your marketing problems so your business can thrive. You’ll learn how to create a foundational marketing OS (operating system) based on neuroscience and backed by real-world results. You’ll be taught how to develop deep customer connections, and how to have your CRM dynamically segment and sell at any stage in the customer’s journey. By the end of the session, you’ll remove confusion and chaos and replace it with clarity and confidence for long-term marketing success.
Key Takeaways:
• Uncover the power of a foundational marketing system that dynamically communicates with prospects and customers on autopilot.
• Harness neuroscience and Tribal Alignment to transform your communication strategies, turning potential clients into fans and those fans into loyal customers.
• Discover the art of automated segmentation, pinpointing your most lucrative customers and identifying the optimal moments for successful conversions.
• Streamline your business with a content production plan that eliminates guesswork, wasted time, and money.
More Related Content
Similar to Macro Consulting - Sawtooth Conference 2013 Image MD Presentation
Data Science Project on Brand Health Track.
o Primary Objective: To measure the Health of Leading Fashion Brands.
o Secondary Objective: To identify the key drivers that make a difference in Consumers Brand Choice and Purchase Behavior.
o Brands: WESTSIDE, SHOPPERS STOP, LIFESTYLE, PANTALOONS, CENTRAL, FBB.
o Questionnaire Preparation and Conduct Survey to collect Primary Data for analysis. (In Progress)
o Final Outcome: Represent Brand Health Data and Key Research findings using visualization and Shiny App.
Presentation delivered during the Introductory Course to Big Data in Agriculture. 29/11/2013, NCSR Demokritos, Athens, Greece.
The presentation is heavily based on the report titled “Big Data Now: 2012 Edition", by O’Reilly Media, Inc.
More info about the event: http://wiki.agroknow.gr/agroknow/index.php/Athens_Green_Hackathon_2013
[UPDATE] Udacity webinar on Recommendation SystemsAxel de Romblay
A 1h webinar on RecSys for the Udacity NanoDegree Program "How to become a Data Scientist" : https://in.udacity.com/course/data-scientist-nanodegree--nd025.
The link to the ipynb : https://www.kaggle.com/axelderomblay/udacity-workshop-on-recommendation-systems
ACM ICTIR 2019 Slides - Santa Clara, USAIadh Ounis
Talk entitled "Unifying Explicit and Implicit Feedback for Rating Prediction and Ranking Recommendation Tasks" presented at the ACM ICTIR 2019, Santa Clara. 2019.
Reference:
Jadidinejad, A. , Macdonald, C. and Ounis, I. (2019) Unifying Explicit and Implicit Feedback for Rating Prediction and Ranking Recommendation Tasks. In: 5th ACM SIGIR International Conference on the Theory of Information Retrieval, Santa Clara, CA, USA, 02-05 Oct 2019
URL: https://dl.acm.org/citation.cfm?id=3344225
A 1h webinar on RecSys for the Udacity NanoDegree Program "How to become a Data Scientist" : https://in.udacity.com/course/data-scientist-nanodegree--nd025
Business Applications of Predictive Modeling at Scale - KDD 2016 TutorialQiang Zhu
Predictive modeling is the art of building statistical models that forecast probabilities and trends of future events. It has broad applications in industry across different domains. Some popular examples include user intention predictions, lead scoring, churn analysis, etc. In this tutorial, we will focus on the best practice of predictive modeling in the big data era and its applications in industry, with motivating examples across a range of business tasks and relevance products. We will start with an overview of how predictive modeling helps power and drive various key business use cases. We will introduce the essential concepts and state of the art in building end-to-end predictive modeling solutions, and discuss the challenges, key technologies, and lessons learned from our practice, including case studies of LinkedIn feed relevance and a platform for email response prediction. Moreover, we will discuss some practical solutions of building predictive modeling platform to scale the modeling efforts for data scientists and analysts, along with an overview of popular tools and platforms used across the industry.
Business Applications of Predictive Modeling at ScaleSongtao Guo
Tutorial delivered in KDD 2016 San Francisco
Abstract
Predictive modeling is the art of building statistical models that forecast probabilities and trends of future events. It has broad applications in industry across different domains. Some popular examples include user intention predictions, lead scoring, churn analysis, etc. In this tutorial, we will focus on the best practice of predictive modeling in the big data era and its applications in industry, especially sales and marketing. We will start with an overview of how predictive modeling helps power and drive various key business use cases. We will introduce the essential concepts and state of the art in building end-to-end predictive modeling solutions, and discuss the challenges, key technologies, and lessons learned from our practice, followed by a case study. Moreover, we will discuss some practical solutions of building predictive modeling platform to scale the modeling efforts for data scientists and analysts, along with an overview of popular tools and platforms used across the industry.
Target Audience and Prerequisites
This tutorial is suitable for researchers, students, and practitioners of predictive modeling who are interested in the industry applications. Advanced techniques in data mining and statistical modeling are not required but some background in statistics and big data is expected.
IAB Rising Stars Study - January 30th 2015 - Topline ReportRomain Fonnier
L’IAB USA publie une étude intitulée «Rising Stars Ads and Brand Equity» et réalisée avec C3Research, qui compare l’efficacité des formats display de type «Rising Star» (voir archive) à celle des formats traditionnels («Universal Ad Package»).
Les conclusions chiffrées indiquent que :
- les formats Rising Star génèrent 4 fois plus de souvenir publicitaire brut que les formats traditionnels,
- ils engendrent 3 fois plus d’interaction avec la publicité (34% vs 11%),
- les effets des formats Rising Star sur l’évolution des indicateurs de capital de marque sont 30% supérieurs à ceux des formats UAP,
- les analyses eye-tracking montrent que 62% des impressions Rising Star sont regardées vs 38% des impressions des formats traditionnels,
- les impressions Rising Star sont regardées en moyenne pendant 4,5 secondes versus 0,9 secondes pour les formats UAP,
- elles génèrent une attention et un intérêt plus élevés, et sont également plus engageantes et plus persuasives,
- elles sont perçues comme moins ennuyeuses et provoquent moins l’envie de les éviter,
- une grande majorité des répondants estime que les formats Rising Star apportent plus de personnalité à la marque (65%), sont plus engageantes (64%), laissent plus de contrôle à l’internaute (60%), donnent davantage d’informations (60%) et sont plus divertissantes ou attirantes (58%).
Similar to Macro Consulting - Sawtooth Conference 2013 Image MD Presentation (20)
Influencer marketing isn't just for big brands or consumer products anymore. In 2024, marketers face hurdles like escalating paid channel costs, diminishing organic reach, and building trust in their ideal customer accounts. This session offers practical ways to bring influencer marketing into your organization, to provide cost-effective access to niche audiences, countering budget constraints and rising CPMs. We'll discuss the impact of social algorithms on reach, the trust deficit in traditional advertising and how influencer partnerships offer genuine connections with audiences. Attendees will gain actionable insights to integrate influencer marketing into their strategies, leveraging influencers for impactful campaigns in both B2B and B2C environments. Join us to unlock the potential of influencers in navigating the evolving marketing landscape of 2024 and driving meaningful business growth.
Key Takeaways:
- Educate on the various types of influence we can use as marketers
- Establish the problems that make influencers a priority
- Walk through some practical tactics on HOW to run a program leveraging several of these influence channels
Most small businesses struggle to see marketing results. In this session, we will eliminate any confusion about what to do next, solving your marketing problems so your business can thrive. You’ll learn how to create a foundational marketing OS (operating system) based on neuroscience and backed by real-world results. You’ll be taught how to develop deep customer connections, and how to have your CRM dynamically segment and sell at any stage in the customer’s journey. By the end of the session, you’ll remove confusion and chaos and replace it with clarity and confidence for long-term marketing success.
Key Takeaways:
• Uncover the power of a foundational marketing system that dynamically communicates with prospects and customers on autopilot.
• Harness neuroscience and Tribal Alignment to transform your communication strategies, turning potential clients into fans and those fans into loyal customers.
• Discover the art of automated segmentation, pinpointing your most lucrative customers and identifying the optimal moments for successful conversions.
• Streamline your business with a content production plan that eliminates guesswork, wasted time, and money.
As the call for for skilled experts continues to develop, investing in quality education and education from a reputable https://www.safalta.com/online-digital-marketing/best-digital-marketing-institute-in-noida Digital advertising institute in Noida can lead to a a success career on this eve
First Things First: Building and Effective Marketing Strategy
Too many companies (and marketers) jump straight into activation planning without formalizing a marketing strategy. It may seem tedious, but analyzing the mindset of your targeted audiences and identifying the messaging points most likely to resonate with them is time well spent. That process is also a great opportunity for marketers to collaborate with sales leaders and account managers on a galvanized go-to-market approach. I’ll walk you through the methods and tools we use with our clients to ensure campaign success.
Key Takeaways:
-Recognize the critical role of strategy in marketing
-Learn our approach for building an actionable, effective marketing strategy
-Receive templates and guides for developing a marketing strategy
A.I. (artificial intelligence) platforms are popping up all the time, and many of them can and should be used to help grow your brand, increase your sales and decrease your marketing costs.In this presentation:We will review some of the best AI platforms that are available for you to use.We will interact with some of the platforms in real-time, so attendees can see how they work.We will also look at some current brands that are using AI to help them create marketing messages, saving them time and money in the process. Lastly, we will discuss the pros and cons of using AI in marketing & branding and have a lively conversation that includes comments from the audience.
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Attendees will learn about LLM platforms, like ChatGPT, and how they work, with preset examples and real time interactions with the platform. Attendees will learn about other AI platforms that are creating graphic design elements at the push of a button...pre-set examples and real-time interactions.Attendees will discuss the pros & cons of AI in marketing + branding and share their perspectives with one another. Attendees will learn about the cost savings and the time savings associated with using AI, should they choose to.
The Secret to Engaging Modern Consumers: Journey Mapping and Personalization
In today's digital landscape, understanding the customer's journey and delivering personalized experiences are paramount. This masterclass delves into the art of consumer journey mapping, a powerful technique that visualizes the entire customer experience across touchpoints. Attendees will learn how to create detailed journey maps, identify pain points, and uncover opportunities for optimization. The presentation also explores personalization strategies that leverage data and technology to tailor content, products, and experiences to individual customers. From real-time personalization to predictive analytics, attendees will gain insights into cutting-edge approaches that drive engagement and loyalty.
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Core Web Vitals SEO Workshop - improve your performance [pdf]Peter Mead
Core Web Vitals to improve your website performance for better SEO results with CWV.
CWV Topics include:
- Understanding the latest Core Web Vitals including the significance of LCP, INP and CLS + their impact on SEO
- Optimisation techniques from our experts on how to improve your CWV on platforms like WordPress and WP Engine
- The impact of user experience and SEO
[Google March 2024 Update] How To Thrive: Content, Link Building & SEOSearch Engine Journal
March 2024 disrupted the SEO industry. Websites were deindexed, and manual penalties were delivered—all to produce more helpful, more trustworthy search results.
How did your website fare?
Watch us as we delve into the seismic shifts brought about by Google's March 2024 updates and explore strategies to not just survive, but thrive in this dynamic digital landscape.
You’ll learn:
- How to create content that is valuable to users (not just search engines) using E-E-A-T.
- How to build links that can boost rankings and withstand algorithm updates.
- Best practices for content creation and link building so you can thrive during algorithm updates.
With Vince Ramos, we'll examine the implications of the latest algorithm changes on content creation, link building, and SEO practices, and offer actionable insights from businesses like yours that have remained steadfast amidst the volatility.
Using real-life case studies, we’ll also show you the effectiveness of manual link building techniques and person-first content strategies.
Whether you're a seasoned SEO professional, a budding content creator, or anyone in between, this webinar will help you weather the changes in Google's algorithms and capitalize on them for sustained success.
Check out this webinar and unlock the secrets to thriving in the new Google era.
Mastering Local SEO for Service Businesses in the AI Era is tailored specifically for local service providers like plumbers, dentists, and others seeking to dominate their local search landscape. This session delves into leveraging AI advancements to enhance your online visibility and search rankings through the Content Factory model, designed for creating high-impact, SEO-driven content. Discover the Dollar-a-Day advertising strategy, a cost-effective approach to boost your local SEO efforts and attract more customers with minimal investment. Gain practical insights on optimizing your online presence to meet the specific needs of local service seekers, ensuring your business not only appears but stands out in local searches. This concise, action-oriented workshop is your roadmap to navigating the complexities of digital marketing in the AI age, driving more leads, conversions, and ultimately, success for your local service business.
Key Takeaways:
Embrace AI for Local SEO: Learn to harness the power of AI technologies to optimize your website and content for local search. Understand the pivotal role AI plays in analyzing search trends and consumer behavior, enabling you to tailor your SEO strategies to meet the specific demands of your target local audience. Leverage the Content Factory Model: Discover the step-by-step process of creating SEO-optimized content at scale. This approach ensures a steady stream of high-quality content that engages local customers and boosts your search rankings. Get an action guide on implementing this model, complete with templates and scheduling strategies to maintain a consistent online presence. Maximize ROI with Dollar-a-Day Advertising: Dive into the cost-effective Dollar-a-Day advertising strategy that amplifies your visibility in local searches without breaking the bank. Learn how to strategically allocate your budget across platforms to target potential local customers effectively. The session includes an action guide on setting up, monitoring, and optimizing your ad campaigns to ensure maximum impact with minimal investment.
SEO as the Backbone of Digital MarketingFelipe Bazon
In this talk Felipe Bazon will share how him and his team at Hedgehog Digital share our journey of making C-Levels alike, specially CMOS realize that SEO is the backbone of digital marketing by showing how SEO can contribute to brand awareness, reputation and authority and above all how to use SEO to create more robust global marketing strategies.
In this presentation, Danny Leibrandt explains the impact of AI on SEO and what Google has been doing about it. Learn how to take your SEO game to the next level and win over Google with his new strategy anyone can use. Get actionable steps to rank your name, your business, and your clients on Google - the right way.
Key Takeaways:
1. Real content is king
2. Find ways to show EEAT
3. Repurpose across all platforms
Mastering Local SEO for Service Businesses in the AI Era is tailored specifically for local service providers like plumbers, dentists, and others seeking to dominate their local search landscape. This session delves into leveraging AI advancements to enhance your online visibility and search rankings through the Content Factory model, designed for creating high-impact, SEO-driven content. Discover the Dollar-a-Day advertising strategy, a cost-effective approach to boost your local SEO efforts and attract more customers with minimal investment. Gain practical insights on optimizing your online presence to meet the specific needs of local service seekers, ensuring your business not only appears but stands out in local searches. This concise, action-oriented workshop is your roadmap to navigating the complexities of digital marketing in the AI age, driving more leads, conversions, and ultimately, success for your local service business.
Key Takeaways:
Embrace AI for Local SEO: Learn to harness the power of AI technologies to optimize your website and content for local search. Understand the pivotal role AI plays in analyzing search trends and consumer behavior, enabling you to tailor your SEO strategies to meet the specific demands of your target local audience. Leverage the Content Factory Model: Discover the step-by-step process of creating SEO-optimized content at scale. This approach ensures a steady stream of high-quality content that engages local customers and boosts your search rankings. Get an action guide on implementing this model, complete with templates and scheduling strategies to maintain a consistent online presence. Maximize ROI with Dollar-a-Day Advertising: Dive into the cost-effective Dollar-a-Day advertising strategy that amplifies your visibility in local searches without breaking the bank. Learn how to strategically allocate your budget across platforms to target potential local customers effectively. The session includes an action guide on setting up, monitoring, and optimizing your ad campaigns to ensure maximum impact with minimal investment.
In this presentation, Danny Leibrandt explains the impact of AI on SEO and what Google has been doing about it. Learn how to take your SEO game to the next level and win over Google with his new strategy anyone can use. Get actionable steps to rank your name, your business, and your clients on Google - the right way.
Key Takeaways:
1. Real content is king
2. Find ways to show EEAT
3. Repurpose across all platforms
3. THANK
YOU
www.macroinc.com
Ricky Odello, Survey Sampling International
Tom Eagle, Eagle Analytics of California
KirillZaitsev, MACRO Consulting, Inc.
Keith Chrzan, Sawtooth Software, Inc.
Christine Lafontaine, MACRO Consulting, Inc.
MACROConsulting, Inc.
3
4. AGENDA
Brand Imagery Measurement
Introduction
• Current Approach
• Issues
www.macroinc.com
New Approach
Case Study
• Research Objectives
• Research Methodology
• Summary of Findings
MACROConsulting, Inc.
MACROConsulting, Inc.
4
6. Introduction
Current Approach
• Rating Scales
• Each brand is rated
independently on
each statement in
an image battery,
eg, 10 point rating
scale.
www.macroinc.com
MACROConsulting, Inc.
6
7. Introduction
Current Approach Issues
1
2
3
4
5
•
•
•
•
Flat Responses Across Statements
Flat Responses Across Brands
Scale Usage Bias
Brand Halo
Ratings Scales
6
7
8
Resulting data are typically
non-discriminating and
highly correlated.
9
10
www.macroinc.com
MACROConsulting, Inc.
7
10. New Approach
Brand-Anchored Max/Diff with Dual Response
Dual Response Max/Diff allows for a zero point in Max/Diff utilities,
making comparisons across studies (and brands) feasible.
www.macroinc.com
MACROConsulting, Inc.
10
11. New Approach
Modified Brand-Anchored Max/Diff
Max/Diff takes longer than ratings scales. Modified brand-anchored Max/Diff
hopes to decrease the interview time of the Max/Diff Tasks.
www.macroinc.com
MACROConsulting, Inc.
11
12. New Approach
Animated Modified Brand-Anchored Max/Diff
Animated Modified Brand-Anchored Max/Diff hopes
to hold the respondent’s attention longer than traditional Max/Diff.
www.macroinc.com
MACROConsulting, Inc.
12
13. New Approach
Direct Binary Response- Positive DBR
Dual Response Max/Diff ALLOWS FOR A
ZERO POINTin Max/Diff utilities, MAKING
COMPARISONS ACROSS STUDIES
feasible.
Direct Binary Response is a MORE TIME-EFFICIENT way
to collect dual-response data.
However, Dual Response Max/Diff has been shown to
RE-INTRODUCE SOME SCALE USAGE BIAS.
www.macroinc.com
MACROConsulting, Inc.
13
14. New Approach
Dual Direct Binary Response- Negative DBR
By ADDING A SECOND, NEGATIVE DIRECT
BINARY RESPONSE QUESTION, we hope to
REMOVE or MINIMIZE scale usage bias.
As a FURTHER ATTEMPT to minimize scale use bias,
half of respondents will be required to SELECT AS MANY
NEGATIVE ATTRIBUTES AS POSITIVE.
www.macroinc.com
MACROConsulting, Inc.
14
15. Summary of New Approach
AA nm a ae e dM oo dfiife e dBB a a n d a a n c h o e e dM a a xDDfiff fSS c ailnn g w i t h
ni im t t d M di i d
r r nd- - nchor r d M x/ / i
cal i g
wP t h iP i v e t av e a ne g a te v e t Dv ee D t r B cn aB yn R r y p o n s e n A e B A M B R )
i os tosi i nd N d N iga i ir c i e i t ri a es Respo ( s M
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16. New Approach
Analytics-Derived Parsimony
2
Latent Class Choice Models
•
•
With Large Sample
With Covariates
Hierarchical Bayes
•
•
Covariates in upper model
Adjusted priors
The goal of the above analytic approaches is to minimize the number of Max/Diff tasks each
respondent must complete and still estimate disaggregate utilities with acceptable accuracy.
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17. AGENDA
Brand Imagery Measurement
Case Study
• Research Objectives
• Research Methodology
• Summary of Findings
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18. Research Objectives
•
Compare two approaches to brand
imagery measurement, ratings scales
and max/diff, in terms of:
-
•
Explore alternative methods of
estimating max/diff utilities most
accurately and most efficiently:
-
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Inter-brand discrimination
Inter-item discrimination
Predictive validity
Standard HB
HB with positive Direct Binary Response
HB with positive DBR and unconstrained
negative DBR
HB with positive DBR and constrained
negative DBR
Latent Class Choice
Use of covariates
Tuned priors
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19. Research Methodology
Online Survey:
• Two cells
- Rating Scales (n=436)
- Max/Diff (n=2,605)
• Three brands
• 12 items
• Questionnaire:
- Brand image measurement
- Three dependent variables
Item top 3 rank-order
Brand purchase likelihood
Brand forced-choice preference
- Demographics
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20. Summary of Findings
In general, AMBAMBR is superior to ratings scales:
-
Better inter-item discrimination
Better predictive validity
Fewer unacceptable respondents
Elimination of both brand halo and scale usage bias
Of the AMBAMBR methods tested, the two methods which
included negative DBR were superior:
- Positive DBR reinserts brand halo into the data
- Positive DBR has slightly weaker inter-item discrimination than either
Negative DBR
AMBAMBR takes longer to administer and has higher
incompletion rates
Task set reduction could not be fully explored with these data
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24. Inter-Item Discrimination Greatest for Negative DBR
Average number of statistically significant differences across 12 items, within brand*
Ratings
No DBR
Positive DBR
Unconstrained
Negative DBR
Constrained
Negative DBR
1.75
4.46
3.90
4.30
4.68
NEW BRAND
0
4.28
3.16
4.25
4.50
BRAND#2
1
4.69
3.78
4.48
4.70
BRAND#1
* 10 random draws of n=436 were pulled for all data sets except Ratings
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25. Predictive Validity of AMBAMBR Superior to Rating Scales
Hit Rates for Top 3 Items Ranking
Random
Numbers
Ratings
No DBR
Positive DBR
1 OF 1
8%
14%
27%
28%
27%
26%
(1 OR 2) OF 2
32%
30%
62%
64%
62%
65%
(1, 2 OR 3) OF 3
61%
51%
86%
87%
86%
88%
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Unconstrained Constrained
Negative DBR Negative DBR
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26. AMBAMBR Yielded More Valid Completes
Invalid Completes
Max/Diff
Ratings
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4%
32%
32%
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27. Brand Halo Was Measured Using Confirmatory Factor Analysis
If brand halo exists,
halo latent will positively
influence scores on all items
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29. Scale Usage Bias Was Measured Using Confirmatory Factor Analysis
Brand halo drives scores
within brand. Scale
usage bias drives scores
independent of brand.
If scale usage bias
exists, the scale usage
latent should load
positively on all items
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30. Only Ratings Reflect Strong Scale Usage Bias
Scale Usage
Latent
Ratings
No DBR
Positive DBR
Unconstrained
Negative DBR
Constrained
Negative DBR
NUMBER OF
NEGATIVE LOADINGS
0
14
5
10
15
NUMBER OF
STATISTICALLY
SIGNIFICANT
LOADINGS
35
30
28
32
29
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31. AMBAMBR Superior But Slower
AMBAMBR Has Higher Dropout Rates
RATINGS
AMBAMBR
TOTAL INTERVIEW LENGTH
9.7 MINUTES
15.8 MINUTES
BRAND IMAGE MEASUREMENT
1.7 MINUTES
6 MINUTES
RATINGS
AMBAMBR
9%
31%
INCOMPLETION RATE
Can We Reduce the Number of
Max/Diff Tasks to Shorten Interview
Length and Decrease Dropout Rates?
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32. HB Models May Perform Slightly Better Than LC With Full Task Sets
But All Perform Well
U N C O N S T R A I N E D Negative DBR
C O N S T R A I N E D Negative DBR
8 Tasks
HB
LC
4 Tasks
HB
LC
2 Tasks
HB
LC
8 Tasks
HB
LC
4 Tasks
HB
LC
2 Tasks
HB
LC
1 OF 1
27%
19%
21%
20%
20%
19%
26%
21%
24%
21%
22%
22%
(1 OR 2) OF 2
62%
54%
59%
57%
58%
56%
65%
61%
61%
59%
59%
56%
(1, 2 OR 3) OF 3 86%
81%
85%
82%
82%
83%
88%
84%
86%
84%
85%
82%
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33. All HB and LC Models Perform Very Well - Perhaps Too Well
• Hit rates seem relatively unaffected by:
−
−
−
−
−
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Number of tasks
Number of latent classes
Tuned priors
Covariates
Sample size
What’s
Going On?
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34. Perhaps These Data Have Little Heterogeneity
• Category is not emotionally engaging
• Brands are not differentiated
− Commodity-like category
− No polarizing brands, eg, Microsoft, Apple or Donald
Trump
− Brands with new technologies not yet established
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35. Aggregate Model Works as Well as Disaggregate
U N C O N S T R A I N E D Negative DBR
Random
HB
8 Tasks
N=1,324
HB
2 Tasks
N=105
HB
2 Tasks
Constantutils
N=105
1 OF 1
8%
27%
22%
25%
(1 OR 2) OF 2
32%
62%
59%
61%
(1, 2 OR 3) OF 3
61%
86%
82%
82%
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36. Summary and Implications
•
The forms of Max/Diff referred to here as AMBAMBR are superior to rating
scales for measuring brand imagery:
-
Better inter-item discrimination
Better predictive validity
Elimination of brand halo
Elimination of scale usage bias
Fewer invalid completes
•
Positive DBR alone reintroduces brand halo
•
Positive DBR must be combined with some form of negative DBR
•
For comparability across brands and time:
-
•
Raw utils must be used rather than rescaled utils
Some form of dual response must be used
AMBAMBR takes longer to administer and has higher incompletion rates
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37. Further Research
• Can we reduce the number of tasks when brands are
heterogeneously perceived?
• How many brands and statements can realistically by
accommodated?
• Is constrained or unconstrained negative DBR superior?
• How would traditional dual response format affect these results?
• Is there a better way to evaluate utility performance?
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38. And The BIG Question:
• Is there a shorter name for this technique
than:
A n i m a t e d Mo d i f i e d
B r a n d - a n c h o r e d Ma x / D i ff S c a l i n g
with Positive and Negative
Direct Binary Response?
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