Cognitive Biases for Marketers
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Examples of ten cognitive biases in the marketing world that you can apply to your own work. Presented at the AMA Houston conference in September 2016.
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This document discusses strategies for controlling common cognitive biases known as "dramatic instincts" that can distort perceptions of facts. It provides tips for countering 10 specific biases: the negativity instinct, fear instinct, size instinct, destiny instinct, single perspective instinct, blame instinct, urgency instinct, straight line instinct, generalization instinct, and gap instinct. The strategies emphasize questioning dramatic stories, distinguishing levels from trends of change, considering multiple perspectives, and resisting overgeneralization.
Don't be Biased | TechSparks 2018
Human biases, behavioural economics, and cognitive psychology — why they matter and how we use them in tech.
GuideStar Webinar (04/30/13) – Major Gifts for Small Shops
Learn how to do major gift fundraising for the first time and how to integrate individual donations into your annual fund. We will explore the who, what, when, where, and why of fundraising from individuals as well as discuss how to get a first meeting, cultivate and solicit gifts from individuals, and deal with "no's."
Presenters: Amy Eisenstein, CFRE, Tri Point Fundraising, and Diana Hand, Senior Marketing Manager, GuideStar
Ed1
This document provides information about an introduction to economic development lecture. It includes the lecturer's contact information, as well as brief introductions to topics that will be covered such as why some countries are rich while others are poor, historical changes in global population, life expectancy, income, and the concept of globalization. Charts and figures are referenced to illustrate these concepts.
Personal Essay For College Application
The document provides instructions for creating an account and submitting a request on the website HelpWriting.net in order to have an assignment written. It involves a 5-step process: 1) Create an account with an email and password; 2) Complete a form with assignment details and deadline; 3) Review bids from writers and choose one; 4) Receive the paper and authorize payment if satisfied; 5) Request revisions if needed, and the website guarantees original, high-quality work or a refund.
Portfolio Veronika Kistamas (final)
This is my portfolio book that I presented at my Final Review at the Academy of Art University in San Francisco. All projects were created for school.
Common Ground Presentation - Istanbul
A presentation delivered at the Common Ground conference in Istanbul 26 February 2015 organised by Myra and a range of Turkish NGOs, and featuring the agencies in http://www.donotsmile.com
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GWC14: PlayBenefit - Gamification and the health revolution (gHealth workshop)
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Are You Really Doing Effective Prevention - from IADDA Conference 2014
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John Haydon- Valley GivesTelling better stories with facebook and instagram
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More from Annie Pettit, Research Methodologist
AI and Voice Search and Chatbots, oh my!
Annie Pettit's AI presentation at the 2018 annual Travel and Tourism Research Association (TTRA) conference in Miami. Sharing results from a Sklar Wilton white paper on Canadian perceptions of AI, plus applications of AI in marketing research.
Links to videos I showed:
@SklarWilton #AI white paper on what Canadians think about #AI, #VoiceAssistants, and #Chatbots.
https://www.sklarwilton.com/wp-content/uploads/2017/12/Sklar-Wilton-Canadian-Artificial-Intelligence-Paper-2017.pdf
Joy Buolamwini of M.I.T.’s Media Lab shows how facial recognition technology has trouble recognizing dark faces.
https://www.youtube.com/watch?v=TWWsW1w-BVo
Google can now make #AI phone calls that are virtually indistinguishable from human beings.
https://ai.googleblog.com/2018/05/duplex-ai-system-for-natural-conversation.html
#AI can write newspaper articles about anything.
http://articlecreator.fullcontentrss.com/index.php
#AI can create humour that people actually laugh at.
https://www.youtube.com/watch?v=Vhe-JOP7PCs
#AI can read your mind.
https://www.youtube.com/watch?v=RuUSc53Xpeg
mindread
#AI, #Chatbots, and #VoiceAssistants are already running #questionnaires.
https://www.messenger.com/t/202671200242510/?messaging_source=source%3Apages%3Amessage_shortlink
Scientific rigour is worth melting for MRS Annual Conference 2016
Scientific rigour is worth melting for MRS Annual Conference 2016Annie Pettit, Research Methodologist
In the first of a two-part session, four research professionals throw caution to the wind and fight for their passionately held beliefs about the way the insight world works. This is the session for those who want to hear the uncensored, unshackled and revolutionary voice of research.
I wish I had kept track of every time a conference speaker said they didn't understand the statistics they were referring to but if anyone had a question, they could find someone to answer it.
I wish I had kept track of every presenter whose 20 slides consisted of 20 pictures.
I wish it was even possible to count the number of infographics floating around the interweebs spewing countless unsubstantiated and out-of-context percentages with multiple decimal places.
In this presentation, I will plead with the audience to reconsider how they communicate to their clients about research, and how they present that research to various audiences.
How to Turn Big Data into Actionable Data IIeX Europe 2016
Of all the datasets that could be delivered to your desk, the most difficult one to work with might be that big dataset. Besides its massive size, it’s exponential growth even as you work on it, and the variety of data types present, big data presents many issues that make it difficult to turn data into action. In this presentation, you will learn how to take thousands of variables and billions of records and turn them into useable and actionable results, just as you would with any traditional research dataset.
NewMR 2016 presents: 9 Big Applications of Big Data
People are sometimes intimidated by big data because it seems overwhelming and they’re much more familiar with using statistics on survey data or analyzing opinions from focus group data. But here are nine examples from companies like Netflix, Ceasars Entertainment, Walmart, eBay, and UPS, that could have conducted survey or focus group research have instead used big data to accomplish big things.
Creating Honesty: The effect of requesting telephone numbers and reporting on...
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Previous research has suggested that people who are willing to provide their telephone numbers may be more likely to provide good quality data. This study examined whether asking people for their phone number 1) at the beginning of a survey or or 2) at the end of a survey affects the results. And yes, it matters.Blasting 10 Big Data Myths with 10 Panel Data Examples
Theory is nice but data is heaven. Most market researchers have heard a lot of theory about big data, but few have seen the data and worked with it themselves. And we all know that the best way to truly understand and internalise something is to see the raw data for yourself. In this presentation, we'll blast ten big data myths using stories that many researchers can actually relate to - survey panel data. With millions of panellists, millions of profiles, millions of survey clicks, and millions of incentives, market researchers have been sitting on pretty big data for nearly 20 years. See how easy it is for trained scientists like yourselves to learn some SAS, R, or SQL, and dig into that big data on your own.
How non-native English speakers respond to English surveys
We like to think that everyone answering our surveys is perfectly fluent in English but let's be realistic. About 10% of Americans have difficulty reading/writing in English because it is not their native language. And when we apply standard techniques to identify which survey takers provide good data and which are simply giving random answers, we are often making the mistake of applying measurements that all require high level language skills.
Survey analysis in a nutshell with Jeffrey Henning
Jeffrey Henning of Researchscape International presented on survey analysis and best practices for analyzing survey data. He discussed the importance of considering analysis before designing and administering a survey to ensure the right questions are asked to answer the main research question. He also emphasized reviewing each question individually and looking at relationships between questions before analyzing responses. Finally, Henning stressed telling stories with the data rather than just presenting analysis, and leaving the data behind to focus on the insights and meaning.
VUE-JUNE-2015
The document is the June 2015 issue of Vue Magazine, which is published by the Marketing Research and Intelligence Association. It includes articles on topics like big data, data mining, competitive intelligence, and social media. It also provides information on the MRIA 2015 conference, new CMRPs, and chapters.
VUE-JAN-FEB-2015
This document is the January/February 2015 issue of Vue Magazine, which is published by the Marketing Research and Intelligence Association (MRIA) 10 times per year. It contains articles, columns, and other content related to marketing research. The issue includes a special feature on staying ahead of industry trends, articles on qualitative research experiences in France and the relationship between lobotomies and surveys, as well as industry news, book reviews, columns, and information on upcoming MRIA events and courses.
VUE-MAY-2013
This document is the May 2013 issue of Vue Magazine, which is published by the Marketing Research and Intelligence Association (MRIA) 10 times per year. The issue features articles on ethics in research, structural collaboration with consumers, and a summary of the 2013 MRIA national conference from the perspective of client-side researchers. It also includes industry news, columns, and information about upcoming MRIA events. The conference issue serves to inform MRIA members about current topics and issues in marketing research.
9 Tips For Creating a Great Numeric Question
As easy as it seems, there are many ways a numeric question can go wrong. Follow along for tips on how to avoid 9 problems.
How to seamlessly integrate data quality measures into your questionnaire
How to seamlessly integrate data quality measures into your questionnaireAnnie Pettit, Research Methodologist
For the most part, people who answer marketing research surveys want and try to do a good job. However, sometimes respondents want to get through a survey as quick as possible in order to earn the incentive and move to the next task.
- Learn the various types of data quality questions you can use, beyond speeding and straightlining.
- How to fit them into your questionnaire with minimal impact on responders.
- And most importantly, how to use the data quality questions effectively so that you don't accidentally exclude data from honest respondents.The Rise and Fall and Rise of Social Media Research #IIEXap14
Just a few years ago, social media research was hailed as the panacea of all marketing research. The ridiculous quantities of brand opinions and opinionators available in social media would mean that focus groups would die, surveys would die, and all research questions would have instant answers. Fast forward to today and surveys continue to thrive. Learn why social media research didn’t hold up to expectations and why it’s finally breaking through. Presented at #IIEXap14 #IIEX
How to Create Census Sampling Targets for Free Using Data Ferret
How to Create Census Sampling Targets for Free Using Data FerretAnnie Pettit, Research Methodologist
Researchers know we're supposed to sample people in the proper proportions but how do we know what those proportions are? In this webinar, I will demonstrate how to use census data to determine what your sample should really look like in terms of variables like age, gender, region and .educationA Tale of Two Surveys: How using real words instead of mumbo jumbo affects su...
A Tale of Two Surveys: How using real words instead of mumbo jumbo affects su...Annie Pettit, Research Methodologist
Surveys have a lot of tradition and norms behind them. And a lot of templates. Many of these templates were written many years ago when formal language made a lot more sense. Today, people expect casual and friendly language everywhere including from brands and companies. This presentation shows what happens to data quality and survey results when real language, not Charles Dickens language, is used.How people talk about us behind our backs
The document discusses how people perceive surveys and provides suggestions for improving surveys. It finds that respondents feel surveys are too long, distrust incentives and data collection, and feel screened out too late. It recommends being transparent about data use, explaining screening reasons, using casual language to avoid boredom, and addressing respondents' concerns to improve perceptions of surveys.
Effects of splitting long surveys into two
The document summarizes research into the effects of splitting long surveys into two shorter surveys. It finds that data quality is maintained or improved with shorter surveys, as respondents make fewer errors and provide more detailed open-ended responses. Results from different question sets are largely equivalent between survey lengths. Respondent satisfaction may also be higher for shorter surveys, as indicated by more positive survey comments. While not a definitive solution, splitting long surveys appears to address issues like respondent fatigue without harming data quality or equivalence.
Using social media data for new product development
1) The document discusses using social media for new product development by collecting ideas and suggestions from online posts.
2) It outlines a process of iteratively searching social media to find posts about new product ideas, wishes, and things people want made or improved.
3) The sources of data have become more diverse over time but may still underrepresent certain groups, and the suggestions tend to focus on generic consumer needs, electronics, and popular brands.
Men are from Mars: Gender differences in word choices in social media
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Perhaps we are all speaking English but men and women do it just a little bit differently. Find out what words are used more often by men or women and see how you fit the stereotype.More from Annie Pettit, Research Methodologist (20)
Scientific rigour is worth melting for MRS Annual Conference 2016
Scientific rigour is worth melting for MRS Annual Conference 2016
How to Turn Big Data into Actionable Data IIeX Europe 2016
How to Turn Big Data into Actionable Data IIeX Europe 2016
NewMR 2016 presents: 9 Big Applications of Big Data
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Creating Honesty: The effect of requesting telephone numbers and reporting on...
Creating Honesty: The effect of requesting telephone numbers and reporting on...
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Blasting 10 Big Data Myths with 10 Panel Data Examples
How non-native English speakers respond to English surveys
How non-native English speakers respond to English surveys
Survey analysis in a nutshell with Jeffrey Henning
Survey analysis in a nutshell with Jeffrey Henning
How to seamlessly integrate data quality measures into your questionnaire
How to seamlessly integrate data quality measures into your questionnaire
The Rise and Fall and Rise of Social Media Research #IIEXap14
The Rise and Fall and Rise of Social Media Research #IIEXap14
How to Create Census Sampling Targets for Free Using Data Ferret
How to Create Census Sampling Targets for Free Using Data Ferret
A Tale of Two Surveys: How using real words instead of mumbo jumbo affects su...
A Tale of Two Surveys: How using real words instead of mumbo jumbo affects su...
Using social media data for new product development
Using social media data for new product development
Men are from Mars: Gender differences in word choices in social media
Men are from Mars: Gender differences in word choices in social media
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5. Promotion with less investment
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1. Services offered with Affordable cost
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Digital Marketing Services | Techvolt Software :
Digital Marketing is a latest method of Marketing techniques widely used across the Globe. Digital Marketing is an online marketing technique and methods used for all products and services through Search Engine and Social media advertisements. Previously the marketing techniques were used without using the internet via direct and indirect marketing strategies such as advertising through Telemarketing,Newspapers,Televisions,Posters etc.
List of Services offered in Digital Marketing |Techvolt Software :
Techvolt Software offers best Digital Marketing services for promoting your products and services through online platform on the below methods of Digital marketing
1. Search Engine Optimization (SEO)
2. Search Engine Marketing (SEM)
3. Social Media Optimization (SMO)
4. Social Media Marketing (SMM)
5. Campaigns
Importance | Need of Digital Marketing (Online Promotions) :
1. Quick Promotions through Online
2. Generation of More leads and Business Enquiries via Search Engine and Social Media Platform
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5. Promotion with less investment
Benefits Digital Marketing Services at Techvolt software :
1. Services offered with Affordable cost
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3. Free Dynamic Website design*
4. Best combo offers on website Hosting,design along with digital marketing services
5. Assured Lead Generation through Search Engine and Social Media
6. Online Maintenance Support
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• Clear and compelling evidence that most legacy SEO metrics and tactics have slim to no impact on SEO outcomes
• A major mindset shift that eliminates most of the metrics and tactics associated with SEO in favor of a single metric that defines and drives organic ranking success
• Practical, step-by-step methodology for choosing SEO pillar topics and publishing content quickly that ranks fastMastering The Best Restaurant Advertising Campaigns Detailed Guide
A guide for making the Best Restaurant Advertising Campaigns with demographics, data analytics, and digital advertising for measurable results.
Top Strategies for Building High-Quality Backlinks in 2024 PPT.pdf
As we move into 2024, the methods for building high-quality backlinks continue to evolve, demanding more sophisticated and strategic approaches. This presentation aims to explore the latest trends and proven strategies for acquiring high-quality backlinks that can elevate your SEO efforts.
Visit:- https://www.1solutions.biz/link-building-packages/
SEO in the AI Era - Trust, Quality and Content Discovery - Andy Crestodina
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We’ve entered a new era in digital. Search and AI are colliding, in more ways than one. And they all have major implications for marketers.
• SEOs now use AI to optimize content.
• Google now uses AI to generate answers.
• Users are skipping search completely. They can now use AI to get answers. So AI has changed everything …or maybe not. Our audience hasn’t changed. Their information needs haven’t changed. Their perception of quality hasn’t changed. In reality, the most important things haven’t changed at all. In this session, you’ll learn the impact of AI. And you’ll learn ways that AI can make us better at the classic challenges: getting discovered, connecting through content and staying top of mind with the people who matter most. We’ll use timely tools to rebuild timeless foundations. We’ll do better basics, but with the most advanced techniques. Andy will share a set of frameworks, prompts and techniques for better digital basics, using the latest tools of today. And in the end, Andy will consider - in a brief glimpse - what might be the biggest change of all, and how to expand your footprint in the new digital landscape.
Key Takeaways:
How to use AI to optimize your content
How to find topics that algorithms love
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Cognitive Biases for Marketers
- 1. @LoveStats Ads Have No Effect On Me: How marketers can leverage cognitive biases Presented by Annie Pettit, PhD FMRIA Buy for Annie BuyforAnnie BuyforAnnie Annieisawesome Thisisthebestpresentationoftheday
- 2. @LoveStats
- 5. @LoveStats When you are aware of them, you can use them But you can bring them into consciousness Unconscious Unconscious Unconscious Unconscious Unconscious Unconscious Unconscious Unconscious Unconscious vUnconsciou Unconscious Unconscious Unconscious Unconsciousconscious nconscious Unconscious Unconscious Unconscious Unconscious Unconsci Unconscio Unconscious Unconscious Unconscious Unconscious Unconscious nconsciousUnconscious
- 6. @LoveStats Social Biases Memory Biases Constituency bias Hyperbolic discounting Hindsight bia Egocentric bias Hawthorne effect Reminiscence bump Outcome bias Decision making Biases Interloper e Interloper effect Omission bias lusory correlation Probability Biases miniscence bump Constituency bias Irrational escalation Halo effect Irrational escalation False memory Suggestibility Herd instinct Gamblers fallacy Barnum effect Hindsight bias Interloper effect Self serving bias Normalcy bias Neglect of probability Hyperbolic discounting Observer expectancy effect False memory Hawthorne effect Memory Biases Telescoping effect Omission bias False consensus effect Neglect of probability Neglect of probab Self serving bias Irrational escalation Hindsight Selection bias Social Bias effect Mere exposure effect Self serving bias
- 7. @LoveStats
- 8. @LoveStats
- 9. @LoveStats
- 10. @LoveStats HA EFF LO ECT Bias: Associate traits of one thing to an aspect of other things Lesson: Run with the beliefs, don’t fight the opposition
- 11. @LoveStats
- 12. @LoveStats
- 13. @LoveStats
- 14. @LoveStats
- 15. @LoveStats BANDW EFF AGON ECT Bias: Tendency to do something because everyone else is Lesson: If it’s your best feature, point out ‘everyone else’
- 18. @LoveStats A $8 C $14 B $12 Cost: $6 Profit: $2 Cost: $12 Profit: $2 Cost: $8 Profit: $4
- 19. @LoveStats
- 20. @LoveStats Bias: Avoid extreme choices because they attract risk Lesson: Increase the profit on the middle item COMP EFF ROMISE ECT
- 21. @LoveStats
- 22. @LoveStats
- 23. @LoveStats
- 24. @LoveStats Bugatti Veyron Jean Bugatti Edition ~$3 million Only three available
- 25. @LoveStats
- 26. @LoveStats LO AVER SS SION Bias: People prefer to avoid loss over acquiring gains Lesson: Create FOMO
- 29. @LoveStats
- 30. @LoveStats Bias: Tendency to accept vague statements as descriptive of them Lesson: Always have a little something for everyone BARN EFF UM ECT
- 31. @LoveStats
- 32. @LoveStats
- 33. @LoveStats
- 34. @LoveStats IK EFF EA ECT high value on ssemble e quality Bias: People place. objects they a regardless of th Lesson: Create investment of time or effort
- 35. @LoveStats
- 36. @LoveStats . ONLY 1% FAT . 99% FAT FREE
- 38. @LoveStats I got 80% right! I got 20% wrong!
- 39. @LoveStats Bias: Avoid risk with a positive frame and seek risk with a negative frame Lesson: Switch the negative to find the positive FRAMING
- 40. @LoveStats
- 41. @LoveStats
- 42. @LoveStats
- 44. @LoveStats BIZAR EFF RENESS ECT Bias: Bizarre is better remembered than common Lesson: Diagnosticate or actualize a grody corporeality
- 46. @LoveStats
- 47. @LoveStats
- 48. @LoveStats Bias: Overly influenced by the first piece of information Lesson: Normalize high usage ANCH BI ORING AS Limit 12 per person
- 49. @LoveStats
- 50. @LoveStats
- 51. @LoveStats
- 52. @LoveStats INGR BI OUP AS Bias: Preferential treatment to members of their own group Lesson: Capitalize on your similarities IMarketing
- 53. @LoveStats Bad! When you don’t know it’s happening When it leads to the wrong decision BIAS
- 54. @LoveStats Good! When you understand it When it makes your decision easier BIAS
Editor's Notes
- Click on button to see live comments
- Avoid risk of 1% fat Seek risk f 99% fatfree