#Data research & development

[catboybiologist]

By now, there's lots of people have heard about the internal CDC memos for all newly prepared manuscripts (like future scientific papers waiting to be published):

There's so much to comment on, and I'm seeing it all right now. What the state of science is. What this means for the queer community. All of that.

But fuck, I think I might genuinely start crying over this. As a transgender biologist, this feels like a brutally personal blow. I slowly accepted my gender alongside my biology education. The more misinformation that was spewed about "biological sex" by mainstream media, the more my professors, colleagues, and primary sources would casually drop information that proved they have no idea what they're talking about. I'm not an expert on sex determination, gender, or transgender biology specifically by any means. But my worldview has been crafted by my studies in genetics and molecular biology.

Engaging with this research helped me demystify transition. It helped me optimize my transition. It helped me explain how HRT and other steps of trans healthcare work to other people. And it helped me overcome my own internalized transphobia, and finally start transitioning, despite knowing I wanted to since my preteen years.

Who knows how enforceable internal guidelines like this will be. But its certainly going to scare a lot of researchers away from transgender healthcare and science in the coming years, and that breaks my heart.

There's a lot I can say here, but fuck. I just needed to vent for a moment. Fuck.

[kittykatninja321]

what’s crazy is that just a year ago I was using the data on the CDC website to research HIV statistics/history for a college project, and right now someone who got the same assignment I did might be having a much harder time with that project because that information is being censored by the government

[ogsuicidal]

“some studies suggest POTS may be a disorder of both the peripheral and central nervous systems”

they’d fucking better??? this is new information? what?

i really feel like the field of medicine would benefit if doctors encouraged patients to be informed about like… general human biology and anatomy. and asked us more questions in general.

because i feel like if you ask any person with POTS who knows what the peripheral and central nervous systems are if they’re both effected we’d probably all say “yes”… or they could ask about specific symptoms or whatever in a more normal way y’know… and idk, think about what part of the nervous system controls those symptoms. or just apply critical thinking in general like… what does the peripheral nervous system do? it communicates with the central nervous system. therefore, we can hypothesize that most things which effect one system will also effect the other.

and then they could’ve done the dumbass water is wet studies to prove it before a global pandemic sparked autoimmune-induced POTS in god knows how many people… and maybe treatment would address the neurological side of the disorder more often as well, rather than just focusing on the cardiovascular side of things and all those people (not to mention the people like me who have non-autoimmune related POTS… who were simply not numerous enough to warrant such research, of course) would face less disability and have access to a higher quality of life.

[jcmarchi]

Eric Schmidt: AI misuse poses an ‘extreme risk’

New Post has been published on https://thedigitalinsider.com/eric-schmidt-ai-misuse-poses-an-extreme-risk/

Eric Schmidt: AI misuse poses an ‘extreme risk’

Eric Schmidt, former CEO of Google, has warned that AI misuse poses an “extreme risk” and could do catastrophic harm.

Speaking to BBC Radio 4’s Today programme, Schmidt cautioned that AI could be weaponised by extremists and “rogue states” such as North Korea, Iran, and Russia to “harm innocent people.”

Schmidt expressed concern that rapid AI advancements could be exploited to create weapons, including biological attacks. Highlighting the dangers, he said: “The real fears that I have are not the ones that most people talk about AI, I talk about extreme risk.”

Using a chilling analogy, Schmidt referenced the al-Qaeda leader responsible for the 9/11 attacks: “I’m always worried about the Osama bin Laden scenario, where you have some truly evil person who takes over some aspect of our modern life and uses it to harm innocent people.”

He emphasised the pace of AI development and its potential to be co-opted by nations or groups with malevolent intent.

“Think about North Korea, or Iran, or even Russia, who have some evil goal … they could misuse it and do real harm,” Schmidt warns.

Oversight without stifling innovation

Schmidt urged governments to closely monitor private tech companies pioneering AI research. While noting that tech leaders are generally aware of AI’s societal implications, they may make decisions based on different values from those of public officials.

“My experience with the tech leaders is that they do have an understanding of the impact they’re having, but they might make a different values judgement than the government would make.”

Schmidt also endorsed the export controls introduced under former US President Joe Biden last year to restrict the sale of advanced microchips. The measure is aimed at slowing the progress of geopolitical adversaries in AI research.  

Global divisions around preventing AI misuse

The tech veteran was in Paris when he made his remarks, attending the AI Action Summit, a two-day event that wrapped up on Tuesday.

The summit, attended by 57 countries, saw the announcement of an agreement on “inclusive” AI development. Signatories included major players like China, India, the EU, and the African Union.  

However, the UK and the US declined to sign the communique. The UK government said the agreement lacked “practical clarity” and failed to address critical “harder questions” surrounding national security. 

Schmidt cautioned against excessive regulation that might hinder progress in this transformative field. This was echoed by US Vice-President JD Vance who warned that heavy-handed regulation “would kill a transformative industry just as it’s taking off”.  

This reluctance to endorse sweeping international accords reflects diverging approaches to AI governance. The EU has championed a more restrictive framework for AI, prioritising consumer protections, while countries like the US and UK are opting for more agile and innovation-driven strategies. 

Schmidt pointed to the consequences of Europe’s tight regulatory stance, predicting that the region would miss out on pioneering roles in AI.

“The AI revolution, which is the most important revolution in my opinion since electricity, is not going to be invented in Europe,” he remarked.

Prioritising national and global safety

Schmidt’s comments come against a backdrop of increasing scrutiny over AI’s dual-use potential—its ability to be used for both beneficial and harmful purposes.

From deepfakes to autonomous weapons, AI poses a bevy of risks if left without measures to guard against misuse. Leaders and experts, including Schmidt, are advocating for a balanced approach that fosters innovation while addressing these dangers head-on.

While international cooperation remains a complex and contentious issue, the overarching consensus is clear: without safeguards, AI’s evolution could have unintended – and potentially catastrophic – consequences.

(Photo by Guillaume Paumier under CC BY 3.0 license. Cropped to landscape from original version.)

See also: NEPC: AI sprint risks environmental catastrophe

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

[un-pearable]

this is yet another random academia nitpick i won’t let go of for weeks but someone in the comments of the victor ninov broccumentary claimed that science is a “incredible field that can’t be simplified to storytelling like this” because “it goes against human nature to do” and writing good sci comm goes against scientific integrity.

and the whole statement is incredibly stupid but in true anthropologist fashion i must say what on earth about science goes against human nature. the desire to test a phenomenon and revise your theories based on the results is literally one of the benchmarks for early modern humans. this is the behavior in corvid’s (tool use) that people loose their shit over. communicating findings to others?? collaborative work to reach an arbitrary goal that won’t necessarily have a direct benefit on your immediate life???? that’s how we domesticated staple crops dumbass. it’s science all the way down

[xlsdesignt]

what u think, to much colour, or less?

https://sdesignt.threadless.com/

[freakystinky]

the way tumblr talks about medicine makes me wonder how many of us here actually have critical thinking skills

[welcometoteyvat]

why did they shove ai research into fontaine

[mangled-by-disuse]

I have such mixed feelings about the love languages thing specifically, because, like, gary chapman fucking sucks and there's no scientific validity to his work BUT

at the same time, i do think there's some value in recognising and discussing the fact that different people need different expressions of love in different amounts? Especially in relationships.

Like, I have just recently been having a discussion with my partner about how he really doesn't tend to express his affection through gifts, whereas (as someone who is mega-bad at expressing sincere feeling) I do rely heavily on giving gifts and doing things for people as a less scary way to express love. Joe doesn't like giving gifts, because he's scared he'll do it wrong, and is only so-so on receiving them. He prefers to express love through physical contact and saying nice things. I hate having nice things said to me unless I am allowed to immediately rebut them with a joke or sarcastic comment that makes them less scarily close to emotional honesty. too many words of affirmation and i will genuinely just start avoiding you because it is painfully awkward to me.

and none of that means we are fundamentally different categories of people, which is where the 5 Love Languages stuff falls into being absolute bollocks. but I have seen, and done, enough throwing the baby out with the bathwater on that to be a little defensive - I think reasonable applications of the concept are actually really quite valuable. and for me, the taxonomy Chapman suggests (words of affirmation, quality time, gifts, acts of service, physical touch) while not at all exhaustive or thorough, is a useful framework to hang those conversations on. bc, like, no, the way people communicate and receive affection is not universal, and from personal experience, assuming that it is can have really significant problems for a relationship.

...you could argue that this is parallel to BMI in terms of "tools being used in totally not the way they should be used" though, tbf.

I can't keep having the same conversations about love languages, mbti, iq, bmi, "brain fully formed at 25" and shit over and over again...

[worldpharmatoday]

MMS, an award-winning CRO, acquires Exploristics and KerusCloud to expand biostatistics & data science capabilities. latest pharma news today

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[thejembe]

How Research Can Boost New Product Launch Success

Launching a new B2C product? Success starts with smart research. This article explores how market research—especially through custom online panels—can help businesses understand audience needs, refine product features, craft effective messaging, set optimal pricing, and anticipate challenges. It also shows how ongoing feedback post-launch supports continuous improvement and customer satisfaction. Discover why data-driven insights are essential to capturing market attention and achieving lasting impact. A must-read for B2C marketers and product teams.

Link: https://thejembe.com/how-research-can-boost-new-product-launch-success/

[phoradendron]

My abstract's been accepted to a conference and I am so nervous

but at least I get to talk about haunted houses and disparage landlords with a bunch of weirdos

[mhorkya]

Mhorkya – Your Best Virtual Service Provider in India

[philomathresearch]

Mastering Quantitative Market Research: Key Strategies

Have you ever wondered how companies like Nike anticipate consumer trends so accurately? Or how Netflix seems to know exactly what you’d like to watch next? The answer lies in the power of quantitative market research—a systematic approach to understanding consumer behavior through numerical data.

In today’s data-driven world, businesses must navigate a complex landscape of consumer preferences, market dynamics, and competitive pressures. Quantitative market research serves as a compass, guiding companies toward informed decisions that resonate with their target audience. In this comprehensive guide, we’ll delve into the secrets of mastering quantitative market research, exploring its methodologies, real-life applications, and the transformative impact it can have on your business strategy.

What is Quantitative Market Research?

Quantitative market research involves the collection and analysis of numerical data to identify patterns, predict trends, and make informed business decisions. Unlike qualitative research, which explores subjective experiences and opinions, quantitative research focuses on measurable variables—think percentages, frequencies, and statistics.

Common methods include:

Surveys and Questionnaires: Structured tools that gather data from a large audience.

Experiments: Controlled scenarios to test hypotheses about consumer behavior.

Analytics: Examination of existing data sets to uncover trends and correlations.

By employing these methods, businesses can quantify consumer behaviors, preferences, and attitudes, leading to actionable insights.

The Growing Importance of Quantitative Market Research

The global market research industry is experiencing significant growth, underscoring the increasing reliance on data-driven decision-making. In 2024, the industry is projected to generate $140 billion, up from $130 billion in 2023. This growth reflects a 37.25% increase from 2021 to 2024, highlighting the escalating demand for precise consumer insights.

Online and mobile quantitative research services have become particularly prominent, accounting for 35% of global market research revenues. This shift indicates a move toward more accessible and scalable data collection methods, enabling businesses to reach diverse audiences efficiently.

Real-Life Example: Nike’s Data-Driven Product Development

Nike’s “Just Do It” isn’t just a catchy slogan—it’s a philosophy grounded in quantitative research. By analyzing consumer feedback, sales data, and trend analyses, Nike creates highly personalized products that resonate with their audience.

In 2022, Nike’s women’s apparel line experienced a 20% growth. This surge was driven by insights revealing that women desired more inclusive sizing and functional designs. By leveraging survey data and sales trends, Nike adapted its product offerings to meet these specific consumer needs, resulting in increased customer satisfaction and sales.

Benefits of Quantitative Market Research

Embracing quantitative market research offers several advantages:

Enhanced Customer Understanding: Gain a deep insight into customer preferences, purchasing habits, and pain points, allowing for tailored products and services.

Improved Decision-Making: Data-backed insights inform strategic decisions across product development, marketing, and customer service.

Increased ROI: Data-driven strategies significantly boost profitability. According to a 2023 McKinsey report, companies utilizing such strategies are 19 times more likely to be profitable.

Competitive Advantage: Anticipate market trends and adapt swiftly, staying ahead of competitors.

Implementing Quantitative Market Research: A Step-by-Step Guide

Embarking on a quantitative market research journey involves several key steps:

1. Define Clear Objectives

Identify what you aim to discover. Are you exploring a new market segment? Assessing customer satisfaction? Clear objectives provide direction and focus.

2. Choose the Right Methodology

Select a research method that aligns with your objectives:

Surveys: Ideal for gathering data from a large audience.

Experiments: Suitable for testing specific hypotheses.

Analytics: Best for uncovering trends in existing data.

3. Develop Effective Data Collection Tools

Craft surveys or questionnaires with clear, unbiased questions. Ensure they are concise to maintain respondent engagement.

4. Select a Representative Sample

Ensure your sample accurately reflects your target population. This may involve stratified sampling or random sampling techniques.

5. Collect Data Systematically

Administer your data collection tools consistently, whether through online platforms, face-to-face interactions, or other channels.

6. Analyze Data Thoroughly

Utilize statistical software to identify patterns, correlations, and insights. Visualization tools like Tableau or Power BI can aid in presenting data effectively.

7. Interpret and Apply Findings

Translate data insights into actionable strategies. This could involve refining products, adjusting marketing campaigns, or exploring new market opportunities.

Real-Life Example: Netflix’s Personalized Recommendations

Netflix’s success is largely attributed to its sophisticated use of quantitative research. By analyzing viewing habits, ratings, and user interactions, Netflix offers personalized content recommendations to its subscribers.

This data-driven approach has led to increased viewer engagement and retention. In fact, over 80% of the content watched on Netflix is influenced by their recommendation system, showcasing the power of quantitative analysis in enhancing user experience.

Challenges in Quantitative Market Research and How to Overcome Them

While powerful, quantitative market research presents certain challenges:

1. Data Overload

The vast amount of data available can be overwhelming. To manage this:

Utilize Data Visualization Tools: Platforms like Tableau or Power BI help in visualizing complex data sets, making them more comprehensible.

Focus on Relevant Metrics: Identify key performance indicators that align with your objectives to maintain focus.

2. Survey Fatigue

Respondents may become weary of lengthy or frequent surveys, leading to lower response rates. Combat this by:

Keeping Surveys Concise: Limit the number of questions to maintain engagement.

Incentivizing Participation: Offer rewards or acknowledgments to encourage responses.

3. Bias in Data Collection

Unintentional biases can skew results. Mitigate this by:

Crafting Neutral Questions: Avoid leading or loaded questions that may influence responses.

Ensuring Diverse Sampling: Strive for a sample that accurately represents your target population.

The Role of Technology in Quantitative Market Research

Advancements in technology have revolutionized quantitative market research:

Artificial Intelligence (AI): AI enhances data analysis by identifying patterns and predicting trends with greater accuracy. As of recent studies, 47% of researchers globally use AI regularly in their market research activities.

Online Surveys: Digital platforms enable rapid data collection from a broad audience. Notably, 87% of market researchers conduct at least half of their qualitative research online.

Analytics Software: Tools like Google Analytics provide real-time insights into consumer behavior, facilitating timely decision-making.

Real-Life Example: Starbucks’ Customer Feedback Loop

Starbucks leverages quantitative research to refine its offerings continually. Through their “My Starbucks Idea” platform, they collected customer suggestions and feedback, leading to innovations like free Wi-Fi and mobile payment options.

This initiative not only enhanced customer satisfaction but also fostered a sense of community and loyalty among patrons. By valuing and implementing customer input, Starbucks strengthened its brand and market position.

Conclusion: Harnessing the Power of Numbers

Quantitative market research is more than just crunching numbers; it’s about uncovering the stories those numbers tell. By systematically collecting and analyzing data, businesses can gain profound insights into consumer behavior, market trends, and operational efficiency.

At Philomath Research, we specialize in transforming raw data into actionable strategies. Our expertise in quantitative research empowers businesses to make informed decisions that drive growth and innovation.

FAQs

1. What is quantitative market research?

Quantitative market research is a data-driven approach that involves collecting and analyzing numerical data to identify patterns, predict trends, and make informed business decisions. It focuses on measurable variables like percentages, frequencies, and statistics.

2. How is quantitative market research different from qualitative research?

Quantitative research focuses on numerical data and statistical analysis, while qualitative research explores subjective experiences, opinions, and motivations through open-ended questions, interviews, and focus groups.

3. What are some common methods of quantitative market research?

The most common methods include:

Surveys & Questionnaires – Gather responses from a large audience.

Experiments – Test hypotheses in controlled environments.

Data Analytics – Analyze existing datasets to identify trends.

4. Why is quantitative market research important for businesses?

It provides actionable insights into consumer behavior, improves decision-making, enhances customer satisfaction, and offers a competitive edge by predicting market trends.

5. How does Nike use quantitative research to develop products?

Nike analyzes consumer feedback, sales data, and trend reports to create products tailored to customer needs. For instance, its women’s apparel line saw 20% growth after incorporating insights on inclusive sizing and functional designs.

6. What are some benefits of quantitative market research?

Enhanced customer understanding

Improved decision-making

Increased return on investment (ROI)

Competitive advantage in the market

7. How do companies collect and analyze data in quantitative research?

Businesses use digital surveys, online platforms, and data analytics tools like Google Analytics, Tableau, and Power BI to collect and interpret data effectively.

8. How does Netflix use quantitative market research for recommendations?

Netflix analyzes viewing habits, user ratings, and engagement patterns to offer personalized content recommendations, with over 80% of watched content influenced by its algorithm.

9. What are some challenges in quantitative market research?

Data Overload: Too much data can be overwhelming—visualization tools help simplify insights.

Survey Fatigue: Long surveys can lead to low response rates—keeping them concise improves engagement.

Bias in Data Collection: Leading questions or an unrepresentative sample can skew results.

10. How is technology shaping quantitative market research?

AI-driven analytics, online surveys, and advanced software tools like Google Analytics and Power BI have made data collection faster, more accurate, and scalable for businesses.

11. How does Starbucks use quantitative market research?

Starbucks collects customer feedback through initiatives like “My Starbucks Idea,” which led to innovations like free Wi-Fi and mobile payments, enhancing customer satisfaction and loyalty.

12. How can businesses implement quantitative market research effectively?

By following these key steps:

Define clear objectives

Choose the right methodology

Develop effective data collection tools

Select a representative sample

Collect data systematically

Analyze data using statistical tools

Interpret findings and apply insights

13. What role does Philomath Research play in quantitative market research?

Philomath Research specializes in transforming raw data into actionable business strategies, helping companies leverage quantitative insights for growth and innovation.

[clivaldatabase]

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