Artificial intelligence
Jan
Financial Services Sector Expanding Rapidly But There Will Be Growing Pains
jerry9789 0 comments artificial intelligence, Brand Surveys and Testing, Brandview World
SIS International says the outlook for the financial services sector is one of solid and consistent growth, expected to reach $47.55 trillion in 2029, but it is not without anxieties. They shared that around three-quarters of financial services executives on a recent survey expressed concerns over their institutions’ ability to navigate economic instability, adapt to emerging technologies and shifting regulations, as well as sustain existing revenue sources in the coming decade.
SIS points to five key trends where financial institutions could focus their research priorities at as the financial services landscape continues to develop and change:
- AI implementation: Despite high technology adoption rates, a good majority of banking customers struggle to trust AI applications.
- Digital Banks: More and more customers are switching to neobanks. Learning the reasons behind this growing preference would help traditional financial organizations reposition themselves while digital banks would benefit from these insights through sustainable growth and expansion.
- Mobile Banking: Digital channels have established themselves as the primary form of interaction between customers and their banks, and fostering engagement and a more personalized experience through research could lead to improved loyalty.
- Expanding Financial Services Options: Delving into growing technology-oriented fronts open up exploring new and additional avenues to offer financial services digitally.
- Addressing Security Concerns: Adopting security measures against fraud and privacy is just the start but targeted research would help recognize which protections build confidence and trust based on the concerns expressed by different customer segments.
High-quality market research would help financial institutions understand what would cause their customers to hesitate or quickly adapt to new technology or measures, the most effective way to communicate benefits and advantages, targeting the most receptive customer segment, and identifying new opportunities and channels, just to name a few.
Overall, effective market research into these five key insights should enable financial organizations to make confident and strategic decisions aligned with business goals.
Image: Audy of Course
Featured Image: Tima Miroshnichenko
Top Image: Jakub Zerdzicki
Dec
Can AI Replace Human Respondents In Qualitative Research?
jerry9789 0 comments artificial intelligence, Brand Surveys and Testing, Brandview World, Burning Questions
Like most industries these days, market research is no stranger to AI with its broad applications including the employment of synthetic respondents, which are individual profiles constructed by Large Language Models (LLMs) from real or simulated data. They offer fast, cheap, and scalable synthetic data that closely mimics how human participants would respond, a boon for quantitative research. But can synthetic respondents be just as effective in qualitative research? Can AI-powered profiles fully take over the role of human respondents in market research?
Image: Diana
Synthetic Respondents and Qualitative Research
L&E Research recently hosted a webinar sharing their findings and observations testing synthetic respondents across a variety of qualitative research tasks. They shared that AI characteristically produces quick, structured, and consistent surface-level insights. It does well with detecting macro trends in usage or preferences, concept screening if you need to compare multiple ideas at scale, and spot issues with survey testing. It is also capable of gap-filling or simulating missing segments from known data, as well as bulk analysis for summarizing large open-ends quickly.
The key takeaway L&E found is that AI can describe what people do, but it falls short of telling why people do it. AI fundamentally excels in following patterns, but it would struggle with finding out the emotional driver, the motivation behind certain responses. AI can match logic but it won’t be able to fill in tone, nuance nor context like human insight and experience can.
Most AI models are also built on public data and may not have access to knowing how real people would respond to certain questions. When the engineers tried to influence AI agents in the direction of how real participants would respond, it rejected this notion and firmly stood by the perspective formed from the vastness of public data.
Additionally, AI can be absolutely and confidently wrong. Synthetic data can look convincingly human but since AI relies on patterns instead of experience, the air of confidence it puts up doesn’t guarantee accuracy.
Of course, the hosts added a disclaimer that this is where synthetic respondents are at right now, as no one could tell how things could possibly be so much different in the years to come. But the continued utilization of AI in market research- or any other industry, for that matter- is inevitable thanks to the operational and executionary efficiency it grants, and that is enough reason to continue studying and developing synthetic respondents.
Image: Ron Lach
Why The Human Factor Matters
In market research, emotions matter and context counts. AI can prove to be a powerful partner but it is no replacement for lived insight or validation. Human researchers are simply going to remain essential.
AI’s inherent structure and consistency is representative of its pursuit of perfection; however, humans aren’t perfect, nor simple. Humans are emotional and oftentimes, irrational. AI participants would respond based on their perfect approximation of how a human being would, but the synthetic logic behind that would be narrower and more consistent, as it discounts the fact that humans are imperfect.
Humans also bring incredible complexity and a broader range of perception to the table. We can contradict ourselves, and this would be natural. One human participant’s perception and experiences could inform the difference in how they respond from the next, while synthetic data would be uniformly shaped by congruence and invariability, no matter how much effort or work is put into making AI come close to mimicking humanlike responses.
The complexity, variability, and randomness of human nature is desirable in qualitative research. The engineers recognized this and cautioned about overly guiding or influencing randomness in AI that it “will hard-code your picture of randomness to the point where it is no longer random.”
AI can quickly give you bulk analysis but you might not want to rush in bringing it to your stakeholders, as they would question and challenge the quality and reliability of synthetic data. Human insight continues to be vital and irreplaceable when it comes to trust, nuance, and real-world complexity in market research.
Image: Kathrine Birch
The Hybrid Approach
At the end of it all, the hosts made a point that the webinar wasn’t meant to scare people away from synthetic data but rather bring a valid conversation on when it makes sense to take advantage or steer clear of AI-generated personas. In fact, they recommended utilizing a hybrid approach of employing virtual respondents and recruiting human participants, striking a delicate balance between synthesis and empathy.
Synthetic data would be great during the early exploratory stages of market research when you want to get an initial pulse check, something quick and good enough before getting people involved. But once you’re at the point when you need to uncover the emotional driver behind responses and decisions, understand or predict behaviors, or even gain a bit more confidence and trust in your findings, that’s when you bring in your human respondents.
This all aligns not only with a recent growing trend of companies coming around from the AI hype of the last few years but also with our stance on the appropriate use of AI, where we advocate for the responsible and ethical use of artificial intelligence. Instead of handing AI complete reins over all aspects of a business- or in this case, all stages of research work- we at Cascade Strategies encourage the thoughtful and practical application of artificial intelligence in combination with or enhanced by human experience, values and discretion.
To find out how our brand of inspired and enlightened human thinking can help you with your market research needs, please contact us here.
Additional Reading:
Can Synthetic Respondents Take Over Surveys?
Featured Image: Darlene Anderson
Top Image: Michelangelo Buonarroti
Nov
Are We Seeing The Start Of The AI Pullback?
jerry9789 0 comments artificial intelligence, Burning Questions
What Is AI Pullback?
In these last few years, we’ve all heard nothing but the revolutionary and transformative influence of Artificial Intelligence not only in the mainstream consciousness but also in various industries. A mixture of excitement and anxiety, we’ve collectively marveled at what Generative AI could produce or emulate in little to no time at all while grasping at the notion of what all this automation means for the human workforce and talent. However, the tone appears to be shifting these past few months with data showing large companies’ adoption of AI on the decline.
As reported in Apollo, a biweekly US Census Bureau survey of 1.2 million firms revealed a downward trend in AI utilization for companies with more than 250 employees. Falling from about 13.5% in June to under 12% in August, it’s the largest decline for AI adoption since the survey started in November 2023. Mid-sized companies or firms with less than 250 employees but more than 19 workers showed decreasing or stagnating AI adoption. It’s only with small companies with less than four employees that demonstrated a slight increase in AI usage.
New reports might help shed light on the AI pullback, such as a recent one from MIT indicating that 95% of AI pilot programs failed to boost company revenues or productivity. MIT’s findings were based on reviews of over 300 public corporate AI usage, surveying 350 employees, and talking with 150 industry leaders.
A recent study by METR revealed that developers surprisingly took 19% longer to complete issues when using AI coding tools than without. Yet despite actually experiencing slowdown, the developers still believed AI sped them up by 20%. This gap between developers’ perception and reality is representative of these past few years with the hyped up implementation of AI into everything software-related and unrestrained confidence in the hot new tech in spite of the unfavorable results.
IT Consultancy Gartner also attempted to quantify how much work AI agents get wrong when it “hallucinates.” They found that generative AI performs office tasks wrong a staggering 70% of the time. With that much error, human oversight becomes a necessity and in some cases, objectives would’ve been served much better had the task been assigned to a person instead of a machine.
Image: Mathias Reding
Is AI Pullback A Sign Of AI Adoption Maturity?
On a different note, the MTLC wrote that the AI pullback might seem like a slowdown but it could actually be a correction or calibration, as is the natural progression with any emerging tech’s usage. They pointed out that the same MIT report accounted for over 90% of employees using AI tools, no matter the company stance with AI. That these workers would utilize AI just so they can perform their tasks more efficiently and faster. And that this is another way at looking at AI adoption- “bottom-up, not just top down.”
It’s not that AI isn’t viable, but rather “the projects weren’t scoped, aligned, or designed for outcomes.” 95% of AI projects fail not because of the technology but because of how companies approach AI adoption.
AI pullback is signaling the transition from overenthusiasm to realistic expectations, from experimentation to production. For enterprise businesses to succeed with AI, they would need to identify which models, tools and processes work, which projects to invest in, and where AI would deliver the most value.
Image: Andrea Piacquadio
Cascade Strategies’ Approach To AI
The promise of increased production and revenue had led to companies to replace or cease hiring human workers in favor of AI during the onset of its mainstream popularity. Now that AI pullback is happening, companies have begun hiring human workers again not only to oversee but fix or improve sloppy AI outputs.
Cascade Strategies has always approached AI not just merely as a tool but as an augmentation and extension of human intelligence and talent. Yes, AI is a very powerful and promising technology but we recognize early on that on its own, it is gravely limited to the datasets its fed and their quality, the eventual gaps providing the perfect breeding ground for “hallucinations,” each iteration degrading and becoming less of what was before. We’ve always seen human intervention and guidance as essential for AI to maximize its potential; with the AI pullback, more and more companies are on the brink of discovering this incredible synergy between human and artificial intelligence.
Powered by AI, research becomes scalable and cost-effective by being applicable in all facets of the business and not just flagship projects; human oversight amplifies all that productivity and efficiency by unlocking innovative, resonant and actionable insights.
If you would like to learn more about how our human-centered market research work can benefit you or your company, feel free to contact us here.
Image: cottonbro studio
Additional Reading:
AI Pullback Has Officially Started – Will Lockett, medium.com Oct. 22, 2025
Data Shows That AI Use Is Now Declining at Large Companies – Joe Wilkins, futurism.com Sep. 8, 2025
AI adoption slows among big firms, U.S. data shows – Jullianna Anne Briones, tech.co Sep. 18, 2025
US Census Bureau: AI Adoption Has Declined for Large Companies – Conor Cawley, Sep. 11, 2025
AI adoption rate is declining among large companies — US Census Bureau claims fewer businesses are using AI tools – Hassam Nasir, tomshardware.com Sep. 8, 2025
Featured Image: MrWashingt0n
Top Image: Thirdman
Oct
A Human Center Makes Market Research All The More Powerful
jerry9789 0 comments artificial intelligence, Brand Surveys and Testing, Brandview World
The Future Of Research Is Here
You’ve seen it and there’s no denying it. Industries have been reshaped by the increasing utilization of Artificial Intelligence just in the last few years alone. Promising and delivering speed and optimization at the fraction of the costs and resources, it’s powerful, revolutionary and exciting. And as with any emerging technology, it comes with its own set of anxieties.
In line with its growing popularity and adoption, people in different industries have been expressing nervousness over being replaced in their jobs by AI. Certain repetitive, data-driven tasks are at the greatest risk of being supplanted by AI. However, AI also opens up opportunities to shift focus and upskill the more complex and creativity-driven facets of work roles, creating new jobs or augmenting existing ones.
The research industry is just as impacted by AI’s progressive application. It’s naive to assume that researchers would be replaced wholesale by AI, but there’s more to delivering research results than just gathering and crunching data.
Image: Circe Deyer
Our take on the integration of AI into research
We’ve always maintained that AI is a good advisor, but it’s a poor decision-maker. We’d like to modify that by saying it’s an even worse storyteller, if at all.
Cascade Strategies has been in the market research industry for over three decades now, serving some of the biggest local and international companies. You can say we’ve seen it all in this industry, but we’re just as fascinated as everyone else by the mainstream popularity of AI in the past few years. We’ve applied it in our methodologies, been impressed by its operational benefits and how it changed industries, but in the end, we know truthfully that it is not the end-all, be-all for research work. We believe that AI would serve us better by being a powerful extension of human judgment, creativity, and insight.
AI can be fed large datasets to approximate human thinking, but we believe it can never replicate human perspicacity, the kind of intelligence honed and guided by human values and experience. Take a look at our Expedia Group Case Study where we’ve utilized AI to generate multiple revenue-granting scenarios, then tempered the decision-making process by applying high-level human thinking to craft messaging that resonates with the end-user.
AI-driven research can produce results based on what has come before, but it can never uncover the truly novel, meaningful and resonant insights high-level human thinking unlocks. These are the insights that empower big and sweeping decisions. Data-based results from AI would seem lifeless and unrelatable. But if they are imbued with human interpretation, that output elevates into a masterful narrative that sparks imagination, questions boundaries, and transforms perspectives.
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Featured Image: mohamed mahmoud hassan
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Oct
Pendleton Woolen Mills – A Retail Story
jerry9789 0 comments artificial intelligence, Brand Surveys and Testing, Brandview World
Pendleton Woolen Mills allowed us to conduct qualitative and quantitative research for them. The result was a key brand insight about a kind of consumer called the Purist, who preferred the Pendleton shopping experience over the experiences offered by key competitors, and whose loyalty to Pendleton could be counted on. The campaigns built around the Purist helped Pendleton weather the storm of competition from competitors like Filson, Carhartt, and Orvis.
It’s doubtful that submitting the same data to AI would produce a finding as incisive as the Purist. This is something to bear in mind if you’re a retail brand seeking to thrive: human perspicacity counts.
There’s a kind of intelligence AI can’t reach. It has dimension, soul, and human inspiration. We’d do well to remember this as we pour more datasets into the maw of AI. If you’re a retailer and need perspicacity, you might call Cascade Strategies. We can help you see things AI can’t see.
Image: Eric Schucht
Sep
Achieve Breakthroughs By Tapping Into Your Primal Intelligence
jerry9789 0 comments artificial intelligence, Burning Questions
Is Artificial Intelligence going to be the be-all, end-all for decision-making, problem-solving and innovation? If AI is faster, more logical and more efficient than humans, why hasn’t it overtaken us already? Is there a way for human genius to gain the edge over AI?
Yes, AI has changed the way we’ve done things these last few years – optimizing and streamlining processes to improve efficiency and effectiveness while maximizing output and in some cases, reducing costs. AI thrives in a production environment with defined datasets, but take away all that reliable data and introduce new variables, and it crumbles.
AI can generate art and stories, but it does this based on the data it was fed and trained on. It’s truly incapable of producing anything genuinely novel from outside that frame. This means it has the potential to suffer in a self-loop of homogeneous and biased outputs over time, building towards incoherence.
In a world that is increasingly being taken over by AI processes and outputs, recognizing and understanding this limitation is going to help human intelligence find its place and continue to thrive and evolve. In fact, just as AI gained mainstream popularity these past few years, another type of human intelligence has captured the attention and imagination of researchers – and the U.S. Army at the same time.
Image: Lukas
What Is Primal Intelligence?
Ohio State University professor Angus Fletcher, along with other researchers at Ohio State’s Project Narrative, started to investigate in 2021 something called “primordial brainpower” that reportedly drives human intuition. Their research led them to something they call Primal Intelligence, a kind of “natural cleverness” by humans that can be strengthened through training, but which AI can’t replicate.
Professor Fletcher describes Primal Intelligence as part of our lost nature and a key to activating intuition, imagination, emotion, and common sense. The U.S. Army Special Operations then adopted primal training for its most classified units and according to Professor Fletcher, Special Operators saw the future faster, thought more quickly, acted more swiftly, and healed more rapidly from trauma. After the Army authorized trials on civilians such as entrepreneurs, doctors, engineers, managers, coaches, teachers, investors, and NFL players, they found their leadership and innovation significantly improved. These civilians coped better with change and uncertainty, and experienced less anger and anxiety. The Army subsequently provided primal training to college and K–12 classrooms with students as young as eight, and they reported substantial beneficial effects from the training. In 2023, the Army awarded Professor Fletcher the Commendation Medal for his research on retraining the human mind.
Professor Fletcher’s research has been endorsed by renowned psychologists, neuroscientists, and doctors. He has received support from major institutions such as the National Science Foundation. He also wrote the book Primal Intelligence: You Are Smarter Than You Know, from which the following five key insights for sharpening our primal intelligence are derived.
Image: Alana Jordan
1. Exceptional Information
Special Operators “see” or anticipate the future faster than other soldiers on the battlefield, thanks to their unusually high level of intuition. But how does one improve their intuition?
To begin with, you’ll need to dissociate intuition from the decades-old concept that intuition is just mere pattern matching. The aforementioned Operators have trained their brains to find what the Army has dubbed “exceptional information.” Succinctly put, exceptional information is an exception to a previously established rule; it’s the opposite of a pattern because it’s the breaking of a pattern.
Young children score high on intuition but lower at pattern matching because their brains are focused more on unusual details than on familiar patterns. Training your brain to spot exceptions rather than thinking in patterns can help improve your intuition.
Travel or go on trips to immerse your brain in places that break the pattern of your regular life. Reading the works of authors like Shakespeare can also help improve intuition because of characters who are exceptions to traditional narrative tropes, like Hamlet the deep-thinking action hero or the cold and scheming Cleopatra who possesses a loving heart. Known Shakespeare readers who were able to anticipate the future by spotting exceptions range from Nikola Tesla with his AC motor, Marie Curie with radioactivity, and even Vincent van Gogh and his use of aquamarine.
Image: Donald Tong
2. Rethinking Optimism
Optimism pushes us to take on chances which could lead to growth, but why do many people fall back into pessimism? Why do we need to remind ourselves that optimism works better than pessimism instead of instinctively switching to the former frame of mind whenever something new or unusual comes up? Why is optimism this fragile in our minds?
This has something to do with how we think of optimism. We’ve been taught that optimism is “this will succeed,” when “this can succeed” is much more powerful and stronger. Instead of convincing us that this will succeed, we remember that we can succeed.
Remembrance over visualization. Special Operators call this method antifragile because remembering that one time in the past when you’ve been successful is more resilient than magically thinking of achieving success. Building your optimism on the foundation of faith where you’ve succeeded one time no matter how many times you fail can be all you need to keep on going. This is an improvement over being buoyed by the hope that you can succeed, but having your confidence eroded when you don’t.
Image: Kaboompics.com
3. Thinking In Story
In new situations with little to no precedent values (where AI falls apart), how are Special Operators not only able to pull through but also excel?
We have to remind ourselves that the human brain features more than one type of intelligence. While it evolved over a million years with the capacity to think logically and process data from which computers were modeled, the human brain also developed narrative cognition or simply put, the ability to think in story.
Thinking in story means the brain sees the “movement” of story, from beginning to middle to end, with room for imagination to explore possibilities and wisdom to sensibly tie things together. AI has the ability to generate story plots and images from datasets, but it still doesn’t read the story. It’s still our human brains that instill story and meaning to these generated plots and images.
High-data environment and conditions might not be conducive for thinking in story, but it finds its place in volatile and uncertain situations. Special Operators who performed well in volatility were found to have brains proficient at thinking in story.
Image: cottonbro studio
4. Empowerment Through Role-playing
Anger and anxiety are physiological indicators of a threat response. So what’s the best way to mitigate the brain’s threat response? Removing the threat, usually with outside force, might spring to mind but what if we tell you that conjuring a gameplan with your brain to deal with the threat is more effective?
That’s exactly how Special Operators function. Instead of avoiding threats, they advanced toward the threats and they do this without feeling anxious or angry. That’s because these Operators have trained their brains to imagine plans for dealing with threats. And they train their imagination by engaging in role-playing exercises.
Outside of Special Operations, role-playing can be taught to regular people or students by taking part in arts and humanities activities such as theater, literature, and history. The key is to be able to imagine oneself as somebody else in another place or situation, engaging the brain’s ability to imagine plans for handling threats.
Image: geralt
5. Possibility Over Probability
How do you train people so that you produce leaders and not just managers? Focus your training on expanding their ability to think not in probability but in possibility.
What’s the difference? Probability is calculated or based from past events while possibility assumes an event that hasn’t happened could happen. Probability is employed by statistics and computer AI while possibility empowers story and imagination. With a fundamentally different mental process involved, possibility engages original thinking, enterprise, and initiative: key mental qualities of entrepreneurs and leaders in general.
You can expand your sense of possibility by stimulating your brain’s premotor cortex and boosting your practical imagination with realistic tales of make-believe. The Wright brothers read the creative works of Charles Dickens and Mark Twain, while Special Operators prefer novels set in the near future or in a different culture.
Image: Katrin Bolovtsova
Cascade Strategies and Primal Intelligence
Cascade Strategies has not only been advocating for the “appropriate use of AI” but has also been consistently pushing for the appreciation of high-level human thinking, especially when it comes to market research. This research on primal intelligence underscores our stance on the irreplicable and inimitable merits of human intelligence. We believe there are values and experiences humans bring to the table that AI simply cannot match. We’ve always believed that breakthroughs in market research can only be unlocked only with the proper application of human intelligence. To learn more about how our thinking can help you with your brand development and market research needs, please contact us here.
Additional Reading:
Why AI Will Never Defeat Primal Intelligence
‘Primal Intelligence’ Review: Why Brains Are Better
Featured Image: johnhain
Top Image: geralt
Sep
Some years ago, Publix Supermarkets allowed us to conduct qualitative and quantitative research for them. The result was a key brand insight about a kind of consumer called the Reluctant Shopper. Despite the ironic name, this kind of consumer hewed more closely to the shopping experience Publix offered than to competitive shopping experiences. The campaigns built around the Reluctant Shopper helped Publix weather the storm of competition from well-heeled operators like Walmart. Winn-Dixie, a much larger chain with many more stores, perished.
We recently asked Gemini to review the same dataset and report on it. Gemini provided a sparkling and quite accurate report on the data but perceived nothing about the Reluctant Shopper. This is something to bear in mind if you’re a consultant advising a brand on how to thrive: perspicacity counts.
There’s a kind of intelligence AI can’t reach. It has dimension, soul, and human inspiration. We’d do well to remember this as we pour more datasets into the maw of AI. If you’re a consultant and need perspicacity, you might want to contact Cascade Strategies. We can help you see things AI can’t see.
Image: Harrison Keely
Aug
Can Synthetic Respondents Take Over Surveys?
jerry9789 0 comments artificial intelligence, Burning Questions
What Are Synthetic Respondents?
AI has increased operational efficiency by streamlining knowledge bases and shortcutting processes so it’s no surprise people and companies are looking for more ways for its application. For market research, one curious consideration is whether it could take over surveys, essentially by replacing actual respondents with synthetic respondents.
Also known as virtual respondents, digital personas, and Virtual Audiences, synthetic respondents are individual profiles constructed by Large Language Models (LLMs) from real or simulated data. Ideally, the data or descriptions used to generate these profiles come from previously conducted surveys and are combined with individual-level demographics, attitudes and behaviors.
Using these synthetic respondents over real respondents could benefit your research with speed, accuracy and cost savings, at least according to their advocates. Basically, you just need to conduct one survey and from the profile description or data you gathered from the actual respondents, you’re able to generate results from the constructed individuals over and over for succeeding studies and research.
Testing Synthetic Respondents
While synthetic respondents could accurately represent real respondents, relying exclusively on the results from these AI-based individuals may not be entirely beneficial. A webinar hosted by Radius Global took a closer look at the potential of AI-generated synthetic respondents through three case studies of quantitative concept testing, quantitative communications research, and qualitative communications research.
Aggregate results for the concept tests involving game controllers indicate somewhat strong similarities between the results of the real and synthetic respondents. This extends to the results from the quantitative communications research when it comes to the believability of statements on the benefits of milk, although there were some differences. The differences were much more pronounced though when it comes to surprise over the same statements, and there was incongruence when considering how each statement could possibly increase milk consumption.
The qualitative communications research was seeking in-depth insights into women’s needs, perceptions, and preferences for running a race or marathon, with the feedback gathered meant to be used for creative content. Personas were constructed from the profiles of six women aged between 18 and 64 years old who ran at least once in an average week. They had an LLM assume each persona to allow a comparison between findings from real participants to synthetic respondents.
They found that while both real and synthetic respondents have somewhat similar responses when it comes to functional aspects as goals for women in general pursuing fitness, the AI responses lacked emotional expressions. There are also little differences in the synthetic respondents’ responses despite having different profiles, and there was even a lack of subtle differences.
As for concerns among women who are aspirational marathon runners, the synthetic personas were consistent in their responses while the real respondents provided more nuances, variety, and perspectives more prevalent among women.
Synthetic Respondents vs. Real Respondents
Synthetic respondents appear to be useful if you’re evaluating existing ideas and concepts; however, if you’re looking for “breakthroughs” or essentially new insights you would’ve never arrived at had you not performed the case study or research, you would need to engage with real respondents, relying exclusively on their results or combining them with that of synthetic respondents. Yes, there could be cases where synthetic respondents could be used, but the results must be extensively validated. It would also require increasing the efficiency of how data used to construct these individuals are analyzed in addition to enhancing the quality of the data and information gathered for these profiles through thorough screening, intelligent probing, and smart choice models.
There is a place for synthetic respondents in market research, but as another tool in a researcher’s toolbox. They won’t be taking over surveys or replacing actual respondents wholesale anytime soon, it seems, as that elusive “Eureka” moment researchers seek is inherently tied to the nuances and perspectives of human emotion and experience you simply can’t construct.
Photo courtesy of Pavel Danilyuk
Aug
How Excellent Market Research Benefits Manufacturing Companies
jerry9789 0 comments artificial intelligence, Brandview World, Burning Questions
More than just an invaluable asset, market research is an essential tool to any company — or industry, for that matter. From identifying and tailoring your messaging towards your ideal customer with consumer research to understanding the competition and strategically positioning your company with competitor research, great market research grants you and your firm vital and actionable insights that would prove key to the success of your marketing efforts. In addition, excellent market research helps companies manage risks effectively and efficiently, as well as aid in measuring the progress and success of projects or even your company as a whole.
The manufacturing industry not only stands to benefit from high quality market research, it’s crucial to its continued growth, innovation and evolution, especially in an industrial landscape that’s continually transforming with technological advancements along with global, cultural and attitudinal shifts. From the steam and watered-power machines of the First Industrial Revolution to the expansion of network systems and electrification of the Second Industrial Revolution to the information technology focus of the Third Industrial Revolution (the Digital Revolution), the manufacturing industry’s evolution continues on in its latest iteration with Industry 4.0, harnessing modern and emerging technologies to facilitate the merging of the physical and digital realms.
And on that note, we take a look at 10 manufacturing industry trends today that exceptional market research can help manufacturers navigate and adapt to as the Industry 4.0 era unfolds.
Image: Livia Wong
1. Smart Factories
Perhaps the best representative of things to come with the Fourth Industrial Revolution, smart factories utilize Industry 4.0 technologies to streamline and improve operational efficiency, quality and maintenance while reducing errors and waste. Older machines are gradually giving way to newer counterparts built with onboard sensors, monitoring tools, interconnected systems and in some cases, machine learning capabilities.
With more and more manufacturing companies transitioning to automated facilities plus the decreasing costs to acquire sensors, software and equipment, manufacturers big and small are all the more incentivized to join the smart factory revolution — if they haven’t yet — to not only keep up with the competition and the changing times but also take advantage of the irresistible operational benefits.
2. Artificial Intelligence
AI has disrupted multiple industries, and manufacturing isn’t immune to it; in fact, it has openly and quickly embraced and adopted it, seeing all the tremendous advantages it brings with its data-crunching prowess and advanced decision-making insights to the core aspects of smart production, quality control, supply chain management, servicing and maintenance, along with enhancements to processes, products and services.
More and more manufacturing companies are finding success and are able to scale competitively when strategically leveraging AI in automating and streamlining their operations, especially when it’s combined with other contemporary technologies. But perhaps the best combination of them all is when AI is combined with human creativity and experience, opening doors for innovation and further advancements.
3. Digital Twins and Data-driven Predictive Maintenance
If smart factories are revolutionizing manufacturing operations, digital twin technology and data-driven predictive maintenance are transforming equipment maintenance and operational downtimes. By utilizing virtual replicas or “digital twins” of equipment and devices, manufacturers can simulate equipment performance under different scenarios and situations to gain valuable insights. These data-driven insights would help manufacturing companies anticipate or predict when an equipment would need servicing or maintenance, reducing or eliminating unexpected downtimes and equipment breakdowns. At the same time, maintenance costs are reduced, material cost savings are increased, and the usage or life cycle of the asset is optimized.
And digital twins aren’t limited to physical assets only, as they can also replicate systems or processes to test new ideas or optimize existing ones before applying any changes or updates to live production. The digital twins approach not only helps minimize resource consumption and waste, but also improves business decisions by backing them with data-driven insights.
4. Other Notable Industry 4.0 Technologies (AR/VR/Robotics)
Arising from the realms of gaming and entertainment, augmented reality (AR) and virtual reality (VR) have now begun revolutionizing manufacturing. Product design, quality control, maintenance and repairs, remote collaboration and even employee training — all these are being impacted and improved by the application of AR and VR technology.
Robotics may have been around longer than AR and VR but modern robots are far more advanced than their forerunners programmed for repetitive tasks. Thanks to AI and automation software, today’s robots are autonomous, collaborative, and far more capable of performing complex tasks and operations.
These technologies in conjunction with AI make it possible for manufacturing operations to be run remotely or without any operator onsite. And as these technologies grow popular to become widely used and accepted, we might even see more fully automated manufacturing facilities called “dark factories” be developed in the near future.
5. Sustainability and Carbon Neutrality
No other industry is perhaps under greater pressure to pursue sustainable processes and carbon-neutral practices than manufacturing. Contracts with governments and institutions and eventually commercial clients require compliance with sustainability efforts while more and more consumers are supporting reputable, sustainable brands.
The manufacturing industry itself is advancing sustainability efforts by developing and employing green software to aid with carbon neutrality, waste reduction, and energy consumption optimization. Renewable energy integration in physical locations is also being embraced, while cloud infrastructure solutions and carbon capture technology are being viewed for their potential. Working toward sustainable practices and carbon neutrality isn’t without its own rewards for the business, as it’s been found that eco-conscious manufacturing companies are able to significantly reduce costs and improve efficiency with their sustainability efforts over time.
6. Reshoring
Reshoring refers to returning production operations back to the manufacturing company’s home country from overseas locations. This trend was a result of recent global events disrupting supply chains. It benefits the manufacturer with shorter supply chains, better quality control, faster market delivery, domestic economic boost, and improved sustainability efforts.
However, reshoring isn’t a decision a manufacturing company should take lightly, as one would need to factor in labor costs, skill, infrastructure, and more, as smaller-scale firms might find it more costly to operate domestically than overseas.
7. Decentralized Manufacturing
Another approach to improving supply chain resilience from disruptions is decentralized manufacturing, which is the distribution of production activities across multiple locations in the form of microfactories. Additional benefits of decentralized manufacturing include reduced logistics costs and quicker response times to local market demands.
While the coordination of multiple microfactories and achieving standardization across all sites may prove to be challenging, Industry 4.0 technologies can aid in making decentralized manufacturing more accessible and manageable through improved transparency and responsive production models.
8. Tapping into B2C
With the ever-growing popularity of e-commerce, manufacturing companies can now bypass the traditional lines of retailers and distributors and sell directly to the end consumer. Smart factories, 3d printing and additive manufacturing also make it possible to offer customized products based on a customer’s preferences. The advent of new manufacturing technology or the evolution of existing ones would only open up more opportunities for enterprising manufacturers looking to connect further with consumers.
9. Cybersecurity
The manufacturing industry’s increasing digitization has made it an irresistible target for cybercriminals, exploiting vulnerabilities with cyberthreats and attacks ranging from ransomware to industrial espionage or even supply chain and/or operational disruption. It’s no surprise then that cybersecurity has joined the elite group of paramount concerns for any manufacturing company.
Measures include multi-layered security, secure-by-design, zero-trust architecture, AI-driven threat detection, advanced encryption, and regular updates and patches, as well as employee cybersecurity training. Cybersecurity is more than just data protection or an IT concern now for manufacturing companies as it safeguards their production, finances, integrity, and reputation.
10. The Workforce of Industry 4.0
In spite of all the exciting technologies emerging in the Fourth Industrial Revolution, the manufacturing industry is experiencing widening skills gaps and labor shortages. These difficulties could translate to a loss in revenue of $1 trillion if approximately 2.1 million jobs aren’t filled in by 2030.
To address these challenges, manufacturing companies could start with reviewing all of their production processes from the ground up and assessing areas that could be improved by a highly skilled and competent workforce. Yes, the manufacturing industry is moving towards automation and advanced technologies but it can’t truly innovate without human creativity and experience.
Manufacturing companies are planning to offer higher wages by at least 3%. At the same time, they’re investing in training programs to reskill or upskill existing employees for the Industry 4.0 work environment. Incorporating new manufacturing technologies like AI and AR in these training programs can help employees not only learn faster, but also give them familiarity and first-hand experience with these digital trends. The same technologies can also be deployed for improving employee health and safety at the workplace.
Other approaches that manufacturing companies can consider taking range from partnering with local educational institutions in creating curriculums tailored for manufacturing careers, diversifying the recruitment pool, and creating appealing work environments which offer flexible schedules, potential promotions, and career development.
Image: InWay
How Cascade Strategies Can Help Manufacturing Companies with Advanced Market Research
Hewlett-Packard wanted to discover what feature-price combinations in high-frequency oscilloscopes would optimize profit. We conducted an advanced conjoint study followed by AI-based modeling to evaluate sales scenarios. Out of hundreds of attributes, we found the qualities below to be most salient. Using the most salient attributes as predictive vectors, we developed an AI model to determine the unique price-feature combinations that would produce the most profit and presented the top 3 to Hewlett-Packard.
We’ve highlighted 10 manufacturing trends shaping the future of the manufacturing industry in this selection but there are actually more out there that we didn’t touch on. And as new technologies arise, existing ones improve, and other industry changes or shifts happen, more trends are sure to emerge.
Regardless of trends, you can be sure to count on market research to help you determine the best approach to leveraging new technologies or guide business decisions to ensure your manufacturing company stays competitive and relevant. Would it be beneficial or costly for your company to go with a dark factory over a smart factory? Which of your AI-driven production processes would benefit from human supervision and input? Are your sustainability efforts being seen and appreciated by your consumer base or do you need to do more?
Between reshoring and decentralized manufacturing, which one would work best for your company? Are you able to expand into B2C? Are your training programs effective in making your employees understand and uphold cybersecurity commitments?
As with any AI-powered or data-driven Industry 4.0 technology, the high quality market research Cascade Strategies provides grants valuable and actionable insights into the operations, perception, and potential of your manufacturing company. If you would like to find out more about how Cascade Strategies can help your manufacturing company thrive in the Fourth Industrial Revolution, please contact us here.
Featured Image: Hyundai Motor Group
Top Image: Foto-Rabe
Jun
How Great Research Helps Financial Services Companies
jerry9789 0 comments artificial intelligence, Brand Surveys and Testing, Brandview World, Burning Questions
From maintaining loyalty and fostering customer relationships to focusing marketing messages on the most profit-optimal consumer, great research is helping Financial Services companies identify not only their best customers and prospects but also their needs and why they prefer their brand over others. This is done through a high-quality segmentation study and persona development, which break a company’s market into different groups so that different strategies for marketing to these groups can be leveraged. The main reason a company wants to complete market segmentation research is so they can gain actionable insights, like how to sell more of their product or services.
Take for example, Banner Bank for whom Cascade Strategies developed a brand model which identified “Strivers” as the primary segment they should focus on. The bank initiated special promotions and appeals featuring the products of greatest interest to Strivers. A Striver-specific ROI program was developed to measure the degree of program success. Modeled indices were used to set Striver product targets by branch. After 2 years of activity, Banner Bank exceeded all key Striver product targets system-wide.
Read about our approach to high-quality brand development research here.
Another example is the case of Capital One where they needed help trying to identify the “persona” or psychographic type most interested in adopting a certain mobile app for personal investing. We conducted in-person depth interviews with “mobile-minded consumers.” We also conducted an unpacking session with Capital One staff where individual staff members were given assignments to review videos and be prepared to discuss key traits and behaviors of respondents, such as outlooks, investing styles, goals, worries, needs, plans, and so forth.
We identified that the “Empath” is the most interested in adopting a certain mobile app for personal investing. The “Empath” persona is fairly immersed in pragmatic thinking and probably best understands the possibilities for “thinking” or guidance apps, allowing Capital One to focus their brand campaign effort on the needs of this psychographic type. The net result was a highly successful new product introduction.
Read about our approach to segmentation studies and the development of brand personas here.
Image: Cottonbro Studio
“But wait, can’t AI do this?” you may ask. While there is a faddish and hype-driven tendency to turn quickly to AI for short-cuts in market research, AI cannot yet fully replicate the deep interpretive and intuitive skills of the human brain, especially the right brain (the nonrational side). Moreover, effective AI deployment requires human supervision and involvement as final arbiter of how the outcomes will be leveraged.
As you can see, market research results as good as the examples above come from human-centered thinking, the kind that allows brands to break past ordinary bounds and achieve true excellence. It’s this kind of extraordinary thinking that Cascade Strategies has consistently provided a long list of US and international clients for 33 years.
Feel free to reach out to us to discuss your needs at https://cascadestrategies.com/contact-us/
info@cascadestrategies.com
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