Jul
What To Make Of ChatGPT’s User Growth Decline
jerry97890 comments artificial intelligence, Burning Questions, Uncategorized
The Beginning Of The End?
More than six months after launching on November 2022, ChatGPT recorded its first decline in user growth and traffic in June 2023. Spiceworks reported that the Washington Post surmised quality issues and summer breaks from schools could have been factors in the decline, aside from multiple companies banning employees from using ChatGPT professionally.
Brad Rudisail, another Spiceworks writer, opined that a subset of curious visitors driven by the hype over ChatGPT could’ve also boosted the numbers of early visits, the dwindling user growth resulting from the said group moving on to the next talk of the town.
The same article also brings up open-source AI gaining ground on OpenAI’s territory as a possible factor, thanks to customizable, faster, and more useful models on top of being more transparent and the decreased likelihood of cognitive biases.
Don’t Buy Into The Hype
But perhaps the best takeaway is Mr. Rudisail’s point that we’re still in the early stages of AI and it’s premature to herald ChatGPT’s downfall with a weak signal like decreased user growth. For all we know, this is what could be considered normal numbers, with earlier figures inflated by the excitement surrounding its launch. Don’t buy into the hype is a position we at Cascade Strategies advocate when it comes to matters of AI.
The advent of AI has taken productivity and efficiency to levels never seen before, so the initial hoopla over it is understandable. However, we believe people are now starting to become a little more settled in their appraisal of AI. They’re starting to see that AI is pretty good at “middle functions” requiring intelligence, whether that be human or machine-based. But when it comes to “higher function” tasks which involve discernment, abstraction and creativity, AI output falls short of excellence. Sometimes mediocrity is acceptable, but for most pursuits excellence is needed.
Excellence Achieved Through High Level Human Thinking
To illustrate just how AI would come out lacking in certain activities, let’s consider our case study for the Gargoyles brand of sunglasses. ChatGPT can produce a large number of ads for sunglasses at little or no cost, but most of those ads won’t bring anything new to the table or resonate with the audience.
However, when researchers spent time with the most loyal customers of Gargoyles to come up with a new ad, they discovered a commonality that AI simply did not have the power to discern. They found a unique quality of indomitability among these brand loyalists: many of them had been struck down somewhere in their upward striving, and they found the strength and resolve to keep going while the odds were clearly against them. They kept going and prevailed. The researchers were tireless in their pursuit of this rare trait, and they stretched the interpretive, intuitive, and synthesis-building capacities of their right brains to find it. Stretching further, they inspired creative teams to produce the award-winning “storyline of life” campaign for the Gargoyles brand.
All told, this is a story of seeking excellence, where hard-working humans press the ordinary capacities of their intellects to higher layers of understanding of a subject matter, not settling for simply a summarization of the aggregate human experience on the topic. This is what excellence is all about, and AI is not prepared to do it. To achieve it, humans have to have a strong desire to go beyond the mediocre. They have to believe that stretching their brains to this level results in something good.
How To Make “Appropriate Use” of AI
But that is not to say that AI and high level human thinking can’t mix. The key is to recognize where AI would best fit in your process and methodologies, then decide where human intervention comes in. This is what we call “Appropriate Use” of AI.
Take for example our case study for Expedia Group and how they engage with millions of hospitality partners. Expedia offers their partner “advice” which helps them receive a booking over their competitors. With thousands of pieces of advice to give their partners, they utilize AI to filter through all those recommendations and present only the best ones to optimize revenue. Cascade Strategies has helped them further by creating a tool called Scenario Analyzer, which uses the underlying AI model to automate the selection of these most revenue-optimal pieces of advice.
Either way, the end decision on which advice to go with (or whether they accept any advice at all) ultimately still comes from Expedia’s partner, not the AI.
Copyright ClaudeAI.uk
A Double-edged Sword
As you can see with ChatGPT, it’s easy to get carried away with all the hype surrounding AI. At launch, it was acclaimed for the exciting possibilities it represented, but now that it has hit a bump in the road, some people and outlets act as if ChatGPT is on its last leg. Hype is good when it’s necessary to draw attention; unfortunately in most cases, it sets up the loftiest of expectations when good sense gets overridden.
This is why we think a sensible mindset is the best way to approach and think about AI — to see it for what it really is. It’s a tool for increasing productivity and efficiency, not the end-all and be-all, as there is still much room for excellent human thinking backed by experience and values to come into play. Our concerns for now may not be as profound and dire as those expressed by James Cameron, Elon Musk, Steve Wozniak and others, but we’d like to believe that “appropriate use” of AI is the key towards better understanding and responsible stewardship of this emerging new technology.
Jun
Kyle Byers of Exploding Topics has written recently about nine key trends in the CPG industry. We’d like to focus on those nine trends below, add one of our own, and talk about how market research has responded to these trends.
From food and drinks to apparel and cosmetics, consumer packaged goods (CPG) are a vital part of everyday life for most consumers and households. Since these products are mostly disposable, there is a regular need and consistent demand for replenishment or replacement, forming the basis for a competitive environment for all brands.
The CPG market has significantly and steadily grown despite the competition and even more so with the COVID-19 pandemic. It was valued at $2.06 trillion in 2021 and with a compound annual growth rate (CAGR) of 3.5%, it is estimated to reach $2.8 trillion by 2030.
In addition to the pandemic, new technologies and consumption habits have contributed to the rapidly changing face of the CPG industry. From direct to consumer (DTC) to sustainability to product personalization, we’ll take a closer look at 10 of the most important trends impacting the CPG industry right now.
1. Legacy CPG Companies Join DTC
DTC online sales growth in 2022 is estimated at $138.03 billion, so you can understand why CPG industry stalwarts couldn’t ignore the DTC wave any longer, joining the trend three ways. First by acquiring competitors, like Unilever who counts Dollar Shave Club, Schmidt’s Naturals and UK-based Graze among its many DTC acquisitions since 2015. Second, they are launching entirely new brands, like Procter & Gamble’s EC30 which is an eco-oriented brand of dissolvable, solid-form soaps and cleaning products. And thirdly, by launching DTC sites like PepsiCo’s PantryShop.com and Snacks.com. These sites went up during the Coronavirus pandemic and PepsiCo nearly doubled their DTC sales in Q3 2020.
2. CPG Startups Emerge to Make Their Mark
Without a middleman and the need for retail shelf space, the DTC business model fosters competition. Many DTC startups use a subscription model to generate steady and recurring revenue, allowing them to take a bite out of the market at the expense of traditional CPG brands. For example, Gillette saw its 70% share of the US razor market go down under 50% within a decade due to competition from Dollar Shave Club and Harrys.
3. More Retailers Launch Private Label Brands
Availability issues during the pandemic have partly contributed to the popularity of private-label products. With 65% of shoppers saying they’ll switch brands if prices are too high, being an affordable alternative also helps private-label brands gain ground in the market. Think Amazon’s private-label clothing brand Goodthreads, which is competing against big brands H&M, Levi’s, and Uniqlo. Better margins and direct control over product development have also convinced retailers like Walmart and Kroger to launch their own consumer brands.
4. Faster and Easier Delivery Than Ever Before
With the pandemic pushing e-commerce into overdrive, access to faster and easier delivery options is becoming a key point in purchasing decisions, according to 68% of shoppers in a recent survey. 85% of online shoppers say they will search for someplace else if the delivery time is too long, while 30% of consumers expect same-day delivery. This need for speed has given rise to dedicated fast-delivery CPG retailers like GoPuff who are offering to deliver not in days or even hours but in minutes.
Copyright Pixabay (Pexels)
5. Focus on The Omni-Channel CPG Shopping Experience
More and more CPG brands and retailers are pushing for omni-channel shopping, allowing a smooth and seamless purchasing experience across different devices, or even between in-store and online. To illustrate: Sephora enhanced in-store experience by letting customers access their online shopping lists called “Loves” on large screens inside stores with the help of in-store tablets. Compared to single-channel brands, CPG companies that utilize at least three retail channels have shown a 287% higher purchase rate.
6. Expanded Omni-Channel CPG Marketing
CPG companies are also leveling up their marketing with a more omni-channel approach. TV ads, product placements, PR, and digital marketing methods like PPC ads, which have proven their effectiveness time and time again, are now joined by the new kid on the block: influencer marketing. Even with as few as 1,000 social media followers, “micro” and “nano” influencers are able to deliver results for CPG brands tapping into these smaller, more focused niche experts.
7. Sustainability and Clear Brand Values Are More Important Than Ever
Another thing that the pandemic accelerated is the rise of green consumerism. Many consumers, mainly Gen Z, now avoid brands that don’t align with their stance on the environment and other sustainability issues. 53% of Internet users have expressed intentions to switch products or services if a company violates their personal values or they weren’t sustainability-focused.
8. Self-Care Product Demand Is Rising
The pandemic also brought to the fore holistic self-care, where consumers use multiple products to optimize their health and wellness. Skincare products are now outselling makeup, thanks to millennials who spend more on self-care than any previous generation, and CPG brands like CeraVe and DRMTLGY who have jumped at this opportunity.
Products containing cannabidiol, also known as CBD, were not legal nationwide in the US until 2018. Now, CBD products are a rapidly growing part of the self-care category, with sales at $4.6 billion in 2020 and expected growth of over $16 billion in 2026.
9. Growing Popularity of Product Personalization
Offering a personalized experience through product quizzes can boost e-commerce conversion rates while building direct, one-to-one relationships with customers. This was the goal behind beauty brand Tatcha offering personalization via its Ritual Finder tool.
In fact, 71% of consumers expect personalized interactions according to McKinsey. Conversely, 76% get frustrated when they don’t get them. 60% of consumers say they’ll become repeat customers after a personalized shopping experience.
Copyright Polina Tankilevitch
10. Gen Z Is Becoming a Major Part Of The Consumer Market
We’ve hinted this earlier, but this trend is just as impactful as the others, especially with the $143 billion of spending power that allows Gen Z to make up 40% of the entire global consumer market. With the shift to digital commerce, companies need to find creative and effective ways to tap into this massive demographic group and understand their buying patterns, especially with regard to social media. Did you know that 97% of Gen Z purchasing decisions are heavily influenced by social media, with 48% of consumers now likely to purchase directly from TikTok?
How Market Research Has Responded to These Trends
Based on these trends, we can assume the CPG market is moving into a personalized and multi-channel direction where leading brands are recognized not only for their competitive price points but also for their value propositions. There are four key ways in which the Market Research industry has responded to these trends and provided newer and more incisive tools for understanding consumer behavior.
1. The Shift from Perceptual Research to Transactional Research
Pandemic restrictions have long been lifted and brick-and-mortar locations have reopened, but there’s no denying that consumers have embraced e-commerce and the convenience it offers. Consumers will still appreciate the opportunity to test products in person with in-store shopping, but when there isn’t such a necessity, e-commerce becomes the go-to sales channel. This is especially true for those who have already established loyalty to a particular brand. Following this trend, there’s been a seismic shift away from perceptual research dealing with the in-store experience to customer research dealing mainly with degree of satisfaction at certain touchpoints in the e-commerce funnel.
Brand and Insights Managers increasingly seek hard metrics to support specific e-commerce initiatives, including product depictions on small and large screens, comparative text descriptions, active displays involving motion, sound, and animation, features such as reviews, promotion codes, side-by-side comparisons, visual try-it-on-yourself options, and options for shipping, group discounts, buy-now-pay-later offers, and repeat-purchase and subscription-purchase offers. While perceptual research can guide them in a general way, the degree-of-satisfaction metrics at these touchpoints in the shopping experience deliver more hard value to the decision maker who is tasked with determining the effectiveness of e-commerce marketing methods.
2. From Qualitative to Quantitative Methodologies
Another development is the shift away from common qualitative methodologies to quantitative methodologies. For example, years ago there was much more exploration of the spatial shopping experience via in-person focus groups, shop-alongs, visual diaries, ethnographies, and the like. A good deal of that has transitioned to quantitative research using direct metrics such as scalar degree-of-satisfaction measures delivered via web and text.
Fundamentally, the need-to-know among contemporary Brand Managers and Insights Managers is not so much “how does my brand’s expression attract consumers?” as it is “how satisfied are consumers with their experiences with my brand?” The first concern was well served by a variety of qualitative methodologies. While it’s still an active concern, it has declined somewhat, while the second concern has become white-hot. Quantitative methodologies on the whole do a better job of serving this second concern than qualitative methodologies do, especially given that brand “experiences” in the current day are less spatial and more virtual. This makes it easier to ask a consumer a transactional question such as “how did it go for you?” while the consumer’s mind is still fresh on the subject.
3. Less Packaging Research
There was a 30-year fascination – even obsession in some cases – with intriguing methodologies in packaging research, pioneered by big packaged goods companies like P&G, PepsiCo, Unilever, etc. These included eye tracking, neurometrics, GSR measurement, EKG measurement, facial coding, Virtual Reality and Augmented Reality simulations, million-dollar “cave” immersive environments, and more. These methodologies are still very much alive, but their application is different. At one time they were widely applied to virtually any inquiry associated with packaging or any stage in the PLM journey: product ideation, prototyping, functional testing, price/value research, comparative attribute research, virtual or physical shelf testing, test marketing, advertising, and even compliance. Now the applications are more narrowly focused on specific research outcomes, and maybe that’s a good thing.
For example, the fragrance people still love biometric methods, and the website testing people still love eye tracking. The people doing that research have specific research outcomes in mind, and these outcomes are often metric rather than perceptual. Are psychic arousals produced by certain aromas? Where do the eyes go when looking at a web page? These questions can be answered metrically via the biometric data. And these are experimental venues where the brain-body response can legitimately be expected to be driven by environmental stimuli – at least enough to be measured by instruments.
As a result, there’s less packaging research in the packaged goods business. The truth is that there’s less keen interest among Brand and Insights Managers in whether the packaging is compelling in a spatial retail environment. There’s more interest in the transaction itself. Brand and Insights Managers want to learn less about the motivations and behaviors involved in wanting the product and more about the motivations and behaviors involved in buying the product.
4. Systems as a Source of Insight
There is also now a greater focus on systems as a source of insight. For years, market research was the primary source of brand insight, so humans were involved by definition. Now the dominant sentiment is that insights come from machines, and humans tend the machines.
Marketing decision-makers are often heavily engaged in the determination of which analytics platform(s) will be implemented at their company, installing the platform and training users, maintaining the security of that platform, licensing issues, system upgrades, patches, maintenance advisories, hardware issues, and more. None of this has anything to do with deriving insights for the brand.
Copyright PhotoMIX-Company
The thought pattern here is that this time is well spent because insights arise from machines, not human effort. A human-focused effort to produce brand insights is still occasionally used, but it’s sort of like a landline phone: interesting but not contemporary.
Brand and Insights Managers in the current day have a passing interest in human-focused market research when the machines cannot produce the insight or do a poor job of it. An example would be the development of a vibrant persona for the brand, or a comprehensive market segmentation scheme involving all competitive brands. Systems and platforms can actually do this (including AI-assisted systems and platforms), but their outcomes are invariably suboptimal. The systems are recursive, and they therefore regurgitate the best-available summarizations of the data inputs they receive. Since they don’t have the intuitive, interpretive, and synthesis-building power of the human brain (especially the right brain), they cannot extrapolate to the level of excellence in their outcomes. In other words, they render mediocrity permanent.
It takes a brain strain – a smart person or two striving with higher intuitive/interpretive layers of thinking and understanding to discover solutions that cannot be reached by simply summarizing human experience on a topic – to produce excellence in these outcomes. The greater unanswered question is whether Brand and Insight Managers want excellence. These managers may be a little more system- and process-driven in their thinking, and they therefore may prefer a large volume of mediocre solutions rather than a single solution at the level of excellence.
How We Approach These Issues at Cascade Strategies
There’s currently a raging debate about the appropriateness and utility of applying AI instruments, especially ChatGPT, to marketing questions typically answered by market research and discussed in this article. Our point of view on this topic can be summarized by the term “Appropriate Use.”
Clearly, there’s big first-party data involved with these CPG trends, especially with DTC. While AI-powered analysis and interpretation of this big data can efficiently and quickly produce objective and accurate results, there is a space that AI is unable to touch and thus falls short of effectively leveraging data to make informed decisions. This area is where the intuitive, interpretive, and synthesis-building capacities of the right brain excel. Here data-driven decision-making could potentially access a different yet extraordinary set of insights, themes and recommendations anchored by human values and experience.
But sophisticated solutions at this level – the level of excellence – might remain undiscovered since machines don’t have the ability to relate to the data on an intuitive and interpretive level. A more enlightened “Appropriate Use” concept, which elevates the role of human inspiration and agency, could lead to more innovative and creative ideas about how CPG companies can optimize operations, forecast sales, develop products, enhance marketing strategies, focus on the most profit-optimal consumers, and develop the most compelling messages for those consumers.
For 33 years Cascade Strategies has demonstrated the capacity to maintain this kind of machine-versus-man balance for leading worldwide companies and thus produce excellence in thinking and outcomes. Please see examples of our higher thinking for clients at https://cascadestrategies.com.
Jun
Appropriate Use of AI
jerry97890 comments artificial intelligence, Brand Surveys and Testing, Brandview World, Burning Questions
The Rise Of AI
Believe it or not, Artificial Intelligence has existed for more than 50 years. But as the European Parliament pointed out, it wasn’t until recent advances in computing power, algorithm and data availability accelerated breakthroughs in AI technologies in modern times. 2022 alone made AI relatively mainstream with the sudden popularity of OpenAI’s ChatGPT.
But that’s not to say that AI hasn’t already been incorporated in our daily lives- from web searches to online shopping and advertising, from digital assistants on your smartphones to self-driving vehicles, from cybersecurity to the fight against disinformation on social media, AI-powered applications have been employed to enable automation and increase productivity.
The Woes Of AI
However, the rise of AI also brings concerns and worries over its expanding use across industries and day-to-day activities. Perceived negative socio-political effects, the threat of AI-powered processes taking over human employment, the advent of intelligent machines capable of evolving past their programming and human supervision- that last one is mostly inspired by the realm of science fiction but a plausible possibility nonetheless. A more grounded and present-day concern, however, is the overreliance and misuse of Artificial Intelligence.
Copyright geralt (Pixabay)
Sure, AI is able to perform a variety of simple and complex tasks by simulating human intelligence, efficiently and quickly producing objective and accurate results. However, there are some activities requiring discernment, abstraction and creativity, where AI’s approximation of human thinking falls short. Cognitive exercises like these not only need high-level thinking but also involve value judgments honed and subjected by human experience.
The Expedia Group Case Study
This brings us to our case study for the Expedia Group, whose brand has around a million hospitality partners. Their goal is to increase engagement with their partners. For five years, Expedia grouped their lodging partners, which at the time were mostly chain hotels, with a segmentation model that helped guide their partner sales teams on how they should prioritize spending their time. This “advice” Expedia provides comes through marketing, in-product or through the partner’s account manager. When a partner takes advantage of Expedia’s advice, they usually receive the booking over their competitor.
Copyright geralt (Pixabay)
Now you can imagine that Expedia has thousands of advices or recommendations to give their partners. So how does Expedia determine which recommendation will most likely push their partner to act accordingly and produce optimal revenue?
If you answered “Use AI,” you’re on the right track. With thousands of possible decisions, Expedia just wants AI to filter the bad choices and boil it down to a few but good recommendations optimizing revenue. Expedia wants to use AI to help with decisions, but it doesn’t want AI to make that decision for them or their partners.
Copyright Seanbatty (Pixabay)
But now things are different- Expedia’s partners have grown to also include independent hotels and vacation rentals. So what if Expedia adds additional dimensions to the model allowing them to target partners with recommendations that would be best for their way of thinking and feeling, as well as appeal to their primary motivations as a property?
So that’s exactly where Cascade Strategies stepped in. We followed a disciplined process where — just to name a few things we’ve performed — we interviewed 1200 partners and prospects across 10 countries in 4 regions, converted emotional factors into numeric values and used advanced forms of Machine Learning to arrive at optimal segmentation solutions. Through this five-step disciplined process, we built them a psychographic segmentation formed into subgroups based on patterns of thinking, feeling and perceiving to explain and predict behavior.
Copyright Pavel Danilyuk
It “conceived the game anew” for Expedia Group (in a way suggested by Eric Schmidt and company in their book The Age of AI: And Our Human Future). Now seeing their partners in a different light, they needed to evolve their communications to reflect the new way they view them with the end goal of targeting which segment with which offer. The messages they would deploy should be very action-oriented based on what compels each segment.
Cascade Strategies then created an application called Scenario Analyzer to make this easy for people at Expedia. Its users could just ask the Scenario Analyzer what’s the optimal decision for certain input conditions. Basically, a marketer selects a target group and a region then the Scenario Analyzer answers by saying “You could do any of these six things and you’d make some money. It’s your call.”
If the partner does nothing, Expedia still makes about $1.5 million from these partners during a 90-day period, which is part of their regular business momentum. However, if the partner acts on the top-ranked recommendation which carries the message “Maximize your revenue potential by driving more groups or corporate business to your property,” it would result in about $140,000 more during the same period, which is about a 1% gain. While we couldn’t reach all partners with the same message, causing us to lower our expectations a little, we did slightly better than we expected to do in the end.
The “Appropriate Use” of AI
So what did we did do? We made “Appropriate Use” of AI. It neither made the decision nor guaranteed the money. It warded off the worst ideas and told us which recommendation was best in comparative terms.
Many people in marketing are treating AI as the next cool thing, so they want to jam it in wherever they can, whether it’s helpful or not. “Appropriate Use” stands against that, saying the best way to apply AI to marketing is for Decision Support to remain under human discretion and judgment, instead of letting AI actually make choices.
We think AI can at times be a very poor decision maker but a very good advisor. And we’re not alone as many others share our concern; to illustrate, 61% of Europeans look favorably at AI and robots while 88% say these technologies require careful management.
Another example to consider when thinking about just how important human intervention is when it comes to the “Appropriate Use” of AI is the topic of health care. As noted by frontiersin.org, the legal and regulatory framework may not be well-developed for the practice of medicine and public health in some parts of the world. Throwing artificial intelligence into the mix without careful and thoughtful planning might underscore or aggravate existing health disparities among different demographic groups.
And this is part of the reason why we believe in shaping AI with human values, including the dignity and moral agency of humans. The “defining future technology” that is AI is already proving to be a powerful tool for providing solutions and achieving goals, but it can only unlock levels of excellence, innovation and integrity when guided appropriately by human values and experience.
Other interesting reads:
https://www.wgu.edu/blog/what-ai-technology-how-used2003.html#close
https://www.investopedia.com/terms/a/artificial-intelligence-ai.asp
Jun
How Great Research Produces Great Campaigns
jerry97890 comments artificial intelligence, Brand Surveys and Testing, Brandview World, Burning Questions
Can AI Produce Your Marketing Campaign?
If you were given the task of developing a global communications campaign for a technical products company, would you let ChatGPT do it?
You might, especially if you noted that ChatGPT could churn out dozens of ads like the one above without paying art directors, copywriters, media professionals, or users of a Demand Side Platform.
But we wouldn’t. This is because it’s hard for AI to produce at the level of excellence, and excellence is what should be sought.
Seeking Excellence in Marketing Campaigns
The ad below is part of an award-winning and profitable “Mentor” campaign for HP. To arrive at this level, HP had to commission very perceptive researchers to spend time with worldwide HP engineers as well as engineers from other companies.
The researchers stretched the intuitive, interpretive, and synthesis-building capacities of their right brains to arrive at a subtle insight that AI would have great difficulty seeing: that HP engineers showed greater qualities of “mentorship” than other engineers. They thought it was important not only to conduct their own technical work, but to impart to others (typically younger people) what they were doing and why what they were doing was important.
It would be very hard indeed to stretch an AI chatbot (or other AI engine) to that deeper level of understanding about what a truly extraordinary ad should do to express the true meaning of a brand to people.
An example from the world of sunglasses
If you were given the job of developing a campaign for a line of sunglasses, you could probably get ChatGPT to produce a large number of ads like the following at little or no cost (with the exception of the cost of the talent).
But AI-produced ads fall short of excellence. AI simply cannot do the incisive interpretive work that humans can do to produce something better.
Researchers working for the Gargoyles brand of sunglasses spent time with those who preferred this brand and made a discovery about them that AI engines would have great difficulty seeing: that many Gargoyles wearers were upward strivers who were at first destined to fail, then turned things around with drive, verve, and strenuous effort.
They had a “storyline of life” worth admiring. To gain this insight, the researchers had to stretch the intuitive and interpretive powers of their brains. They could not simply rely on a summarization of prior human experience in producing ads about sunglasses.
Higher powers AI cannot reach
AI cannot stretch to this level of excellence. It cannot see broader levels of human experience that may be required to produce excellence, such as “how could sunglasses have anything to do with striving?” or “how could a life story of struggling ever be associated with sunglasses?” Hell, generative AI wouldn’t even think to inquire about a storyline of life. But humans can do that when their right brains are performing at a very high level.
The researchers in this case had to sweat the details a little more, spend quality time pondering the higher thematic levels, and drive their brains well beyond summarization to a more sublime expression of the true meaning of a brand to people.
This is the kind of work Cascade Strategies does on a daily basis. Please have a look at some other examples of higher thinking for clients at https://cascadestrategies.com.
People are catching on and speaking out
More people are seeing the chasm between the summarization of human experience that AI can provide and the excellence provided by the greater intuitive powers of the human brain, and they are speaking out about it. One example is Po-Shen Loh, a charismatic math coach who directly confronts AI, challenging his students to attack complex math problems at higher levels of understanding and interpretation than AI could ever provide.
But there are even more people who are discovering this excellence gap, and their voices will grow stronger.
Jan
Link to HP Case Study
jerry97890 comments Uncategorized
In a recent case study, HP wished to explore which paper package would be most successful at retail. By utilizing our innovative Nimbus Virtual Shopping System, Cascade Strategies has once again proven the power of market research.