Burning Questions
Mar
Can Psychographic Segmentation Help Financial Services Companies?
jerry97890 comments Brand Surveys and Testing, Burning Questions
Why Is Market Segmentation Effective?
By now you’ve most likely come across the idea that instead of using the “blanket” approach for marketing by using demographic or geographic data, you and your marketing goals can be better served by identifying your ideal customer and then focusing and tailoring your marketing campaign towards that consumer. This is achieved through a high-quality segmentation study and persona development, as was the case with the “Strivers” and “Empath” personas in our Banner Bank and Capital One case studies, respectively.
To sum it up, when we developed a brand model identifying “Strivers” as the primary segment Banner Bank should focus on, they were able to not only meet but also exceed all key Striver product targets system-wide after two years of implementing the program. Also, we recommended Capital One focus their brand campaign efforts for a personal investment mobile app on the pragmatic thinking type “Empath,” resulting in a highly successful new product introduction. You can learn more about these two case studies and how great research can help financial services companies here.
By recognizing your profit-optimal customer through market segmentation, a financial services company can effectively focus its marketing efforts and resources, optimizing or helping drive down costs, while at the same time engaging more efficiently with the consumer, enhancing satisfaction and loyalty.
But what if we tell you that you can also segment your financial services market so you target not one but different groups of customers?
Copyright geralt (Pixabay)
Single-segment Focus vs. Multi-segment Strategies
“Now hold on a minute,” you might say in your mind as you read that last line. “Didn’t you just say at the beginning of this that identifying your best customer is better than the ‘blanket’ approach?”
Yes, we did say that but no, this is no “blanket” approach. The main reason a financial services company wants to complete market segmentation research is so they can gain actionable insights into how to sell more of their products or services. With high-quality segmentation studies, breaking down your financial services market into different groups uncovers a variety of insights allowing you to craft and leverage different marketing strategies toward these segments. With this data-driven approach, customer segmentation helps financial services companies decide how to offer a customized journey to different kinds of consumers. It also provides the opportunity to tap into niche segments, which are usually smaller groups with considerable potential.
Think of it this way: instead of a blanket, what you have is a different set of marketing playbooks for your various customer segments. The blanket covers primarily the “who” of your market; each of your playbooks identifies not only “who” they are for but also deep dive into answering questions like “what” type of buyer behavior they have, “why” they behave this way, and “how” best to approach and engage them.
Copyright Gerd Altmann
Why Use Psychographic Segmentation?
Generally, four types of market segmentations can provide a financial services company with actionable segments: Geographic Segmentation, Demographic Segmentation, Behavioral Segmentation, and Attitudinal or Psychographic Segmentation. Out of these four, we’ll be focusing on Attitudinal or Psychographic Segmentation, as it is often considered the most useful way to segment an audience.
Attitudinal or Psychographic Segmentation separates customers by how they think and feel, their attitudes and values. Essentially, it aims to become a window into a buyer’s thought process. It is often considered the most useful segmentation approach because it provides the clearest actionable steps for a company to take as they try to target each segment.
Not only do you gain a deeper understanding of who your customer is, but your financial institution can map out the customer journey more effectively and efficiently with Psychographic Segmentation. It also allows the financial services company to recognize opportunities to offer different or new products/services in response to changes in consumer behavior. In addition to improved customer satisfaction and retention resulting from a client feeling valued, a financial institution that effectively engages with its consumers can also enjoy increased brand perception, helping with word-of-mouth and referrals as well as stand out from the competition.
Segmentation study data can come from several sources including survey data, observational data, public panel data, customer relationship management (CRM) databases, and even large-scale public databases such as Data Axle (previously InfoUSA), Experian, LiveRamp (previously Acxiom), and the like. It’s also possible to append demographic and behavioral data to your company’s house list. A financial services company is already sitting on a large pool of customer data; while it’s easy to go down the route of Geographic or Demographic Segmentation when analyzing all that information, converting those data into actionable insights with Psychographic Segmentation would lead to more personalized and meaningful buyer experiences.
Whether it’s for single or multiple segments, Psychographic Segmentation studies can tell you why a particular marketing or messaging approach to a particular segment is likely to be profitable. They can also tell you how to make adjustments toward more effective approaches when the standard approaches are not working. There are many financial services companies that tried demographic targeting and were disappointed with the results, then switched to psychographic targeting and found that their messaging strategies produced much higher rates of response and conversion.
Copyright Andrea Piacquadio
Cascade Strategies combines the most advanced AI and machine learning tools with market research expertise from over three decades of experience. Let us help your financial services firm convert your customer data into valuable, real, and actionable business insights. Don’t settle for a simple breakdown of your customer data; our experienced team strives for genuine breakthroughs by imaginatively interpreting all that complex quantitative segmentation data. We can also develop creative briefs that can be used for your advertising and website strategy based on the segments we discover, as well as tackle practical tasks, such as predicting the likely revenue to flow from campaigns directed toward specific consumer segments and measuring the actual monetary effectiveness of such campaigns. Contact Cascade Strategies today to see how our approach to segmentation studies can give you real business insights.
Nov
The Importance of Psychographic Segmentation in Brand Building
jerry97890 comments Brandview World, Burning Questions
What Is Psychographic Segmentation?
So you’ve completed your research on the demographics of your online perfume store and you’ve seen that women in their twenties in Seattle were your top buyers. That’s great, you thought as your mind started to work on the outlines of your next campaign targeted towards these women. However, you discovered upon going through the data one more time that your perfumes are just as popular with forty-something-year-old women in Las Vegas. And when you went to double-check again you discovered another group of women around 25 years old being ardent supporters of your perfumes, but this time they’re from New York.
Now how do you go about your marketing given that you would need to adjust it to target your top demographic? Sure, you’ve identified your best patrons as women between 20 and 50 years old but aside from the different locations, you’re not quite sure now what else sets them apart, which could poke holes in your messaging and cause it to fail to resonate with a number of them.
This exercise shows you the limitations of demographic-based marketing. Demographics answer the question “Who are your buyers?” but in order for your efforts to become more effective, you need to go deeper by answering “Why are they buying?” And this is where psychographic segmentation comes in.
Psychographic segmentation is the process of grouping consumers according to their motivations, goals, attitudes, opinions, beliefs and other psychological factors. It helps you better understand what drives purchase decisions. Not only does psychographic segmentation allow you diversify your marketing and reach out to different groups of consumers, it also allows you to create or customize products or services to cater to the varying needs of your buyers.
Copyright Elf-Moondance (Pixabay)
Why is Psychographic Segmentation Important in Brand Building?
Going back to the earlier scenario, you decided to reach out to your target demographic through an online survey, explaining it would help you understand them and serve their needs better. Based on the responses you received, you discovered that these women between 20 and 50 years old from different states appreciated the sweet-smelling but unique line of perfumes you’ve been selling at cost-effective pricing with efficient delivery times. Thus, the messaging of your next campaign highlighted the popularity of your sweet-scented perfumes, competitive pricing, and quick delivery. And the next time the opportunity presented itself, you even went as far as offering free delivery for a limited time.
Because you’ve used psychographic segmentation to break your market into different groups, you’ve also become aware of your other customer segments, which opened up marketing strategies you could leverage towards these subsets. Let’s say one of these groups was composed of regular clients who — although they didn’t buy as much as the earlier group we’ve discussed — you discovered frequently bought a certain perfume. Upon further research, surveys, and interviews of some of the members of this segment, you found that you’re the only online perfume shop that carried this fragrance. This then allowed you to branch out with new marketing which put a spotlight on the fact that this hard-to-find scent could only be bought at your online store, tapping into more potential customers falling under this segment. This also opened up more research on what fragrances your competitors didn’t offer but which your brand carried as well as the development of new unique perfumes that one wouldn’t find anywhere else online.
Psychographic segmentation not only gave you an understanding of the “why” behind purchases, it also granted you actionable insights on selling more of your products. With this data-driven approach, your brand is able to create different marketing playbooks for your various customer segments. The buyer’s journey would be different per customer, but in their minds there is only one brand that’s on top when it comes to a selection of unique scents at great prices and fast turnaround time for delivery.
Copyright Mohamed_hassan (Pixabay)
What Are Psychographic Segmentation Variables?
So how do you group your market according to your psychographic segmentation data? While there are several types of psychographic data on which you could base the customer segments you’ll be forming, indeed.com listed the following as the five main psychographic segmentation variables:
1. Personality – This variable refers to the beliefs, motivations, behaviors, and overall outlook of your target audience. You can group your customers based on personality traits like creativity, sociability, optimism, empathy, etc.
2. Lifestyle – This variable focuses on the daily habits and preferences of a customer, including how they spend their time and things they consider important.
3. Social class – This variable assumes preferences based on income level and spending power. It can also influence how a product is priced or whether it should be marketed as a luxury.
4. Attitudes – This variable considers the behavior of a customer based on their background and values. An example would be an animal lover who leans towards perfume brands that are known to be cruelty-free, meaning they don’t test their products on animals.
5. AIO (Activities, Interests and Opinions) – This variable groups consumers based on what they similarly enjoy or are passionate about. The second scenario earlier where you discovered the subset of regular customers purchasing the hard-to-find fragrance is an example of this variable.
Copyright geralt (Pixabay)
Personas vs. Psychographic Segmentation
While it might be easy to confuse psychographic segmentation with personas, these two concepts are subtly different. Psychographic segmentation groups your markets according to similar psychological traits and can therefore present a whole-market picture of consumers, spanning the range from those who passionately love your market offering to those who dislike it or resist it. This whole-market look also gives you the ability to attach real numbers to the data, enabling you to do things like demand forecasting, market sizing, receptivity studies based on counts of prospects, and the like.
Personas, on the other hand, are profiles — portraits of individual persons. They are more specific, detailed, and focused. Think of a police profile of a crime suspect (just the format of it, not the content.) A well-drawn persona presents a fictionalized representation of your ideal buyer, with information about key traits of that person. You might describe these traits by saying something like “likes to splurge on expensive vacations,” or “typically employed in middle-echelon white-collar jobs like administrative staff, etc.” The persona provides a vivid description of that individual, so you can better understand how to appeal to that kind of person with marketing campaigns and other forms of brand outreach. A good persona description humanizes the data and gives it a relatable face.
Please click here to find out more about segmentation studies, including some interesting case histories. Cascade Strategies has for over three decades been assisting top US and international companies with high quality market research and superior thinking in identifying and focusing on their most profit-optimal consumers. If you would like to find out more, or learn how Cascade Strategies can help provide brand development research for your specific marketing needs, feel free contact us here.
Sep
What It Means to Choose or Decide In The Age of AI
jerry97890 comments artificial intelligence, Burning Questions
Longstanding Concerns Over AI
From an open letter endorsed by tech leaders like Elon Musk and Steve Wozniak which proposed a six-month pause on AI development to Henry Kissinger co-writing a book on the pitfalls of unchecked, self-learning machines, it may come as no surprise that AI’s mainstream rise comes with its own share of caution and warnings. But these worries didn’t pop up with the sudden popularity of AI apps like ChatGPT; rather, concerns over AI’s influence have existed decades long before, expressed even by one of its early researchers, Joseph Weizenbaum.
ELIZA
In his book Computer Power and Human Reason: From Judgment to Calculation (1976), Weizenbaum recounted how he gradually transitioned from exalting the advancement of computer technology to a cautionary, philosophical outlook on machines imitating human behavior. As encapsulated in a 1996 review of his book by Amy Stout, Weizenbaum created a natural-language processing system he called ELIZA which is capable of conversing in a human-like fashion. When ELIZA began to be considered by psychiatrists for human therapy and his own secretary interacted with it too personally for Weizenbaum’s comfort, it led him to start pondering philosophically on what would be lost when aspects of humanity are compromised for production and efficiency.
Copyright chenspec (Pixabay)
The Importance of Human Intelligence
Weizenbaum posits that human intelligence can’t be simply measured nor can it be restricted by rationality. Human intelligence isn’t just scientific as it is also artistic and creative. He remarked with the following on what a monopoly of scientific approach would stand for, “We can count, but we are rapidly forgetting how to say what is worth counting and why.”
Weizenbaum’s ambivalence towards computer technology is further supported by the distinction he made between deciding and choosing; a computer can make decisions based on its calculation and programming but it can not ultimately choose since that requires judgment which is capable of factoring in emotions, values, and experience. Choice fundamentally is a human quality. Thus, we shouldn’t leave the most important decisions to be made for us by machines but rather, resolve matters from a perspective of choice and human understanding.
AI and Human Intelligence in Market Research
In the field of market research, AI is being utilized to analyze a multitude of data to produce accurate and actionable results or insights. One such example is deep learning models which, as Health IT Analytics explains, filter data through a cascade of multiple layers. Each successive layer improves its result by using or “learning” from the output of the previous one. This means the more data deep learning models process, the more accurate the results they provide thanks to the continuing refinement of their ability to correlate and connect information.
While you can depend on the accuracy of AI-generated results, Cascade Strategies takes it one step further by applying a high level of human thinking. This allows Cascade Strategies to interpret and unravel insights a machine would’ve otherwise missed because it can only decide, not choose.
Take a look at the market research project we performed for HP to help create a new marketing campaign. As part of our efforts, we chose to employ very perceptive researchers to spend time with worldwide HP engineers as well as engineers from other companies.
This resulted in our researchers discovering that HP engineers showed greater qualities of “mentorship” than other engineers. Yes, conducting their own technical work was important but just as significant for them was the opportunity to impart to others, especially younger people, what they were doing and why what they were doing was important. This deeper level of understanding led the way for a different approach to expressing the meaning of the HP brand for people and ultimately resulted in the award-winning and profitable “Mentor” campaign.
If you’re tired of the hype about AI-generated market research results and would like more thoughtful and original solutions for your brand, choose the high level of intuitive, interpretive, and synthesis-building thinking Cascade Strategies brings to the table. Please visit https://cascadestrategies.com/ to learn more about Cascade Strategies and more examples of our better thinking for clients.
Aug
The Future Is Here
“Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war.”
With just 22 words, we are ushered into a future once heralded in science fiction movies and literature of the past, a future our collective consciousness anticipated but has now taken us by surprise upon the realization of our unreadiness. It is a future where machines are intelligent enough to replicate a growing number of significant and specialized tasks. A future where machines are intelligent enough to not only threaten to replace the human workforce but humanity itself.
Published by the San Francisco-based Center for AI Safety, this 22-word statement was co-signed by leading tech figures such as Google DeepMind CEO Demis Hassabis and OpenAI CEO Sam Altman. Both have also expressed calls for caution before, joining the ranks of other tech specialists and executives like Elon Musk and Steve Wozniak.
Earlier in the year, Musk, Wozniak, and other tech leaders and experts endorsed an open letter proposing a six-month halt on AI research and development. The suggested pause is presumed to allow for time to determine and implement AI safety standards and protocols.
Max Tegmark, physicist and AI researcher at the Massachusetts Institute of Technology and co-founder of the Future of Life Institute, once held an optimistic view of the possibilities granted by AI but has now recently issued a warning. He remarked that humanity is failing this new technology’s challenge by rushing into the development and release of AI systems that aren’t fully understood or completely regulated.
Henry Kissinger himself co-wrote a book on the topic. In The Age of AI, Kissinger warned us about AI eventually becoming capable of making conclusions and decisions no human is able to consider or understand. This is a notion made more unsettling when taken into the context of everyday life and warfare.
Working With AI
We at Cascade Strategies wholeheartedly agree with this now emerging consensus and additionally, we believe that we’ve been obedient in upholding the responsible and conscientious use of AI. Not only have we long been advocating for the “Appropriate Use” of AI, but we’ve also made it a hallmark of how we find solutions for our client’s needs with market research and brand management.
Just consider the work we’ve done with the Expedia Group. For years, they’ve utilized a segmentation model to engage with their lodging partners by offering advice that could lead to the partner winning a booking over a competitor. AI filters through the thousands of possible recommendations to arrive at a shortlist of the best selections optimized for revenue.
With the continued growth and diversification of their partners, they then needed a more effective approach in engaging and appealing to them, something that focuses more on that associate’s behavior and motivations. We came up with two things for Expedia: a psychographic segmentation formed into subgroups based on patterns of thinking, feeling, and perceiving to explain and predict behavior, and more importantly, a Scenario Analyzer that utilizes the underlying AI model but now delivers recommendations in very action-oriented and compelling messaging tailor-fit for that specific partner.
The best part about the Scenario Analyzer is whether the partner follows any of the advice recommended or does nothing, Expedia still stands to make a profit while maintaining an image of personalized attentiveness to their partner’s needs. And ultimately, it’s the partner who gets to decide, not the AI.
Copyright Tara Winstead
Our Future With AI
This is how we view and approach AI- it’s not the end-all, be-all solution but rather an essential tool in increasing productivity and efficiency in tandem with excellent human thinking, judgment, and creativity. Yes, it is going to be part of our future but in line with the new consensus, we believe that AI shaped by human values and experience is the way to go with this emerging and exciting technology.
Aug
How Can Healthcare Companies Identify Who Needs Remediation Programs?
jerry97890 comments artificial intelligence, Burning Questions
What Is Remediation?
The Cambridge Dictionary defines remediation as “the process of improving or correcting a situation.” Remediation programs are commonly employed in teaching and education wherein they address learning gaps by reteaching basic skills with a focus on core areas like reading and math. And as pointed out in an understood.org article, remedial programs are expanding in many places in our post-COVID 19 world.
In healthcare, there’s a wide range of remediation programs, or “remedial care,” diversified based on their end goal which may include smoking cessation, anti-obesity, weight reduction, diet improvement, exercise, heart-healthy living, alcoholism treatment, drug treatment, and more. But how do you identify the people who need remedial care the most?
Who Needs Remediation?
You might say you can tell who needs remedial care by just looking at the physical aspect of the prospective patient, but this is a shortsighted answer to the question. And what about those who need remedial care for a heart-healthy lifestyle? Surely you can’t tell a likely candidate for this remediation program with just one look alone.
It goes deeper than that. What if you, a healthcare representative, could only devote remedial care to a select few individuals given limited resources and time but you want to make sure that the whole remediation program is successful by achieving its intended goals? Just imagine all that time, effort and resources spent only for the patient to relapse back into their old ways not too long after program completion- or even in the middle of the remediation process itself.
Deep Learning and Remediation
This is where deep learning comes in. Also known as hierarchical learning or deep structured learning, Health IT Analytics defines deep learning as a type of machine learning that uses a layered algorithmic architecture to analyze data. In deep learning models, data is filtered through a cascade of multiple layers, with each successive layer using the output from the previous one to inform its results. Deep learning models can become more and more accurate as they process more data, essentially learning from previous results to refine their ability to make correlations and connections.
Deep learning models handle and process huge volumes of complex data through multi-layered analytics to provide fast, accurate, and actionable results or insights. When applied to the scenario we mentioned beforehand, deep learning filters through that multitude of patient data and prioritizes those who need remedial care the most.
You can also align its findings to effectively identify individuals who will not only return monetary value to your healthcare brand, but at the same time are most likely to “engage” or participate in programs offered by your company, such as wellness, diet, fitness or exercise. They can also be the best people to commit to avoiding poor lifestyle choices, such as overeating, smoking, and alcohol, helping guarantee the success of the remediation program.
With a combination of three decades of market research experience and conscientious use of AI, Cascade Strategies has been helping healthcare organizations develop advanced models to handle, filter and identify the likeliest of candidates for their program purposes. Cascade Strategies helps industry professionals not only recognize their ideal customers but also reach out to them with some of the most effective and award-winning marketing campaigns, thanks to our array of services such as Brand Development Research and Segmentation Studies. To see more examples of how we help leading worldwide companies achieve their goals, please visit our website.
Here are some of our suggestions for further reading on deep learning and healthcare:
https://builtin.com/artificial-intelligence/machine-learning-healthcare
https://research.aimultiple.com/deep-learning-in-healthcare/
https://healthitanalytics.com/features/types-of-deep-learning-their-uses-in-healthcare
Aug
The Impact of AI
In The Age of AI, which Henry Kissinger co-wrote with Eric Schmidt and Daniel Huttenlocher, Kissinger tried to warn us that AI would eventually have the capability to come up with conclusions or decisions that no human is able to consider or understand. Put another way, self-learning AI would become capable of making decisions beyond what humans programmed into it and base such conclusions on what it deems the most logical approach, regardless of how negative or devastating the consequences can be.
A common example to illustrate this point is how AI had already transformed games of strategy like chess, where given the chance to learn the game for itself instead of using plays programmed into it by the best human chess masters, it executed moves that have never crossed the human mind. And when playing with other computers that were limited by human-based strategies, the self-learning AI proved dominant.
When applied to the field of warfare, this could possibly mean AI proposing or even executing the most inhumane of plans regardless of human disagreement simply because it considers such a decision the most logical step to take.
The Influence of AI
As part of Kissinger’s warning, it’s been noted just how far-reaching AI’s influence already is in modern life, especially with its usage in innocuous things such as social media algorithms, grammar checkers, and the much-hyped ChatGPT. With the growing dependency on AI, there runs the risk of human thinking being eclipsed by machine-based efficiency and effectiveness. And how it arrives at such efficient and effective decisions becomes questionable because it could become difficult or near impossible to trace what it has learned along the way.
Just imagine someone making a decision influenced by the information fed to them by AI and yet failing to rationalize the thinking behind such a decision. That particular human may not realize it, but at that point they’re living in an AI world, where human decision-making is imitating machine decision-making rather than the reverse. It was this interchangeability Alan Turing was referring to with his famous postulate about artificial intelligence — the so-called “Turing Test” — which holds that you haven’t reached anything that can be fairly called AI until you can’t tell the difference.
Copyright Pavel Danilyuk
Appropriate Use of AI
However, it’s been pointed out that the book doesn’t follow “AI fatalism,” a common belief wherein AI is inevitable and humans are powerless to affect this inevitability. The authors wrote that we are still capable of controlling and shaping AI with our human values, its “appropriate use” as we at Cascade Strategies have been advocating for quite some time. We have the opportunity to limit or restrain what AI learns or align its decision-making with human values.
Kissinger had sounded the warning while others had already made calls to start limiting AI’s capabilities. We are hopeful that in the coming years, with the best modern thinkers and tech experts at the forefront, we progress to more of an AI-assisted world where human agency remains paramount instead of an AI-dominated world where inscrutable decisions are left up to the machines.
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.