Jun
Appropriate Use of AI
jerry9789 0 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
jerry9789 0 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.
Jun
How Great Research Helps Tech Companies
jerry9789 0 comments artificial intelligence, Brand Surveys and Testing, Brandview World, Burning Questions
How Well do you Understand Your Customers’ Needs?
As a Tech Company, how well do you know your customers? In most cases, identifying who has an affinity for your brand and focusing on the needs of that customer type can spell success for your products, especially the launch of your new offerings.
Sure, you might think you can have AI go over your customer database and hope it’s able to recognize customers and prospects most likely to purchase your product. However, AI shortcuts are unable to approach the intuitive and interpretive power of human thinking, let alone the kind performing at a high and excellent level.
The Story of HP Test & Measurement
The case of Hewlett Packard’s “Mentor” campaign is instructive. HP commissioned our researchers to spend quality time with worldwide HP engineers as well as engineers from other companies, learning about their daily lives – how they think, feel, and behave. 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.
The result was a highly successful, award-winning global campaign. Conversion rates soared as HP logged higher equipment sales in virtually every world region. The campaign also produced significant financial gains for HP and won an ADDY Award for creativity.
The Squaresoft Video Games Story
We also conducted primary market research for Squaresoft Video Games to determine affinities for their products. They had been sending out about 200,000 mail pieces per month to key metros across the US. By giving us extracts of their file of purchases of similar games, we appended characteristics and modeled affinities for prospective buyers.
We called those most likely to respond “Videobrats.” The model reduced the number of markets to 4 key metros which had the highest concentration of “Videobrats,” concentrating their marketing on high-affinity households in these markets.
Our researchers spent a great deal of time with Videobrats in these markets, exploring their daily lives, discovering how they think, how they interact with others, and how they spend time with entertainment and gaming software. This hard work produced a key set of insights that could be perceived only through the intuitive and interpretive power of the human mind. It’s not something AI could touch.
The result was a campaign of extraordinary power and great marketplace success. Squaresoft reported dramatically increased sales of the two game titles in the specific geographies in question, ranging from 20% to 200%. Not only that, the “Videobrats” campaign won the KPMG Award of Merit for ROI performance and the Ernst & Young Most Effective Marketing Campaign Award.
The Lessons for Marketing in the Tech Sector
Many people conducting marketing campaigns in the tech sector believe you just need to tell people on the web what you have (e.g., software, hardware, systems), and the magic of internet targeting will take care of the rest. They’re wrong. It’s as important in tech as in any other category to tell people why they should want the software, hardware, or systems from your brand instead of another brand. That requires you to express something about what psychologically or emotionally binds your customers to your brand.
Discovering the root of these deeper connections requires more complex layers of understanding and perception than AI can provide at present. Hard-working humans driving their minds to higher levels of interpretation and synthesis can do it.
When market research is used not just as a means to an end but as a way to gain a deeper understanding, Tech Companies are able to produce outstanding results because they are able to come up with inspired and creative solutions addressing the needs of those who value their brand the most. AI is unable to unlock these sophisticated types of solutions because it’s unable to relate on an intuitive and interpretive level the same way excellent human thinking does.
If you’d like to see this kind of magic brought to life for your brand, please reach out to us here.
May
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.
Copyright 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/
May
Five Ways AI Can Help Telecom Companies Improve Their Marketing
jerry9789 0 comments artificial intelligence, Burning Questions
By moving away from business-driven marketing towards customer-centric, data-driven, and highly customized efforts, companies like telecom operators can thrive in these rapidly changing times. Here are five examples of how telecom companies can benefit from utilizing Artificial Intelligence in their marketing:
1. Increase in Product Marketing
With the millions of customer data they’ve collected, telcos can leverage AI to create targeted marketing campaigns via text, email, online ads, etc. This helps them gain a more real-time picture of their users’ experiences, thanks to sharper insights, suggestions, and trend recognition. Critical marketing knowledge and understanding of their user base are also enhanced by incorporating machine learning apps and algorithms into their product.
2. Improved Campaign Performance
Personalization as a strategy has proven through time its helpfulness in boosting several types of marketing campaigns. Integrating AI into the mix can rapidly grow its scale and capacity.
Ad targeting becomes more efficient with AI identifying the most appropriate customers for specific ads based on secured information on buying history and user preferences.
And by also automating user journeys, marketers are able to decrease the time and costs of sales targets and conversions.
3. Addressing Customer Service Issues Better
AI allows telcos to respond quickly to customer experience concerns by gathering data and identifying where the user journey fails, fostering customer satisfaction. Various AI-powered software analyzing customer feedback also improves customer support efforts by finding more appropriate, more empathetic solutions.
Front-end customer service employees can also get holistically educated about various issues and scenarios through AI training. Here the AI takes on the role of a customer. AI training also helps businesses cut back on major labor and time costs.
4. Improved Digital Marketing and Customer Engagement
Cloud-based products offer well-integrated data insights and marketing intelligence, machine learning and analytic technologies with recommendations, multi-dimensional visualizations of complex data, and free-form user analysis.
Such products solve problems by allowing users to easily integrate disparate data sources, breaking down traditional silos and enabling insight-driven decision-making.
5. Notifications Sent at More Appropriate Times
AI is also being used to boost push campaign engagement by determining the best time of day to send notifications to consumers, preferably the time they are most open to brand interactions.
With the enormous data and complexities handled in industries, telcos must use AI in staying ahead of competitors. It’s just simpler to address problems and automate solutions, run daily operations more efficiently, and provide better customer service and satisfaction. In the long run, telcos continuing their development along this path are more likely to emerge as undisputed winners.
Mar
What if every US citizen had a dollar for every good decision made by the president and lost a dollar for every bad decision? How much would Americans have in their “Decision Account” now? What about a half-good decision? Would Americans’ Decision Account be credited for 50 cents? Clearly, the whole matter hinges on what is defined as a good or bad decision.
Mar
Responsible AI – What Causes Bias in Training Data?
jerry9789 0 comments artificial intelligence, Burning Questions
Over the past few decades, the use of AI in business has grown tremendously. By 2030, AI may generate up to $15.7 trillion in revenue to the global economy.
From process automation to sales forecast, the potential applications for AI in business are nearly limitless. But, you’ve still got to wonder, what happens when we place so much power on fairly new technology? Will it be fair or biased? Will it try to take over the world in the future? We don’t give the fear mongers much weight about AI taking over the world, but unchecked bias in AI data or models can lead to unintended negative consequences that do real harm.
Mar
Artificial Intelligence (AI) is becoming a critical component of digital marketing. AI in marketing can be particularly revelatory, often delivering valuable insights that marketers can use to develop personalized content, drive conversions, and improve customer experience. Such insights help develop effective marketing strategies, which increase Return on Investment (ROI) for AI implementations.
Mar
4 Ways Data Can Help Create Sustainable Revenue Growth
There is no question that year after year, the cost of revenue (COR) generation continues to climb. Look at publicly traded companies in nearly any sector and read the reported costs associated with sales and marketing. In almost every case, the costs of acquiring revenues continue to outpace the gross revenues generated. It costs more to make the same money. In today’s world of shifting digital and economic landscapes, tapping into data in real time and extruding insights gives executives a critical tool to stay ahead of the curve. Near real-time decision making is a necessity – not a luxury.
Feb
Data Science Team: Build or Rent?
Eric Layland 0 comments artificial intelligence, Burning Questions
Building an Efficient & Effective Data Science Team
There are numerous reasons why a company may decide to develop a data science team in their organization. The skills an in-house team brings can enable organizations to turn raw data into strategic assets. Their skills lead to better use of data assets including understanding customer behavior, error detection, automation of repetitive tasks, and overall more sophisticated decision support. A data-driven organization can benefit and gain a competitive edge.
However, building an effective and efficient data science team is not as simple as adding new hires. Before we can discuss whether to rent or build a team of experts, it’s essential to understand the roles typically needed to fully staff a data science team.
The included salary estimates do not include benefits. The figures are an average of the latest available data from Salary.com, PayScale and ZipRecruiter and reflect US labor markets.
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