Feb
Can AI & Human Researchers Coexist In Market Research?
jerry9789 0 comments artificial intelligence, Brand Surveys and Testing, Burning Questions
AI In Market Research Today
With 90% of the world’s data created in just two years time between 2021 and 2023 and the global data volume standing at 149 zettabytes by 2024, it’s understandable why AI would be readily adopted by the market research industry. Traditional methods of data collection and analysis would hold a place in market research but they simply aren’t as powerful as AI when it comes to handling all that staggering volume of data. But is AI powerful enough to take the place of human researchers?
AI enables research teams to move, process and analyze massive datasets with speed and accuracy, efficiently handling all the repetition and scale involved in the research process. From drafting questionnaires to monitoring survey data quality, from analyzing open-ends to formulating dashboards and charts, AI fully automates the research process leading to faster and better decisions at a scale beyond the capabilities of human researchers.
But is AI the endgame for market research? Does it make human researchers obsolete?
Image: geralt
Cascade Strategies and AI
Cascade Strategies conducted a member perceptions study for a company looking to develop and implement a brand typology. The overall goal of the study was to help them better understand their different customer type’s overall motivations and aspirations for more effective engagement. As part of the study, we conducted an online survey with over 1,500 of their randomly selected members. We then utilized an AI-assisted Self-organizing Map (SOM) to run all the cases recursively, sometimes millions of times, until it optimizes the separations among the groups. The SOM produced a 6-group solution, with each group having a dominant passion that is served well or poorly by the company, ranging from proclivity for deals and new brands to yearning for customization and connection with other users.
The AI has done the heavy lifting of scanning all that dataset, surfacing themes, and summarizing the respondents. It has done enough to structure the story of each group but not enough tell or paint the whole picture.
This is where the human researchers at Cascade Strategies step in. We came up with names for each group that best described their dominant passion, names resonant enough that they not only convey an immediate idea of what they’re most passionate about but makes them fundamentally relatable even if one doesn’t necessarily share the same propensities: Shopper, Seeker, Learner, Sharer, Individualizer and Intellectual.
In isolation, each group achieves the study’s goal of guiding the company on the most effective way to engage with them. Their sum, however, grants the company an overview on how to improve and further develop its platform by considering and introducing new features that matter to one particular group, but would essentially benefit its membership base as a whole when implemented. For example, the Sharer would appreciate increased opportunities to connect and interact with other experts and enthusiasts of the same interests in the platform by making it easier to make reviews and share content.
AI surfaced all those patterns and signals from all that survey data, but it lacked the judgment and context to elevate it into a meaningful and coherent narrative. Human researchers, on the other hand, saw what story can be told from all those themes and by layering in human understanding, they’re able to tie them down to actionable business decisions.
Image: Christina Morillo
Leveraging AI In Market Research
So would AI replace human researchers? We’d like to frame our response to this question with the words of Joseph Weizenbaum, one of AI’s early researchers: “We can count, but we are rapidly forgetting how to say what is worth counting and why.”
Yes, AI is powerful enough to handle large amounts of data to identify patterns, cluster themes, and summarize respondents, but it generates outputs rather than insights. Outputs foster decisions rooted in logic and reasoning, but insights spring from judgment and context. Outputs can provide directions and surface themes from which stories can be framed, but insights take it one step further by asking what matters and why it matters, adding depth and resonance to the story.
In addition, Weizenbaum posits that computer programming can make decisions but it can’t ultimately choose. Just like insights, choosing requires judgment which takes in emotions, values and experience.
We at Cascade Strategies are among a growing number of proponents who believe that AI works best as a tool and extension of human intelligence and talents. AI strips the friction from manual, repetitive work without compromising methodological rigor and accuracy, but rather than adopting it for the sake of automation, we choose to see it as a freeing and empowering agent that enables researchers to focus more on interpreting data with the context of human understanding and values, translating insights into sensible and confident business decisions. Just as quantitative and qualitative research can coexist in the same study, we choose to live in a world where AI and human researchers work together towards the same goal of finding and crafting meaningful and relevant stories worth telling.
Image: Pavel Danilyuk
Featured Image: Ron Lach
Top Image: kc0uvb
Oct
A Human Center Makes Market Research All The More Powerful
jerry9789 0 comments artificial intelligence, Brand Surveys and Testing, Brandview World
The Future Of Research Is Here
You’ve seen it and there’s no denying it. Industries have been reshaped by the increasing utilization of Artificial Intelligence just in the last few years alone. Promising and delivering speed and optimization at the fraction of the costs and resources, it’s powerful, revolutionary and exciting. And as with any emerging technology, it comes with its own set of anxieties.
In line with its growing popularity and adoption, people in different industries have been expressing nervousness over being replaced in their jobs by AI. Certain repetitive, data-driven tasks are at the greatest risk of being supplanted by AI. However, AI also opens up opportunities to shift focus and upskill the more complex and creativity-driven facets of work roles, creating new jobs or augmenting existing ones.
The research industry is just as impacted by AI’s progressive application. It’s naive to assume that researchers would be replaced wholesale by AI, but there’s more to delivering research results than just gathering and crunching data.
Image: Circe Deyer
Our take on the integration of AI into research
We’ve always maintained that AI is a good advisor, but it’s a poor decision-maker. We’d like to modify that by saying it’s an even worse storyteller, if at all.
Cascade Strategies has been in the market research industry for over three decades now, serving some of the biggest local and international companies. You can say we’ve seen it all in this industry, but we’re just as fascinated as everyone else by the mainstream popularity of AI in the past few years. We’ve applied it in our methodologies, been impressed by its operational benefits and how it changed industries, but in the end, we know truthfully that it is not the end-all, be-all for research work. We believe that AI would serve us better by being a powerful extension of human judgment, creativity, and insight.
AI can be fed large datasets to approximate human thinking, but we believe it can never replicate human perspicacity, the kind of intelligence honed and guided by human values and experience. Take a look at our Expedia Group Case Study where we’ve utilized AI to generate multiple revenue-granting scenarios, then tempered the decision-making process by applying high-level human thinking to craft messaging that resonates with the end-user.
AI-driven research can produce results based on what has come before, but it can never uncover the truly novel, meaningful and resonant insights high-level human thinking unlocks. These are the insights that empower big and sweeping decisions. Data-based results from AI would seem lifeless and unrelatable. But if they are imbued with human interpretation, that output elevates into a masterful narrative that sparks imagination, questions boundaries, and transforms perspectives.
Image: geralt
Featured Image: mohamed mahmoud hassan
Top Image: geralt
Mar
Can Psychographic Segmentation Help Financial Services Companies?
jerry9789 0 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.
info@cascadestrategies.com
2032 Newport Way NW,
Issaquah, WA 98027
(425) 677-7430