MxMIndia

Tag: Francis Kanoi

  • Helpful insights rarely come from focus groups but from mining the psyche of the team, writes Ashoke Agarrwal

    Insight Mining: The Creative Approach to Consumer Research

     

     

    By Ashoke Agarrwal

     

    Ashoke AgarrwalAs one of Indian advertising’s first wave of account planners, I positioned the discipline as representing “the creative dimension of strategy and the strategic dimension of creative”.

     

    Before joining the ranks of account planners, I was a founder of a research agency – Francis Kanoi – a deeply modelling-oriented quantitative agency. In 1983, Kanoi pioneered the large sample annual syndicated study of the consumer durables market that used the Bass Epidemiological Model to forecast consumer demand. This study, in its various avatars, continues to be an integral part of the marketer’s toolkit in the consumer electronics and durable industries.

     

    This grounding in quantitative research and market modelling proved to be of limited utility in practising the art of account planning, which consists chiefly of fine-tuning the positioning of a brand for lasting competitive advantage through insight-driven advertising. I leaned into qualitative research – focus groups and such – to find that fresh glimpse into the consumer psyche in general and her interaction with the product category and the brand that could lead to effective and advantage-yielding communication and creative strategy.

     

    However, over the years, I discovered that the source of helpful insight rarely came from focus groups but from elsewhere. They came from mining the psyche of the team – the planners, the creatives, the client servicing people and the client’s brand and marketing team.

     

    Each of us is a repository of sub-conscious insights into our behaviour and that of others we interact with daily and come across in popular culture – films, books, and the news. The mining of these insights – bringing them up from the sub-conscious depth to the conscious realm – is through free-form contemplation and discussion. It is brainstorming without the “driven intensity” that the word “storming.” implies. I find that insight mining is most productive when done in a relaxed setting and when it is open-ended in that it begins with a general discussion.

     

    The Insight Mining process yields richer results as the EQ and ITQ quotient of the team increases. EQ is, of course, Emotional Quotient- drives greater empathy and thus a richer storehouse of insights into behaviour and attitudes. ITQ is a coined term and stands for Intellectual and Travel Quotient. An intellectually curious and widely travelled team has broader experience and a more comprehensive range of insights into behaviours and attitudes.

     

    How does one get the target consumer to join the Insight Mining team? The answer is simple – make them – team members. Make friends and engage with them frequently in an informal, interactive, and conversational fashion. FCB, the Chicago headquartered agency, give the process a proprietary name – Mind & Mood – with Mind standing for the connotative aspects and Mood standing for the affective aspects.

     

    While insight mining was critical to generating practical and fresh ideas, traditional research also played a role.

     

    Focus Groups and Depth Interviews run by moderators and interviews and analysed by researchers with high EQ and ITQ yielded valuable Insight Mining inputs.

     

    Quantitative research helps confirm and ratify hypotheses and campaigns generated from Insight Mining and quantify and model subsequent marketing planning and market mix models.

     

    Insight Mining yields results where conventional research could not find fresh insight. For example, it recognised weddings as a high-impact occasion for being mistaken to be younger than one is – a plank for a soap brand positioned on the “keep-looking-young.” benefit. Or recognising that freshness is the difference between how one feels when one sets out for work in the morning and when one returns from the office – leading to a memorable creative rendition for an eau-de-cologne campaign. Or how, for a young mother, a bubbly child is the most convincing metaphor for overall family health – the basis for positioning a packaged food brand.

     

    Besides traditional consumer research, social and anthropological research tools like ethnography and semiotics are valuable inputs into Insight Mining.

     

    Insight Mining is as valuable upstream – in product development, product form – in marketing as it is downstream – brand positioning and marketing communication.

     

    Steve Jobs firmly believed that no amount of market research could have led to the breakthrough product concepts – the iPod and the iPhone. Top-flight creative people like Steve Jobs are a one-person Super Lode of insights. The success of many organisations or institutions in producing a continuous stream of innovations is the result of Super Lodes supported by a bright Insight Mining team and a diligent upstream process team.

     

    To sum up, at its core, Insight Mining is the final step in the consumer research process. It takes place after everyone in the Insight Mining team has absorbed the relevant traditional primary and secondary research, ethnography and semiotics. The magical, mystical process of Insight Mining catalyses all that with the life experience of the Insight Mining team. To paraphrase Pink Flyod, Insight Mining is the synergy of what is contextually known with:

     

    All that you touch/ And all that you see/All that you taste/All you feel

    And all that you love/And all that you hate/All you distrust/All you save

    And all that you give/And all that you deal/And all that you buy

    Beg, borrow or steal/And all you create/And all you destroy

    And all that you do/And all that you say/And all that you eat

    And everyone you meet (everyone you meet)/And all that you slight

    And everyone you fight/And all that is now/And all that is gone

    And all that’s to come/And everything under the sun

     

  • Tech-driven significant shifts are likely to drive change in market research over the coming decades, writes Ashoke Agarrwal

    3 Big & Coming Shifts in Market Research

     

     

    By Ashoke Agarrwal

     

    Ashoke Agarrwal

    I have been a purveyor and user of market research for a little more than four decades now. At 26, I co-founded Francis Kanoi (Kanoi is my family name). I worked with my partner, the legendary Francis Xavier, in designing and executing what was then the most extensive market research study in the country. An all-India, 70,000 sample size study using the Bass Epidemiological Model to forecast the demand for household durables like refrigerators and TVs. The study found 33 subscribers in the first year, and four decades down the line is still going strong.

     

    In the 90s, I directed research and planning at Ulka, with perhaps the strongest strategy team in the advertising world. Anil Kapoor, the MD and his handpicked team, genuinely believed in accessing and acting upon consumer research and insights. That was one of the reasons why Ulka, those days, sat at the high table in strategy sessions with clients’ marketing teams that went beyond advertising and creative strategy.

     

    In the new millennium, I run, in partnership with other veterans of the marketing and marketing services industry, a marketing advisory service with market research as a core input.

     

    Over the decades, market research has been slow to change. However, I have noticed an incipient change in this otherwise conservative industry over the past few years that will snowball into a paradigm shift over the coming decade.

     

    Shifts in socio-economic and technological forces are driving this change.

     

    The following key trends are powering the shift:

    Hyper-individualisation: Sampling lies at the heart of traditional market research. At its most fundamental, sampling methodology is based on an assumption. Sampling assumes that a market divides into a finite number of segments usually defined by simple demographic parameters like age, gender, education, income and pop strata. Further, consumers in each segment behave homogeneously concerning their usage and attitudes towards the focus product or service category. On the strength of this assumption, traditional market research makes do with samples in the hundred and the thousands to assess and forecast markets with tens and hundreds of millions of entities. In essence, this ability is at the heart of the business model and viability of the market research industry. Unfortunately, this assumption has started failing, and doubts have started creeping into traditional market research methods.

     

    The spectacular failings of one aspect of market research that gets frenzied media attention – election forecast polling – have further fuelled these doubts. The core assumption of homogenous demographic segments no longer holds because of the hyper-individualisation of opinions, attitudes, behaviour and lifestyles that the emergence of the digital world has wrought. In the old world, socio-economic forces, including mass media, lead to conformity among people of the same age, gender and social class groups. Today, with a proliferation of career and lifestyle choices, ever-increasing choices in products and services, and the ability to create a curated stream of media-based, every individual is a segment of one.

     

    Big Data & Machine Learning: If market research is to survive, it will need to replace the traditional demographic segments-based sampling (this applies to both quantitative and qualitative market research). To my mind, the answer lies in the realm of Big Data coupled with machine learning. All commercial organisations will need to invest in the collection, warehousing, and analysis of Big Data covering all aspects of their business, including consumers. Big Data and its informed use are becoming critical to any organisation’s competitive strength.

     

    In the age of hyper-individualisation, factors other than demographics drive attitudes, behaviour and lifestyles. For example, a twenty-five-year-old today might have more commonalities in attitudes and lifestyles with a forty-year-old than with any of the individual’s age cohorts. When applied to Big Data on consumers, machine learning can unearth such patterns and build a market segmentation map beyond demographics to actual behaviour. This shift gives back market research its predictive power. For example, in micro-lending, a growing fintech area, such analysis has led to factors like the day of the week an individual applies for a loan being an indicator of his creditworthiness.

     

    There are many sources of Big Data. Governments and social organisations put out public sources. In addition, companies and organizations collect private first-party data from their operations. In fact, for an organization like Facebook and Google, this data is the lifeblood of their business. Finally, a fast-emerging source of Big Data is voluntary disclosures by individuals. In industry parlance, such Big Data collected through voluntary disclosures by individuals is called Zero-Party Data. Heightened privacy concerns and more stringent regulations will herald a new age of Zero-Party Data. I believe this will become the backbone of a new paradigm in market research.

     

    Zero-Party Data, Data Vaults and Active Research: The market research agency of tomorrow will be a collector, storer and analyser of Zero-Party Big Data. The agency will partner with every individual whose data it collects and stores. The collection will be permission-based. The usage will be transparent, and, using blockchain technology, the individual will get a share of all revenues generated from using their data.

     

    The agency will invest in machine learning to unearth patterns and, based on these patterns and directed probes will run market research projects and forecasts for its clients. In addition, the agency will anonymise all data used in such research projects.

     

    Beyond market research, Zero-Party Data and Data Vaults opens up a whole new arena to marketing. I call this arena Active Research. With the individual’s permission, the agency opens up a one-on-one conversation between the individual and brands to unearth needs and desires, customize and test products and services and make relevant offers. The agency mediates and adds value by using state-of-the-art probes and is informed by the ongoing learnings across the database. Since the agency’s Zero-Party Big data covers a substantial part of the market, Active Research becomes a real-world test marketing option and even a viable Route-to-Market (RTM).

     

    Beyond Zero-Party Big Data, Data Vaults and Active Research, other tech-driven significant shifts are likely to drive change in market research over the coming decades. The two technologies that drive this change will be

    :: The emergence of NLP-driven custom-framework-based fourth-generation search engines to generate curated reports will transform secondary research.

    :: Research in the metaverse will take ethnographic research to the next level.

     

    I hope to discuss the above two horizons in market research in later columns.

     

    Ashoke Agarrwal is a veteran advertising professional with around four decades in advertising and marketing services. Agarrwal, a chemical engineer from IIT Mumbai and a postgraduate from IIM Bangalore, is a pro-entrepreneur with past and current ventures in market research, advertising, CGI, e-learning and brand consultancy. He writes on MxMIndia every other Thursday. His views here are personal.