viernes, 9 de marzo de 2012
¡¡Vive despeinada!!
Para despedir la semana de la mujer, compartimos estos sabios consejos de la gran Mafalda. ¡Feliz fin de semana!
jueves, 8 de marzo de 2012
Las mujeres del futuro.
Las
mujeres del futuro. Un estudio sobre las mujeres alrededor del mundo
Guadalupe Vargas.
¿Cuáles
son los medios tradicionales y nuevos más exitosos para influir en sus
decisiones de compra? ¿Las mujeres de países desarrollados piensan y actúan
diferente que aquellas que viven en países emergentes? ¿Qué preocupaciones
tienen las mujeres ahora y qué esperan para las generaciones futuras? ¿Existen
aún los papeles tradicionales o los hombres comparten equitativamente las
responsabilidades? ¿Cómo pueden los mercadólogos impactar con mayor efectividad
a las mujeres y crear mensajes que se comuniquen mejor con los sentimientos y
emociones que las impulsan y fortalecen?
Este estudio
fue conducido entre febrero y abril de 2011 y contó con la
participación de casi 6,500 mujeres (en 21 países) ubicadas en Asia Pacífico,
Europa, América Latina, África y Norteamérica.
La muestra
fue aplicada en el campo en países desarrollados usando una metodología online.
En países emergentes se aplicó una aproximación online con Metodología
de Campo Mixta (MCM), de ubicación central y/o entrevista puerta a puerta. El
margen de error es +/- dos puntos. Los países en el estudio representan 60% de
la población mundial y 78% del PIB. Fuente: Estudio Nielsen Las Mujeres del Futuro 2011.
Publicado en la Revista Amai. Si desea ver el estudio completo, busque en este link: http://www.amai.org/publica_revista.php
En
la distribución del gasto en los hogares, las mujeres tienen el control
Las
mujeres controlan la mayoría de las decisiones de compra en el hogar y su
influencia está creciendo. Alrededor del mundo están ampliando sus roles
tradicionales para intervenir en decisiones del hogar, negocios y política.
El poder
de decisión con el que cuentan, representa una gran oportunidad para vincular
de mejor manera a las mujeres con los productos que compran, los servicios que
utilizan y las tecnologías de medios que usan; capitalizar el conocimiento que
se tiene de las mujeres como consumidores, indudablemente puede producir
resultados muy positivos.
Para
contestar estas preguntas, Nielsen realizó un estudio con mujeres de distintas
generaciones ubicadas en economías desarrolladas y emergentes. El estudio
incluyó 21 países que representan a nivel mundial 60% de la población y 78% del
PIB. Este análisis proporciona insights respecto a cómo las generaciones
actuales y futuras de mujeres consumidoras compran productos y servicios, y
usan los medios de manera distinta. Una verdad universal prevalece: las
mujeres en todos los lugares creen que su papel está cambiando y que
esta transformación es para mejorar.
Las
mujeres consideran que su rol está cambiando para mejorar
El 80% de
las mujeres de los países desarrollados creen que el rol de la mujer está cambiando
y –de ellas– el 90% considera que este cambio es para mejorar. En países emergentes,
el futuro se percibe aún más prometedor. Esta tendencia, de que las mujeres
trabajen fuera de casa, ha sido más notoria en los países desarrollados; sin
embargo, poco a poco se ha ido incorporando a las naciones emergentes, como las
que integran Latinoamérica. De hecho, la expectativa que se tiene de la
participación de la mujer en los ingresos del hogar para los siguientes cinco años,
evidencia esta clara tendencia.
Las redes
sociales están conectando a las mujeres alrededor del mundo, ampliando su “círculo
de influencia”, convirtiéndose en una herramienta indispensable para resolver
problemas, hacer preguntas y construir una comunidad.
Los medios
sociales son mucho más que sólo entretenimiento; en el caso particular de las
mujeres proporcionan sin lugar a dudas beneficios funcionales. Nielsen estima que
existen en promedio entre 200 a 300 foros de mujeres dedicados a la discusión
entre mercados globales (sin contar blogs individuales), donde las mujeres se
conectan para tratar temas que van desde la vida familiar, administración de
carrera, salud y bienestar, compras y salud financiera.
•• En línea,
las mujeres son más comprometidas que los hombres, ya que pasan más
tiempo en menos sitios durante una sesión.
• Las
mujeres hablan 28% más por celular y envían 14% más cantidad de mensajes de
texto que los hombres.
Éstos son
datos interesantes para mercadólogos y publicistas, tienen la oportunidad de
conectarse mejor con las mujeres vía online y encontrar formas de
hacerlas sentir como clientes valiosas y a su vez, recompensarlas por ser
abogadas de la marca.
Las redes
sociales tienen el poder de conectar a mujeres alrededor del mundo y –mientras
lo hacen– sus comunidades y círculos de influencia llegan a ser mucho más amplios.
Hoy, Nielsen reporta que el uso de los medios sociales ha alcanzado altas
cifras de penetración en países como Estados Unidos (73%), Italia (71%), Corea
del Sur (71%), Australia (69%), Francia (64%), Brasil (63%) y Alemania (50%).
Mientras
tanto, las tasas de adopción de medios tecnológicos continúan al alza en países
emergentes. Tres cuartas partes de las mujeres en países emergentes declaran
que la computadora y el teléfono móvil les permiten tener una mejor vida en
general.
Las
mujeres son más influenciadas por personas que conocen
Entre 22
formas de publicidad medidas, las “recomendaciones de gente que conoce”, son
por mucho la fuente de publicidad más confiable para las mujeres, tanto en países
desarrollados (73%) como en países emergentes (82%); sin embargo, cuando se
trata de publicidad pagada, las opiniones varían ampliamente.
Después de
las recomendaciones y opiniones encontradas online, las mujeres en países
desarrollados dan su confianza al contenido editorial de periódicos (35%),
sitios en Internet de la marca (32%) y correos electrónicos a los que se han
inscrito (29%). En países emergentes, los sitios en Internet de la marca (60%)
son el medio más confiado, seguido de las editoriales de periódico (56%) y anuncios
en TV (49%).
El estudio
de Nielsen también reveló que la mayoría de las mujeres dijeron que son más reticentes
a confiar en anuncios de texto vía teléfono celular, en redes sociales y en
dispositivos como teléfonos inteligentes y tablets.
Anuncios
en línea tipo banner cuentan con un amplio aspecto positivo para ganar su
confianza. La TV es la fuente preferida cuando se trata de obtener información
sobre nuevos productos y servicios; este medio continúa siendo el medio más
persuasivo y es la fuente número uno en que las mujeres de distintos
continentes confían. En 10 de 10 mercados emergentes y en 7 de 11 mercados
desarrollados, la televisión se destacó notoriamente sobre las 14 fuentes de
información alternas.
Las
recomendaciones de boca en boca se ubicaron como la segunda o tercera opción.
Los periódicos y revista fueron otra fuente de información popular para las
mujeres de mercados emergentes, mientras que el uso de Internet fue más
dominante en mercados desarrollados.
En 95% de
los países, la calidad es el constructor número uno de lealtad a la marca. En
tanto que el precio es una influencia importante para la decisión de compra, en
la mayoría de las categorías no se encuentra dentro de los tres primeros
criterios. Cuando se trata de generar lealtad a la marca, la calidad es el
detonador principal en los países emergentes
Más
influencia sí, pero también más estrés
Conforme
se incrementa el poder, el estrés aumenta. Ante este cambio de rol que desempeña
la mujer a nivel global, las encuestadas declararon que se sienten presionadas
por el tiempo, rara vez tienen oportunidad de relajarse y se sienten estresadas
y con sobrecarga de trabajo constantemente.
Se pudo
observar que en los países emergentes, ellas sienten esta presión aún más que
sus congéneres de países desarrollados. Las mujeres de India (87%), México (74%)
y Rusia (69%) reportan que el tiempo es su mayor preocupación; en países
desarrollados, en España (66%), Francia (65%) e Italia (64%) son las más
estresadas por la misma causa.
Adicionalmente,
la investigación muestra que las mujeres que viven en países emergentes
distribuyen la mayor parte de sus ingresos adicionales en básicos esenciales, como
comida y ropa; en tanto que las mujeres en países desarrollados indican que están
más dispuestas a destinarlos a vacaciones, compra de abarrotes, pago de deudas
y para ahorro en general. Específicamente para el caso de Latinoamérica, el
orden de sus preferencias se ubicó de la siguiente manera: vacaciones, ahorro,
alimentos, ropa y entretenimiento en el hogar
Las
mujeres pueden controlar el gasto en el hogar, pero uno de los aspectos que
realmente desean es tener responsabilidades compartidas y más equitativas con
sus parejas, respecto a todas las materias de la vida, desde el cuidado a los
niños hasta la compra de un auto.
En países
desarrollados, la noción de compartir la toma de decisiones y de
responsabilidades está bien establecida para todas las materias, aunque las
compras relativas a cuestiones de salud y belleza, así como en todas las áreas
que tienen que ver con los niños dentro y fuera de casa, permanecen entre las
decisiones en las cuales las mujeres ejercen mayor influencia.
En economías
emergentes, los hombres aún son considerados como los depositarios de la toma
de decisión principal en cuanto a electrónicos y autos, en tanto que la mujer
predomina en materia de salud, belleza, alimentos, así como en las decisiones
que tienen que ver con el cuidado de los niños.
Día Internacional de la Mujer
Día Internacional de la Mujer - Mensaje de Michelle Bachelet, Directora Ejecutiva de ONU
miércoles, 7 de marzo de 2012
Whatever next?
"Los críticos de la investigación de mercado disfrutan cuando se refieren al porcentaje de productos nuevos que fracasan. Pero no son sólo fracasos en función de una mala investigación, pues está claro que los mercados sólo pueden acoger a un determinado número de productos nuevos, por lo que la investigación sólo puede reducir las probabilidades de fracaso."
http://www.research-live.com/features/whatever-next?%2F4006746.article

“We are already on the verge of discovering the secret of transmuting metals… before long it will be an easy matter to convert a truck load of iron bars into as many bars of virgin gold.” Those were the words of Thomas Edison in 1911 predicting scientific advances in the century ahead. By 2011, Edison said, “there is no reason why we should not ride in golden taxi cabs” or “why our great liners should not be of solid gold from stem to stern”.
Edison didn’t live to see his golden taxi cab, and 101 years on from his forecast it still hasn’t shown up. To be fair to him, it’s not difficult to find examples of predictions from the past that were woefully off the mark – and people aren’t getting any more prescient. A 1962 advertisement for Michigan Mutual Liability predicted its customers of 2012 would need insurance for their “picnics on Mars”.
More prosaic predictions can be just as wrong. Many 1960s scholars predicted food shortages in the decade ahead which never came to pass. In the 1980s it was widely believed that Japan was poised to topple the US as the number one world power. And we all remember the anticlimax that was the Y2K bug. Meanwhile hugely significant global events such as the financial crisis and the 9/11 attacks continue to catch us off guard.
In fact half the time we don’t even know what’s happening today, let alone what will happen tomorrow. On New Year’s Eve 2007 the Financial Times predicted that America would not go into recession in the year ahead. They were sort of right – in the sense that the country already was in recession (a fact that would only became clear in economic data released later).
Ask the experts
Clearly, predicting the future is hard – even for experts. In an experiment that ran for 20 years psychologist Philip Tetlock put 28,000 questions about future events to 284 experts in various fields and compared the results with real-world outcomes. Looking back on their performance, Tetlock compared the experts to “dart-throwing chimpanzees”.
Yet despite these failures, we keep making and seeking predictions. We place bets, we listen to pundits, we conduct market research. In his latest book Future Babble journalist Dan Gardner reviews predictions from recognised experts in politics, economics, technology and climate science. “No matter how many times the best and brightest fail, more try,” says Gardner. “And they never doubt they are right.”
Thanks to various psychological quirks from which we all suffer, people whose predictions go awry often don’t accept, or even realise, that they were wrong. But even more worryingly, failed predictions rarely dent an expert’s credibility – people keep listening to them.
Cognitive illusions like these can lead to bad predictions of the value of a company’s stock or of an individual’s professional performance, as Nobel Prize-winning psychologist Daniel Kahneman describes in his new book Thinking Fast and Slow. For most fund managers, choosing stocks is “more like rolling dice than playing poker”, says Kahneman, because despite the knowledge and expertise that traders undoubtedly possess, very few consistently beat the market. The correlation in performance from year to year at a company Kahneman studied was close to zero, suggesting that they were “rewarding luck as if it were skill”.
Similarly, when Kahneman had to evaluate soldiers in the Israeli army for their potential to succeed as officers, he realised that the ones he and his team picked out as the best didn’t do any better than the rest in the long run. But that didn’t stop him. “We knew as a general fact that our predictions were little better than random guesses, but we continued to feel and act as if each of our specific predictions was valid,” he says.
All this might sound a bit disheartening. But market researchers haven’t got much choice other than to keep trying to predict the future. And even when the questions at hand are confined to the minutiae of individuals’ decision-making, it’s still not an easy business. So can market researchers really help clients face the future, or are they just chimps throwing darts?
Critics of market research enjoy citing the percentage of new products that fail – a figure that’s different every time you hear it, but is generally agreed to be a large majority. But flops aren’t just a function of bad research – markets can clearly only support a certain number of new products, so research can only reduce the odds of failure so far. Besides, a bit of healthy trial and error can do you good – just look at Google.
SPA Future Thinking forecasts sales for new consumer products, and claims margins of error of +/-9% (or sometimes as low as 4% for brand extensions). But a product’s actual success depends in large part on factors going beyond how consumers respond to it, such as whether distribution goes according to plan, how ad campaigns perform and what competitors do – so forecasts need to be revised after the product is launched.
Another area where the predictive ability of survey results can be tested is election polls – and in the UK’s last general election the prize for most accurate prediction went to ICM. Martin Boon, head of social and government research at ICM, says: “The opinion polls are the only things which are evaluated against a real-world outcome the next day. Nothing else in market research can be treated like that, so it’s critical not only for the polling agency’s reputation but for the reputation of market research in general.”
Opinion polls generally arrive caked in the mud of controversy, but on the whole they do a pretty good job of predicting election results. But there are always unexpected factors that can send things off course – in 1992 it was the infamous ‘shy Tories’, in New Hampshire in 2008 it was Hillary Clinton crying on TV, and in 2010 it was the Cleggmania phenomenon, which led to significant overestimation of the Lib Dem vote. The deceptive simplicity of a voting intention question hides a wealth of complexity, says Boon, as emotional and social factors play on people’s responses.
New methodologies offer hope of improved predictive power. Surveys designed to measure respondents’ implicit attitudes have been shown to help predict their behaviour, while analysis of social media buzz can be used to track epidemics and forecast elections (see box below).
Claims for the predictive ability of survey research techniques have at times proved controversial. Net Promoter Score, the recommendation metric made famous in Fred Reichheld’s book The Ultimate Question, is billed as a predictor of a company’s future sales growth – but a 2007 study by Tim Keiningham and others concluded that there was no evidence for its supposed predictive power. Still, companies haven’t stopped using it, and Reichheld published The Ultimate Question 2.0 last year.
Facing the future
Some researchers make a living from visualising the future. Martin Raymond is co-founder of The Future Laboratory, which runs the trendspotting network LS:N Global and a research division, Future Poll. The firm runs twice-yearly trends briefings, and members of the LS:N Global network constantly discuss, update and refine trends that it highlights, in response to events.
Facing the future can be scary, and Raymond has periodically had to turn clients away who weren’t open to considering certain scenarios. This has included auto manufacturers who didn’t want to discuss electric cars, retail clients who weren’t willing to talk about e-commerce and hotel clients who couldn’t get over the distinction between mainstream and luxury. “The process is always about collaboration and if a client thinks their view is correct, then we say, OK, we can’t work with you,” says Raymond. “The whole point of a network is that you’re being buffeted constantly by new stimulus and the point is to analyse those from a point of view of where the customer will be when you get this to market – not what you think your brand’s needs are.”
Part of the firm’s job, Raymond says, is to shock clients into realising that change is happening, so that they are ready to recognise and respond to it. One client, he says, described the trend briefing as “like having your head pushed into a basin of cold water” – which, for Raymond, is a good review.
Crowd dynamics
Meanwhile, some researchers seeking to predict the success of new product ideas are putting their faith in the wisdom of crowds. This is the idea that the predictions of everyone in a group about what the group as a whole will do are better than the predictions of each individual about what they themselves will do. The principle can be put in to practice through prediction markets, where participants trade ‘shares’ in a product, proposal or election candidate (see box below). It’s a technique that harnesses the predictive power of the market itself – rather than trying to outsmart it like the traders whom Daniel Kahneman observed.
BrainJuicer CEO John Kearon says prediction markets beat standard survey research hands down in predicting the success of new products and services. He rates market research’s current predictive ability at 7 out of 10, but thinks it could improve to an 8½ or 9 if techniques like this were more widely applied. The difficulty in selling prediction markets as a research methodology, he says, is that “it doesn’t seem plausible”.
By assuming that we are reliable experts on ourselves we fall into the same trap as the experts in Philip Tetlock’s experiment, who were overconfident in their abilities and unable to see their failings. The notion that you can predict what other people will have for lunch tomorrow better than you can for yourself is hard to accept. “It just happens to be true,” says Kearon.
As part of BrainJuicer’s efforts to win clients round, the agency has set aside £30,000 for an investment fund that will use markets to bet on the outcomes of public votes such as The X Factor. But it’s not lack of evidence that holds clients back from embracing prediction markets, Kearon believes – it’s inertia.
“Human beings are odd creatures,” he says. “We do odd things, and the way we buy and use research is no exception. We’re trying to work out ways to get people to change behaviour and buy into these methods, and one thing we already know is that evidence of it being more accurate isn’t the way. You’d think it would be but it isn’t.”
Kearon sees research as “part of a game” – a tool deployed when decisions have to be made, but also when boxes have to be ticked, backs covered and past decisions justified. On top of that comes the risk and hassle of changing from one method to another. Kearon says he is reminded of the observation that science only moves forward when the old professors retire or die. It sounds like a bleak view of the world of research, but Kearon doesn’t let it get to him. “You’ve got to work with human nature rather than throw your arms up about it,” he says. “It’s endlessly fascinating.”
Also fascinating, and just as problematic for research providers, is the value we put on the certainty of pundits when judging their predictions. Agency researchers know that clients pay for clarity and confidence, and interpret ifs and buts as signs of weakness, not wisdom. Similarly, former chancellor Norman Lamont once remarked that he enjoyed reading William Rees-Mogg’s column in The Times because he’s “often wrong but he’s never in doubt”.
But one of Tetlock’s most intriguing observations about predictive ability was the distinction he drew between people who know “many things” and those who know “one big thing”. Broadly speaking, people who have a single overarching belief tend to be more certain about their predictions – and less accurate. Those who can triangulate knowledge from many sources, are capable of self-criticism and are not married to any viewpoint or ideology, will be more cautious in their predictions – and more accurate.
For researchers, this is an argument for a pluralist approach to methodology, an openness to new ideas and a healthy scepticism of received wisdom about both research methodology and consumer behaviour. It also means agencies must strike a balance between communicating a compelling story and not overstating or oversimplifying their case.
Will that approach pay off? We’d be lying if we said we knew.
Some methodologies that offer hope of improved predictive power
http://www.research-live.com/features/whatever-next?%2F4006746.article
Visualising what tomorrow will bring is crucial to what researchers do. But it’s also notoriously difficult. Robert Bain takes a look at the business of prediction.
“We are already on the verge of discovering the secret of transmuting metals… before long it will be an easy matter to convert a truck load of iron bars into as many bars of virgin gold.” Those were the words of Thomas Edison in 1911 predicting scientific advances in the century ahead. By 2011, Edison said, “there is no reason why we should not ride in golden taxi cabs” or “why our great liners should not be of solid gold from stem to stern”.
Edison didn’t live to see his golden taxi cab, and 101 years on from his forecast it still hasn’t shown up. To be fair to him, it’s not difficult to find examples of predictions from the past that were woefully off the mark – and people aren’t getting any more prescient. A 1962 advertisement for Michigan Mutual Liability predicted its customers of 2012 would need insurance for their “picnics on Mars”.
More prosaic predictions can be just as wrong. Many 1960s scholars predicted food shortages in the decade ahead which never came to pass. In the 1980s it was widely believed that Japan was poised to topple the US as the number one world power. And we all remember the anticlimax that was the Y2K bug. Meanwhile hugely significant global events such as the financial crisis and the 9/11 attacks continue to catch us off guard.
In fact half the time we don’t even know what’s happening today, let alone what will happen tomorrow. On New Year’s Eve 2007 the Financial Times predicted that America would not go into recession in the year ahead. They were sort of right – in the sense that the country already was in recession (a fact that would only became clear in economic data released later).
Ask the experts
Clearly, predicting the future is hard – even for experts. In an experiment that ran for 20 years psychologist Philip Tetlock put 28,000 questions about future events to 284 experts in various fields and compared the results with real-world outcomes. Looking back on their performance, Tetlock compared the experts to “dart-throwing chimpanzees”.
Yet despite these failures, we keep making and seeking predictions. We place bets, we listen to pundits, we conduct market research. In his latest book Future Babble journalist Dan Gardner reviews predictions from recognised experts in politics, economics, technology and climate science. “No matter how many times the best and brightest fail, more try,” says Gardner. “And they never doubt they are right.”
Thanks to various psychological quirks from which we all suffer, people whose predictions go awry often don’t accept, or even realise, that they were wrong. But even more worryingly, failed predictions rarely dent an expert’s credibility – people keep listening to them.
Cognitive illusions like these can lead to bad predictions of the value of a company’s stock or of an individual’s professional performance, as Nobel Prize-winning psychologist Daniel Kahneman describes in his new book Thinking Fast and Slow. For most fund managers, choosing stocks is “more like rolling dice than playing poker”, says Kahneman, because despite the knowledge and expertise that traders undoubtedly possess, very few consistently beat the market. The correlation in performance from year to year at a company Kahneman studied was close to zero, suggesting that they were “rewarding luck as if it were skill”.
Similarly, when Kahneman had to evaluate soldiers in the Israeli army for their potential to succeed as officers, he realised that the ones he and his team picked out as the best didn’t do any better than the rest in the long run. But that didn’t stop him. “We knew as a general fact that our predictions were little better than random guesses, but we continued to feel and act as if each of our specific predictions was valid,” he says.
People whose predictions go awry often don’t accept, or even realise, that they were wrong. But even more worryingly, failed predictions rarely dent an expert’s perceived credibility – people keep listening to themSo predictable
All this might sound a bit disheartening. But market researchers haven’t got much choice other than to keep trying to predict the future. And even when the questions at hand are confined to the minutiae of individuals’ decision-making, it’s still not an easy business. So can market researchers really help clients face the future, or are they just chimps throwing darts?
Critics of market research enjoy citing the percentage of new products that fail – a figure that’s different every time you hear it, but is generally agreed to be a large majority. But flops aren’t just a function of bad research – markets can clearly only support a certain number of new products, so research can only reduce the odds of failure so far. Besides, a bit of healthy trial and error can do you good – just look at Google.
SPA Future Thinking forecasts sales for new consumer products, and claims margins of error of +/-9% (or sometimes as low as 4% for brand extensions). But a product’s actual success depends in large part on factors going beyond how consumers respond to it, such as whether distribution goes according to plan, how ad campaigns perform and what competitors do – so forecasts need to be revised after the product is launched.
Another area where the predictive ability of survey results can be tested is election polls – and in the UK’s last general election the prize for most accurate prediction went to ICM. Martin Boon, head of social and government research at ICM, says: “The opinion polls are the only things which are evaluated against a real-world outcome the next day. Nothing else in market research can be treated like that, so it’s critical not only for the polling agency’s reputation but for the reputation of market research in general.”
Opinion polls generally arrive caked in the mud of controversy, but on the whole they do a pretty good job of predicting election results. But there are always unexpected factors that can send things off course – in 1992 it was the infamous ‘shy Tories’, in New Hampshire in 2008 it was Hillary Clinton crying on TV, and in 2010 it was the Cleggmania phenomenon, which led to significant overestimation of the Lib Dem vote. The deceptive simplicity of a voting intention question hides a wealth of complexity, says Boon, as emotional and social factors play on people’s responses.
New methodologies offer hope of improved predictive power. Surveys designed to measure respondents’ implicit attitudes have been shown to help predict their behaviour, while analysis of social media buzz can be used to track epidemics and forecast elections (see box below).
Claims for the predictive ability of survey research techniques have at times proved controversial. Net Promoter Score, the recommendation metric made famous in Fred Reichheld’s book The Ultimate Question, is billed as a predictor of a company’s future sales growth – but a 2007 study by Tim Keiningham and others concluded that there was no evidence for its supposed predictive power. Still, companies haven’t stopped using it, and Reichheld published The Ultimate Question 2.0 last year.
Facing the future
Some researchers make a living from visualising the future. Martin Raymond is co-founder of The Future Laboratory, which runs the trendspotting network LS:N Global and a research division, Future Poll. The firm runs twice-yearly trends briefings, and members of the LS:N Global network constantly discuss, update and refine trends that it highlights, in response to events.
Facing the future can be scary, and Raymond has periodically had to turn clients away who weren’t open to considering certain scenarios. This has included auto manufacturers who didn’t want to discuss electric cars, retail clients who weren’t willing to talk about e-commerce and hotel clients who couldn’t get over the distinction between mainstream and luxury. “The process is always about collaboration and if a client thinks their view is correct, then we say, OK, we can’t work with you,” says Raymond. “The whole point of a network is that you’re being buffeted constantly by new stimulus and the point is to analyse those from a point of view of where the customer will be when you get this to market – not what you think your brand’s needs are.”
Part of the firm’s job, Raymond says, is to shock clients into realising that change is happening, so that they are ready to recognise and respond to it. One client, he says, described the trend briefing as “like having your head pushed into a basin of cold water” – which, for Raymond, is a good review.
Crowd dynamics
Meanwhile, some researchers seeking to predict the success of new product ideas are putting their faith in the wisdom of crowds. This is the idea that the predictions of everyone in a group about what the group as a whole will do are better than the predictions of each individual about what they themselves will do. The principle can be put in to practice through prediction markets, where participants trade ‘shares’ in a product, proposal or election candidate (see box below). It’s a technique that harnesses the predictive power of the market itself – rather than trying to outsmart it like the traders whom Daniel Kahneman observed.
BrainJuicer CEO John Kearon says prediction markets beat standard survey research hands down in predicting the success of new products and services. He rates market research’s current predictive ability at 7 out of 10, but thinks it could improve to an 8½ or 9 if techniques like this were more widely applied. The difficulty in selling prediction markets as a research methodology, he says, is that “it doesn’t seem plausible”.
By assuming that we are reliable experts on ourselves we fall into the same trap as the experts in Philip Tetlock’s experiment, who were overconfident in their abilities and unable to see their failings. The notion that you can predict what other people will have for lunch tomorrow better than you can for yourself is hard to accept. “It just happens to be true,” says Kearon.
As part of BrainJuicer’s efforts to win clients round, the agency has set aside £30,000 for an investment fund that will use markets to bet on the outcomes of public votes such as The X Factor. But it’s not lack of evidence that holds clients back from embracing prediction markets, Kearon believes – it’s inertia.
“Human beings are odd creatures,” he says. “We do odd things, and the way we buy and use research is no exception. We’re trying to work out ways to get people to change behaviour and buy into these methods, and one thing we already know is that evidence of it being more accurate isn’t the way. You’d think it would be but it isn’t.”
Kearon sees research as “part of a game” – a tool deployed when decisions have to be made, but also when boxes have to be ticked, backs covered and past decisions justified. On top of that comes the risk and hassle of changing from one method to another. Kearon says he is reminded of the observation that science only moves forward when the old professors retire or die. It sounds like a bleak view of the world of research, but Kearon doesn’t let it get to him. “You’ve got to work with human nature rather than throw your arms up about it,” he says. “It’s endlessly fascinating.”
“Human beings are odd creatures. We do odd things, and the way we buy and use research is no exception. Evidence of a method being more accurate isn’t the way to get people to buy into it”Known unknowns
John Kearon, BrainJuicer
Also fascinating, and just as problematic for research providers, is the value we put on the certainty of pundits when judging their predictions. Agency researchers know that clients pay for clarity and confidence, and interpret ifs and buts as signs of weakness, not wisdom. Similarly, former chancellor Norman Lamont once remarked that he enjoyed reading William Rees-Mogg’s column in The Times because he’s “often wrong but he’s never in doubt”.
But one of Tetlock’s most intriguing observations about predictive ability was the distinction he drew between people who know “many things” and those who know “one big thing”. Broadly speaking, people who have a single overarching belief tend to be more certain about their predictions – and less accurate. Those who can triangulate knowledge from many sources, are capable of self-criticism and are not married to any viewpoint or ideology, will be more cautious in their predictions – and more accurate.
For researchers, this is an argument for a pluralist approach to methodology, an openness to new ideas and a healthy scepticism of received wisdom about both research methodology and consumer behaviour. It also means agencies must strike a balance between communicating a compelling story and not overstating or oversimplifying their case.
Will that approach pay off? We’d be lying if we said we knew.
Tomorrow’s world
Some methodologies that offer hope of improved predictive power- The Iowa Electronic Markets, run by the University of Iowa’s Henry B Tippie College of Business, are perhaps the best-known example of prediction markets in action. Participants use real money to bet on the outcomes of elections and other events by buying or selling ‘shares’ at between $0 and $1 – with the promise of receiving a full $1 for every share they hold in the correct result when it is announced. As people trade, the price fluctuates and is used to predict the final result. Since the markets were set up in 1988, they have come up with more accurate election predictions than the opinion polls in about three quarters of cases.
- Specialised online surveys can measure people’s gut reactions to quickfire words and images. These tests analyse not only what choices people make but also other factors such as how quickly they choose. Head-to-head tests of implicit and explicit responses have shown implicit measures to be a better predictor of subsequent behaviour.
- Social media and the rise of ‘big data’ have created an unprecedented view of what people are doing at a given moment. Google’s Flu Trends service, launched in 2008, showed that monitoring the number of people searching for information about flu symptoms could provide a rapid and accurate way of tracking the spread of the disease – closely matching the official data but available much
more quickly. - Experiments have been carried out to predict election results based on the volume and sentiment of social media chatter about political candidates. A 2010 study at Carnegie Mellon University found that analysis of Twitter data could rival polls as a way of tracking US public opinion over time, while social media service Tweetminster analysed Twitter buzz to predict the last UK general election result with an average error of just 1.75 points – better than some of the traditional polls.
lunes, 5 de marzo de 2012
(2) John Allen Paulos y la variación estadística
Veamos
también las precursoras de las ideas de variación estadística: desviación
estándar, varianza, etcétera. Se trata de insólito, peculiar, extraño, singular,
original, extremo, especial, diferente, único, anormal, distinto,
dispar, raro, demasiado, etcétera. Una expresión como fuera de lo común,
que indica algo extraordinario, viene muy al caso, porque una observación que
está en la «cola» de la gráfica de una distribución estadística está fuera de lo habitual y señala una gran desviación de la magnitud en cuestión.
Con el tiempo, cualquier situación o entidad que se repita sugerirá la idea de excepción. Si unos acontecimientos son corrientes, otros son raros.
Tomado de: “Erase
una vez un número”. John Allen Paulos. Tusquets
Sombrías perspectivas para los hombres estadounidenses
No sólo los niveles de testosterona sérica de los hombres se han reducido en un 20 por ciento en las últimas décadas (New England Research Institute, 2007), para un hombre es menos probable que le vaya bien en la escuela secundaria, que se gradúe en la universidad, o que encontre trabajo.
De acuerdo con datos del Departamento de Educación, en 1975 los hombres obtenían un 60 por ciento de todos los grados de la universidad. En 1985, hubo distribución equitativa por género. Pero en el año 2009, el péndulo había oscilado en favor de las mujeres. De los más de 3 millones de títulos universitarios (promoción de 2009), las mujeres obtuvieron cerca del 60 por ciento de los grados. Para el año 2017, el Departamento de Educación estima que las mujeres obtendrán más de 160 grados por cada 100 de los hombres.
Texto completo (en inglés) aquí:
http://www.adweek.com/sa-article/man-down-138397
Foto: According to a May 2008 survey of American men for Jockey International, 9% of American men have underwear which is at least 10 years old, while another 15% have underwear which is at least 5-9 years old.
Source: USA Today, 8/21/2008
Shygantic (flickr 2006)
De acuerdo con datos del Departamento de Educación, en 1975 los hombres obtenían un 60 por ciento de todos los grados de la universidad. En 1985, hubo distribución equitativa por género. Pero en el año 2009, el péndulo había oscilado en favor de las mujeres. De los más de 3 millones de títulos universitarios (promoción de 2009), las mujeres obtuvieron cerca del 60 por ciento de los grados. Para el año 2017, el Departamento de Educación estima que las mujeres obtendrán más de 160 grados por cada 100 de los hombres.
Texto completo (en inglés) aquí:
http://www.adweek.com/sa-article/man-down-138397
Foto: According to a May 2008 survey of American men for Jockey International, 9% of American men have underwear which is at least 10 years old, while another 15% have underwear which is at least 5-9 years old.
Source: USA Today, 8/21/2008
Shygantic (flickr 2006)
jueves, 1 de marzo de 2012
(1) John Allen Paulos y la tendencia centralizadora
A propósito de la Estadística, ciencia indispensable para la investigación de mercado, hemos decidido compartir estos deliciosos fragmentos del libro Erase una vez un número de John Allen Paulos (Tusquets).(1) Tendencia centralizadora Pensemos en primer lugar en las nociones de tendencia centralizadora: media, mediana, clase modal, etcétera. Lo más seguro es que surgieran de palabras cotidianas como habitual, acostumbrado, típico, mismo, regular, mayoría, clásico, estereotipo, esperado, vulgar, normal, corriente, medio, convencional, tópico, mediano. Cuesta imaginar a los prehistóricos, incluso a los que carecían del vocabulario descrito, sin algún barrunto de lo típico. Es de creer que fenómenos o seres como las tormentas, los animales y las piedras que se presentasen una y otra vez condujeran de manera natural a la idea de recurrencia típica o media.
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