Seminario web: Acelera el crecimiento de tu marca con el análisis de los factores clave
Descubre qué es lo que más valoran tus clientes y consigue una ventaja competitiva.
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The Sawtooth Software Conference brings together research and analytics professionals to deepen their knowledge and get hands-on training on the latest conjoint analysis methodologies. As a longtime Sawtooth Software partner, a team of SKIMmers will once again share our choice modeling expertise with industry peers in Orlando.
Our methods and analytics experts from across the U.S. and Europe will present various technical papers, workshops and tutorials on a range of choice modeling topics. Be sure to attend of our sessions or chat with us to learn about exciting career opportunities.
Amplía tus conocimientos sobre análisis de datos: participa en las ponencias de expertos de « SKIM »
Managing Director, US
A veces, los estándares no bastan para responder a las preguntas de investigación que se plantean, y hay que salirse de los caminos más transitados. Nos gustaría que te sumaras a este taller de cuatro horas sobre aplicaciones avanzadas. En él nos centraremos en varias extensiones complejas, pero muy interesantes, de la modelización de elecciones, entre las que se incluyen:
- Técnicas de diseño estadístico personalizadas (diseños realizados con Lighthouse Studio y Excel; por ejemplo, diseños específicos para alternativas, desequilibrio de frecuencias, reglas de fijación de precios) y las implicaciones de estas personalizaciones
- Mostrar diferentes métodos de codificación
- Soluciones provisionales para el problema del autobús rojo y el autobús azul
- Y algunas otras soluciones prácticas
Senior Director Methodology & Innovation EU
Co-clustering is the simultaneous clustering of rows and columns of data. For example, when used for rating questions, or MaxDiff scores, it provides excellent insight into the underlying heterogeneity of this data: which respondents are similar and which items are similar. Adding covariates in the process – both for respondents and for the variables! – adds another layer of insights. This paper will show different ways of visualising co-clustered data and explain the heuristics on how to do co-clustering with covariates.
PayPal
VP, Methods & Analytics, US
PayPal and SKIM recently developed a pragmatic approach to isolate behavioral drivers of consumer shopping journey at the digital checkout stage among online merchants. We innovated on survey design experience by simulating checkout experience and combining conjoint and non-conjoint analytics. Further, we translated answers into actionable business recommendations that were accessible to non-technical audience as well. This innovation elevated Checkout workstream as a strategic priority at PayPal and adoption of these recommendations to the product, marketing and sales roadmap.
VP Methodology, US
Are we overfitting our models with how we are estimating our price parameters?
Complicated pricing studies can end up with a lot of part-worth levels of price. From recent conferences, a piecewise function that uses from 2 to 6 breakpoints (aside from the endpoints) is recommended and 12-20 breakpoints have been seen as potentially useful. We would want to investigate whether a dozen or more breakpoints is an overfit and we are better off with a more parsimonious approach. This investigation will also test if it would be best to have multiple simpler price effects. RLH, Holdout Hit Rate, and % of effects that don’t need to be constrained will be used as testing criteria.
Manager
Director adjunto
Thompson sampling in multi-attribute CBC
Often, we run into the challenge that we can only test a certain number of levels per attribute to make sure the estimation remains robust. However, there are scenarios in CBC studies where we want to test many more levels and we just want to find out what the best levels and combinations of levels are. By employing Thompson Sampling, we select preferred products to oversample for each new respondent.
Senior Director Methodology, EU
Volumetric Conjoint and the role of assortment size
Predicting the volume of a new product to be launched is a task that many researchers have done at least once. There are a variety of methodologies to accomplish the task, which are grouped in three families: real-life tests, benchmarking, and replication of market environments. In this paper, we show the pros and cons of each of them and explain an approach that oversteps some of the limitations of these methods by using them in combination.
Senior VP, Methods & Analytics, US
Vector Autoregressive Modeling of Longitudinal sales data using simulated Populations Informed by Conjoint experiments
Vector Autoregression (VAR) is often used for modeling sales of P items over time. VAR forecasts sales at time tnew using previous sales at tlag, coupled with attributes explaining those changes like price, distribution, and trend. We also model correlated sourcing among P items using a simulated population ~ Multivariate normal(α_lag, ∑). We show how to use conjoint experiments to inform ∑ and how that significantly improves predictions versus modeling ∑ from sales data alone.
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Acerca de Sawtooth Software
Sawtooth Software ofrece « advanced analytics » y análisis que ayudan a las organizaciones a comprender qué es lo que más importa a sus clientes y a predecir qué comprarán o elegirán. Para ello, recurre a su plataforma de soluciones, a sus servicios de consultoría y a sus servicios formativos.
La plataforma Sawtooth permite realizar encuestas tradicionales, pero es más conocida por una solución integrada de análisis predictivo denominada «análisis conjunto» o «análisis de elección».
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