We use qualitative and quantitative research methods coupled with experiments, biometrics, big and small data, and many more data sources to gain insights.
But this is only part of the story, as our Unique Research Framework is 3-Dimensional. Our research framework takes shape from integration of each of its 3 dimensions:
- Selecting the right source of data
- Measuring the right metrics
- Knowing how to interpret the data
Data Sourcing
Observation
Experiments
Tracking
Questioning
Biometrics
Proprietary data / CRM
Social / Online listening
Blockchain
Experiments
Tracking
Questioning
Biometrics
Proprietary data / CRM
Social / Online listening
Blockchain
Measurements
Behaviors
Declarative
Contextual Feedback
Attention
Emotions
Implicit
Declarative
Contextual Feedback
Attention
Emotions
Implicit
Data Interpretation
Behavioral Economics Framework
Text Analytics
Artificial Intelligence
Predictive Modeling
Evidence-based Recommendations
Hard & soft business Expertise
Text Analytics
Artificial Intelligence
Predictive Modeling
Evidence-based Recommendations
Hard & soft business Expertise
Innovation
The growth model of multinational companies in the past 20 years has been behind incremental innovation. The problem is that half of these innovations fail in market because of their inherent lack of disruptiveness.
Failing innovation leads to poor financial results, business fragmentation and brand erosion. Lack of disruptive innovation eventually leads to obsolescence.
We accompany our customers in their journey through innovation, from insights discovery, ideas generation, screening and development until in-market activation.
We work with agile processes to get the best of innovation projects to increase their success rate by a factor 2 to 3.
Ideas Generation
We help our customers in the process of generating ideas or finding applications for upstream technologies. There are several approaches that we use to find consumer-relevant ideas with qualitative and quantitative research.
We found that online listening, consumer immersion, observation and mobile ethnography tend to provide the best insights at early stages of the idea generation process, when starting with a blank sheet of paper.
More structured approaches like our version of the KANO model, conjoint and other early screening approaches are most useful when technologies are (more) narrowly defined.
Auction-based Innovation Screening
We have been struggling for a long time – just like everyone else – to find a tool providing accurate pre-screening of ideas while making it easy and efficient for business and R&D teams.
We have finally developed our own screening methodology to achieve predictive power in a time and budget efficient way, combining the lessons from ‘The wisdom of crowds’ with game theory.
The methodology uses an auction mechanism which incentivizes respondents to play our game seriously, so that proven auction Nash-equilibria can be applied to innovation ranking.
Innovation Pre-testing
Our credo is to maximize predictive power of pre-testing by measuring consumer behaviors in the most realistic context possible.
Depending on the iteration or the progress in the development stage of a new product or service, different stimuli should be used, but the same overall testing approach should be followed to keep comparability at every step of the development process.
The approach entails experimental design, context and framing so that respondents go through the same cognitive processes as consumers would at time of launch, improving the reliability of pre-testing.
Output can be tied to our proprietary agent-based forecasting model to assess the potential of new products in financial terms.
All-in-all, our approach can multiply innovation success rate by a factor 2 to 3.
Behavioral
Behavioral research is at the heart of what we do. The Behavioral Economics Framework we developed back in 2012 has been providing dependable guidance in numerous projects, both in design and delivery phases.
In addition, we systematically explore new technologies to assess whether they can add relevant new measurements to the set of behavioral metrics we used as part of our framework.
Through this constant focus we have integrated biometrics, sensor-based tracking, online and mobile behavior tracking technologies as well as academic/experimental methods into our behavioral research arsenal.
In-store Tracking
Context matters in human choice; and purchase choices happen in a store.
We use AI-based tracking technology to provide detailed measurements of in-store behaviors at an aggregate level.
In-store tracking can be applied to most questions relating to shopper and [brick & mortar] store optimization. The approach is versatile: it can be used to gain superior insights on path to purchase, impact of smartphone on behaviors at the point of sales, traffic, category planogram or in-store activation activities.
E-commerce Simulations
eCommerce is deeply reshaping the retail landscape. Much has been said, but little has proven helpful. So, we developed a new solution to gain insights on the online retail landscape.
We use a technology that simulates realistic eCommerce environments and built upon it.
All actions are tracked in test environments – path, scroll, search, basket – with the same granularity as Google Analytics. We combine these behavioral metrics with targeted questions to add depth of insights (the why) to accurate measurements (the what and how).
The approach is versatile: it can be used to assess conversions in different scenarios involving different keywords, results pages/ranking, product or corporate pages, eCom assets, ads and other stimuli/activities.
Consumption Tracking
‘What gets measured gets managed’ is a well-known adage. Today, disproportionate attention is devoted to sales data, because it is available, but very little attention is spent on consumption data, because it is hard to get. Understanding consumption better than competitors provides competitive advantage.
We use a proprietary methodology that accurately measures category and brands consumption.
Our methodology tracks how consumers consume a specific product category over time. The data gathered provides a wealth of granular information which could historically only be captured in ‘Habits & Practices’ projects in a ‘not-so-accurate’ and ‘one-off’ manner.
The methodology enables assessing brand share of consumption and total market size regardless of where products are bought, including online, boutique or cross-border.
Occasion-based Insights
Life is made up of moments. Brands and products fight for a share of relevance in particular moments, but these moments can be quite elusive to managers.
We use mobile ethnography technology to gain rich insights about those moments that are most important for brands, from purchase context to consumption occasions.
Mobile platforms provide rich content related to consumers’ lives in the form of videos, pictures and voice, which are super-useful to intuitively grasp and communicate insights.
The technology can also be used to track behaviors over time, in what one could call diaries 2.0.
Tailored
Smart Insights on Demand
Agility is a key ingredient for success in the competitive markets of today, but it shouldn’t come at the expense of quality or work-life balance. Smart Insights on Demand is our unique methodology to give managers professional DIY research: Meaningful Answers, Fast & Hassle-Free.
Research is fully customizable to the pressing business questions faced by the organization.
It is high quality, as it is grounded in a robust sample size, and in our expertise in answering exotic questions with tailored research.
It is fast: Count 3-days to insights delivery.
Finally, it is hassle-free: we take on all work from the business problem to vividly presented answers in a PowerPoint deck.
We use cutting-edge techniques and approaches, but most importantly we select and combine those tools with single focus on the questions that need answering.
Case studies provide a glimpse of what’s possible.