INNOVATION

Breakthrough Consumer & Shopper Insights From Behavioral Economics (Quantitative, Qualitative, Worldwide)

FILL AN INNOVATION PIPELINE

 

Innovation fuels growth; organizations that innovate more grow their business by an extra +3% yearly compared to other organizations. But the journey towards innovation starts with ideas.

We accompany our customers in the process of generating ideas or finding applications for an upstream technology. There are several approaches that we use to find consumer-relevant ideas; from immersion to co-creation with consumers.

ALLOCATE RESOURCES TO INNOVATION

 

There is no one-size-fits all research plan for new product development. Each innovation has specific characteristics, related risks and killer issues that need to be addressed at the different stages of innovation development.

We view innovation as game changing, break-through or tactical. Using our tiering model, we help customers allocate resources across innovation projects based on risk, budget and speed.  

We adapt our involvement in the innovation research process based on this tiering; stepping up our operational involvement to free capacity or increasing business consultancy.

PRIORITIZE IDEAS

 

We trim down the number of ideas based on consumer interest.

Our credo is to measure consumer interest based on the choices they make and benchmark these choices with existing or comparable products. Together with the screening, we collect extra feedback from consumers to make the winning ideas even bigger.

STRENGTHEN CONCEPTS

 

We explore concept descriptions and visual territories for new products to make them stronger.

We typically prioritize depth in concept research, and use a mix creative and traditional consumers to explore their emotional connection with different conceptual routes. We demolish concepts and rebuild them with their most promising features.

We aim to get out of concept exploration with ready to use material; stimuli for quantitative testing, communication or design briefs.

DESIGN SELF-SELLING PACKAGING

 

In-store context drives the majority of purchase decisions; investing in product packaging so that it stands-out of cluttered shelves is one of the cheaper ways to increase sales.

Shoppers make choices mostly unconsciously, so declarative feedback on packaging is typically over-rationalized and not predictive of packaging success.

Our approach to packaging testing addresses these shortcomings. We combine purchase simulation in real competitive context with targeted shopping metrics and diagnostics. This way we activate the same consumer sensory and cognitive processes and significantly improve the quality of packaging success metrics, which leads to more accurate packaging decisions.

MAKE STRONG CLAIMS

 

Pack and in-store claims can boost sales by up to +6% and do not generate incremental production costs, making them a great marketing lever.

Like with packaging testing, we recommend to test claims in their competitive environment. This enables more accurate impact estimates for claims.

For quicker work or early screening, other methodologies like the MaxDiff can be used; for more in-depth work, we can deep dive in consumers emotional reactions to claims.

MAXIMIZE INNOVATION SUCCESS RATE

 

Despite the great focus and energy organizations put on innovation, the success rate of new products matches that of a coin-flip at best.

To increase the predictive power of innovation qualification research, we simulate consumer purchase behavior in context, with new product packaging and communication or advertising to replicate real launch situation. Respondents go through the same cognitive and choice process as consumers would at time of launch, improving the reliability of the assessment.

Our approach is particularly recommended when the risk of new launch is high and the business teams needs a consumer-based go/no-go recommendation.

Our approach can be tied to a proprietary agent-based forecasting model. We use the purchase patterns observed in quantitative research to simulate the behavior of each consumer after launch. We model the impact of marketing and in-store stimuli on each purchase occasion; aggregating purchases over time we estimate the most likely trial and repeat rates for the innovation. The model has been validated in most FMCG product categories across countries.   

All-in-all, our approach can multiply innovation success rate by a factor 2 to 3.

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