An efficient alternative to concept optimisation

Innovation research – an art and a science 

The art is evident in the workshops, ideation sessions, and concept-building huddles that take place at the earliest stages of innovation. This is where creativity, imagination and ingenuity meet to form the keys to success.

And then there’s the science. This happens when quantitative testing, optimisation, and modelling help to steer the concept to success. Often there are multiple combinations of product features, benefits, branding, price- points, packaging and insights to measure as the optimum combination for the greatest market potential is sought. This can get even more complex when estimating trial potential, ‘what if’ simulations and volume forecasts.

Readers will be familiar with the empirical tools used to evaluate these factors. However, there seems to be a missing piece—one that our clients are increasingly asking us to provide.

The piece in question is the recipe for what consumers want from the concept. Specifically, what is the best combination of elements to include in a concept? Our clients narrow down the best insights, benefits, reasons to believe and other elements to include in the concept. What they still need to know is which combination of these elements will yield the greatest consumer appeal in the most efficient way.

So, how do we do this in a way that nurtures unique, disruptive ideas versus a natural selection method which rewards common, close-in ideas? While most concept optimisation tools employ choice or purchase intent—which kill anything that is different from what’s already in the market— we at Ipsos find that solutions that actually reward uniqueness are much better in the long run. 

Getting to the best concept

For this sort of work, many readers will be familiar with conjoint trade-off methodology. There are many variations of this but all they will do on their own is identify the winner of the bunch – but not if the eventual ‘winner’ actually has sufficient appeal to the target consumer, with current competing options factored in.

So we find that the key is to also have the various concepts rated on three key factors: relevance, expensiveness, and differentiation.

These measures, which are proven success factors, are defined as follows:

The extent to which an innovation meets consumer needs.

The extent to which an innovation is perceived to be higher-priced than competitors (higher price points are not always bad of course, but price points have to be justifiable via high performances on the other two measures here).

The extent to which the innovation provides unique benefits versus competitors. 

By testing in a competitive context and using appropriate modelling, results from this kind of analysis can be delivered quickly and flexibly, so no further re-testing is usually necessary. Another key benefit from using these three measures is that they are not biased toward familiar concepts like line extensions, so we can be confident that disruptive concepts with high potential will not be killed.

In addition, by looking at how each concept performs across these three variables it is also possible to profile the nature of each concept’s profile – e.g. whether it has the markings of being a true winner; simply an also-ran; a breakthrough concept; or perhaps a niche or premium option – all of which require different go-to-market strategies.

Armed with this information, product innovators can choose the best possible concept to move forward with; understand its strategic role in the innovation portfolio; and predict how well it will perform in-market.

The high failure rate of newly launched products has often been cited in marketing circles, but that need not be the case anymore. 

  • This piece was written by Lee Markowitz, Lucy Robles, Luis Abimerhy and Jonathan Dodd, Ipsos 
  • Please contact: Jonathan Dodd, research director, Ipsos NZ, [email protected]

This story is part of a content partnership with Ipsos. 

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