Boost your Product Innovation SKIM Virginie Jesionka | Mini Kalivianakis

When thinking of

developing an

innovative product,

many features can be

varied to build an

optimal concept.

For a phone, you can

think of coverage,

camera type,

waterproof option,

storage…

SD 5 MP SD 4 MP SD 5 MP

A typical market research solution is to combine

different levels of each product feature to create

concepts, to have them evaluated by respondents

and to estimate the value of each level.

When it comes to accumulating the different

product features and levels, the amount of

combinations quickly adds up.

This means that each individual concept might be

seen by very few (or no) respondents.

In some areas, that’s not a problem : for example

in telecom. Putting the best levels of all product

features together, will give you the best phone.

But when it comes to optimizing FMCG

products, the overall concept needs to

make sense and drive a coherent

message which fits the brand image.

Treating your concept as a

sum of perfect levels is a

risk, and could lead to a

“Frankenstein effect” as

nobody - or very few

respondents - really

evaluated the final concept.

This situation arrives very quickly as

already 4 features with 4 levels leads

to 256 possible combinations…

NO LIMIT

As we are in the early

stage of the innovation

process, this is the time

where creative ideas

should have their place.

No constraints should be

made in the amount of

levels and features to try.

In a nutshell, our dynamic optimization method

is about considering all the possibilities (all

features with all different levels), while finding

the best concept that has been evaluated by a

sufficient amount of respondents.

Our solution is to break down the optimization process into steps.

Each step consists of creating a few concepts, having them evaluated

by respondents, running a regression to identify the worse levels and

removing them from the set up.

By doing so, we learn more an more at

each step on the preferred concepts.

10

60

In the very last step, all final (10)

concepts are being evaluated by a

sufficient set of (60) respondents.

This allows a very good read on the

winning concept.

So far for the theory.

In practice, we program all this step-

wise approach in advance. We

determine sample size, levels to be

removed and experimental designs.

So once we go into field, our

optimization algorithm works on his

own until it gives us the solution.

Let’s go through a case study

regarding an anti-parasite

product packaging.

The goal was to optimize their

current packaging.

Design, color, cat picture, claim, logos… Many pack

features could vary, leading to 108,000 possible concepts.

How likely would you be to purchase this product?

Extremely unlikely

Neither Likely nor unlikely

Extremely likely

Respondents

were facing a

5 minute

evaluation

survey with 10

screens with a

different pack

to evaluate.

In the end, with 400 respondents, the possibilities were narrowed

down in a step-wise process to an optimal concept which proved

to be significantly better than the current packaging.

At the end of this optimization process you will

have a clear recommendation on the best

concept (or set of winning concepts), with

performance indicators for all features & levels.

Additionally, qualitative insights on why and

how can be provided for the winning concepts.

-

+

Respondents can click on concept elements and provide

(open end) feedback on what they like most and least.

PRODUCT CONCEPT BROCHURE ADVERTISEMENT

This dynamic optimization approach has multiple

applications, anything combining text and visuals.

Boosting

product innovation

Robust results

No Frankenstein

No limit in options

Boost your Product innovation

Mini Kalivianakis m.kalivianakis@skimgroup.com

+31 10 282 3551

Virginie Jesionka v.jesionka@skimgroup.com

+31 10 282 3532