Let the words of the user be the base of your next product!

We help our customers to take to the right decisions in the product development life cycle by identifying user attitudes on social networks. Our help is not in terms of consultancy, but is based on the delivery of VoU, a platform which allows product teams to be completely autonomous in the discovery of “killer features” of the new product.

VoU is based on a big data compliant architecture (we do not do much buzz about it, but yes we are dealing with big data!) where several world class Artificial Intelligence libraries have been injected, notably in the domain of Natural Language Processing. Shortly, the main steps to deliver you key indicators about your new product success are the following:

Sources Selection


In this phase you select the most pertinent social networks, with the support of Innoradiant experts. These are not necessarily the most popular, but just the most pertinent to the product you are planning. In this phase all relevant spontaneous user interactions are stored locally for being processed.

Product Feature Selection

The starting point of this phase is the identification of what your future product looks more like (target product). If it is an enhancement of a previous version, the choice is reasonable easy. If it is a brand new product, something the market never saw, then target products must be identified by analogy.  Once the similar product(s) has been identified, thanks to the application of optimized Natural Language Processing algorithms, VoU detects how users characterize it, i.e. which features are more often taken into consideration. Optionally you can normalize these spontaneous expressions to connect the words of users to your internal organization of knowledge.

Detect Attitudes

At this stage you know  what are the most popular features of the product under conception/design. But popularity  is just one side of the complex polygon of  user attitudes. In order to drive your innovation you must be able to answer questions such as “Is this feature connected with an intention to buy?”, “Do they need that feature or they consider it as redundant?” “Do that feature raise enthusiasm or, on the contrary, it is blamed as inappropriate?”… VoU captures these product-related attitudes and disclose them to you as an easy to use dashboard.


Patterns Towards Innovation

At Innoradiant we recognize that sometimes product innovation is so visionary that it is difficult to find “analogous products” to feed the research. In these cases the process become “event-driven” rather than “object-driven”. For instance if you want to deliver a cutter specially fit to cut plexiglas, you might want to track events of people cutting plexiglas, as well as the outcome of that process, rather than features of cutters. We can answer this as well!