The pressure to decide whether to launch a new product is nothing new – and with massive investments required for new product development (NPD), many brands might forgot their NPD efforts, especially during times of economic pressure.
But uncertain times have proven to be the mother of innovation, and now is the time to think about pushing out new products and tapping into changing consumer needs.
Here’s everything you need to know about the latest NPD market share projection framework, designed to estimate the in-market success of newly developed products by leveraging virtual environments.
What is the crucial first step in NPD testing?
One of the most important steps in every research study is screening. Recruiting the right target audience is critical, especially for a new product launch strategy. That’s why it is necessary to take steps to pinpoint the right target audience for each study and to do so diligently.
Nowadays, most automated research platforms on the market only allow researchers to pick category shoppers, at best. Driven by this, we ensured that our solution is highly customisable and tailored to each study – by adding more granular subcategory criteria, including usage frequency, understanding brand awareness and openness to purchasing the new product, and even filtering the geolocation in some cases. With every added testing criterion, the potential risk of a new launch gets smaller.
On top of this, with the remote research approach, we can conduct studies in over 40 countries across the globe via respondents’ mobile or desktop devices, enabling our clients to tap into any market.
How does this solution ensure in-store and digital innovation success?
As the world of e-commerce continues to take the world by storm, more and more brands have been on a mission to establish their online presence. So it goes without saying that, nowadays, most new products end up on both the in-store and digital shelves. But what works in digital might not have the same impact in B&M, and vice versa.
This is where the contextual research for our NPD solution comes into play. Given that our tests are conducted remotely and on respondents’ devices to enable the findings’ scalability, developing highly realistic virtual shopping environments was essential. So when it comes to new product launches in stores, we are able to recreate any store or retail environment with high accuracy, allowing shoppers to buy products as they normally would.
With eye tracking, we can also measure respondents’ gazes to understand what they are or are not looking at and whether they are noticing the new product on the shelf. The same goes for e-commerce: we can develop websites or webpage mock-ups such as Amazon, Target, and Kroger, and let respondents shop and explore as they do in real life, while we collect data about their shopping behaviour.
Having the ability and agility to put them in a context that feels familiar and authentic, and to do so remotely for any market, is undoubtedly key to estimating the success of any new product launch strategy.
Why is a sequential monadic approach king in innovation testing?
In order to really capture switching behaviour and potential cannibalisation effects, EyeSee’s NPD solution rests on the premise of having the same people make two shopping purchases: one in a competitive environment before the new product’s introduction, and another one with the new product launched and implemented on the shelves or webpages.
Of course, there can be certain bottlenecks with this approach, which is why it was crucial to develop tactics that overcome the potential downsides of sequential design – such as putting a cognitive load on people’s working memory with different memory tasks between purchases, exposing them to marketing materials, catalogues, or newsletters with the NPD incorporated, and so on.
What does an NPD study entail and uncover?
To help paint a picture of what a market share estimation study for brick-and-mortar stores looks like, we conducted an NPD study that aimed to verify the EyeSee NPD solution against real-life sales data. Just like any NPD, the tested product had a specific proposition: it came from a beloved and trusted brand that is a category leader, but it aimed to enter a completely new space – the breakfast category. With its packaging type and position on the shelf, this product represented an alternative to instant oatmeal breakfasts.
Just a few months before our study, the new product hit the shelves on the local market, allowing us to longitudinally follow the development of its sales on the one hand and to conduct the study among consumers unaware of its existence on the other. This in turn provided the insights that confirmed our NPD solution based on virtual shelves, giving a reliable estimate of real NPD sales in the first year of launch.
Additionally, the switching analysis on the SKU level uncovered that not only oatmeals but also some less expected breakfast categories represent relevant competition to this NPD. Consumers don’t switch just within the same product category and packaging type, but within the same flavour, price range, and consumption purpose.
This article was first published in the Q3 2022 edition of Asia Research Media