PERSONALISATION
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How R&D data can create new digital services
Jamie Downing – Tessella, UK
Data driven digital services are everywhere, from health apps to skin care subscriptions, transforming how companies interact with customers. Very often they come from digital startups, looking to steal market share from established companies. But now, thanks to increasingly
sophisticated AI and data science capabilities, established consumer product companies have a way to fight back: using their extensive R&D data. And in doing so, they will be able to gather invaluable new data for product development.
Why do digital services matter to R&D? To see how this might work, imagine a new skin care subscription service. Any old startup can develop a model to track preferences, optimise delivery, and suggest similar products. If they are smart, they can refine recommendations by broad customer groups using publicly available data on skin types or weather data. But this data is easily accessible, and anyone can do it. Established skin care brands, on the other
hand, have vast R&D data that no one else has access to. Within this are detailed secrets about absorption, scent, etc, and how each of these performs on a wide variety of skin types and environments.
These specialised models and data can
be used to offer highly personalised skin care recommendations which consider the confluence of skin tone, dryness, age, diet, local air conditions, time of year, and so on. The user could upload a photo (or take other measurements using increasingly sophisticated sensors and wearables) and the app could work out what combination of products is best for that skin, at that time. To do this right, they need sophisticated models based on the underlying science of how different skin types respond to different products in different environments. This is not measuring clicks and spotting correlations to get ‘this-is-what-people-like-you-buy’ recommendations. It is modelling fundamental chemistry and biology, using complex R&D data combined with real world environmental data. With scientific data we can model reality
itself and use this as a foundation to build digital services that deliver much deeper insight. But it does not stop there. The daily photos/
measurements of user skin care regimes uploaded via the app are also hugely valuable for the R&D team. This data helps the R&D team
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understand how their products are being used, how they perform on different skin types and in different environments – much richer data than they can get in the lab. This helps better understand existing products and provides data to model new ones.
The companies already building digital services on R&D data These digital services based on scientific models are still very new. For those prepared to take a leap, the field is wide open for product companies to get ahead of their competitors. The flip side of that is that there is little industry experience to learn from. But we can draw on a few examples from the broader ‘consumer goods’ industry to illustrate the possibilities. Mars’s Pet Care division developed DNA
profiling for pets, built around models of genetics, bioinformatics of gut biome, and food chemistry. This allows them to make personalised recommendations of diets aligned to optimal pet health, and so sell more pet food. But more significantly, it allows them to move from selling tins of food, to selling pet health plans that include a custom diet. AkzoNobel (which makes paints and
coatings) has an app that allows customers to visualise colour in a highly accurate way, allowing them to make decisions without the
need for product samples. Underpinning this are models (which Tessella helped build), around the science of colour and light, allowing the app to visualise exactly the right tones, taking into account the lighting conditions and the screen of their phone, to show them what colour will really look like. A new entrant to the field is Lumen, a
breathalyser which measures biomarkers in breath and uses models to provide personalised weight loss recommendations based on the user’s individual metabolism at that moment. Lumen is a startup which did two years of R&D to gather the right data. It shows startups remain a threat to established businesses, but established businesses with decades of R&D have a headstart if they are prepared to use it.
How to approach using R&D data to build digital services: Think like a startup Unlike new products, which require lab research, mass manufacturing and stock management, digital services can be brought to market very quickly and in an iterative way. This may mean embracing new way of working for product companies! Companies need to think like a lean start-
up. Keep laser focused on the value that they are delivering. Try (and fail) quickly by building
April 2021 PERSONAL CARE
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