Meanwhile, Nestle’s e-retail media investments made directly with e-commerce platforms have more than doubled since 2019.
The company is tracking all key online stores carrying its brands in more than 60 markets on a daily basis to ensure content accuracy and product availability, as well as reviewing consumer feedback — all expected to increase products add-to-cart rate by up to 30%.
“This is the new reality of our markets to support the e-commerce acceleration,” said Meunier, likening the strategy to those of digitally native brands.
While not a true digital native, Nestle’s scale does afford it access to a wealth of data — Gandon said they speak with more than 200,000 consumers weekly and monitor 500,000 product reviews monthly —and it’s building out its data science capabilities to leverage these sources more strategically. This includes building predictive analytical models to improve sales outcomes and consumer lifetime value, and surfacing them in real time to identify early trends and innovation opportunities.
Examples include using predictive capability to identify potential opportunities for new items in the United States, as well detecting possible out-of-stocks and providing personalized pricing, promotion, and assortment optimization recommendations to retail partners.
In the more fragmented retail landscape in India, Nestle consolidated all store data to capture the effect of media, trade investment, and promotions in order to identify optimal resource allocation based on geography and channel.
[See also: Inside Nestlé’s Largest R&D Accelerator]
The company is also using data solutions to better segment retail outlets, including suggesting "must sell SKUs" per store and mapping more strategical areas to focus sales force efforts. These moves are in turn improving distribution, availability and visibility.
Predictive models, meanwhile, are improving sales demand accuracy and the ability to anticipate out-of-stocks. Both have combined to drive incremental sales from 2% to 4%, and optimize 10% of its investment to be more productive, said Gandon.
In China, Nestle has digitized its innovation process, using big data technology to identify key trends and innovation opportunities within real-time social data. These insights are then used to develop innovation ideas and concepts that are fast-tracked through Nestle’s local Product Innovation Centers and manufacturing capabilities, with quick concept testing.
As a result, Nestlé China multiplied its innovation intensity by three, in three years, said Rashid Qureshi, chairman and CEO of Nestlé Greater China region.