Nestle Plans To Double Consumer Data Records & Sales From E-com By 2025
Nestle unpacked its digital transformation strategy at an investors conference this week, identifying three priorities to increase e-commerce to a quarter of its total sales and doubling its consumer data records.
Having quick access to actionable data insights is key to understanding today’s shifting consumer behavior, noted Bernard Meunier, Nestle head of strategic business units and marketing and sales, while optimizing demand-gen activities and leveraging the influence of brand advocates within the rise of digital communities are likewise required to design both optimum product concepts and experiences and stay relevant today.
“Direct access to consumer data is not just a plus — it's a pre-requisite to be the leading data-powered experience brands company,” said Meunier.
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As a result, in addition to enhancing its e-commerce offerings and increasing digital marketing spend, Nestle will focus on capturing more valuable consumer data points to deliver more impactful and personalized experiences.
In doing so, the company intends to increase online sales from around 13% at the end of 2020 to 25% by 2025 — double the average of its total consumer goods. Online marketing investment spend will increase to 70% by 2025, up from around 47% today, and consumer data records will double over the next four years.
Meunier and Aude Gandon, global chief marketing officer, Nestlé SA, subsequently walked through Nestle’s three strategic priority growth areas: Direct Access to Consumers at Scale, Channel-less Commerce, and Always-On Analytics.
Direct Access to Consumers at Scale
Nestle will collect more first-party data across its category ecosystems through key digital properties with traffic-driving search authority. Gandon cited an example within the culinary category in which select recipe websites record more than 200 million visitors per month, enabling Nestle to drive more culinary brand sales or connect them within its DTC business.
The No. 1 consumer goods company will in turn ground use of consumer data within four personalization principles:
- Precision marketing to identify more precise and effective audience in its brand campaigns
- Direct engagement to increase lifetime value
- Content personalization to activate with more effective content, including integrating more artificial intelligence to dynamically associate content with audience
- Product personalization to grow beyond core categories
“We are looking at scaling and monetizing these data ecosystems over the next few years by moving from simply ‘reaching’ consumers to really engaging and serving them,” said Gandon.
Channel-less Commerce
Evolving beyond the traditional omnichannel mindset, Nestle is deliberately using the term “channel-less” as a rethinking of how it provides experiences across the full customer journey, whether in-home or out-of-home. As part of this, it’s investing in new e-commerce packaging solutions and supply chain agility.
Currently, more than 40% of Nestle e-commerce sales are in fit-for-purpose packaging formats, and Meunier said the Nestle supply chain has been strengthened to manage the increased demand, particular in pet care and coffee.
Meanwhile, Nestle’s e-retail media investments made directly with e-commerce platforms have more than doubled since 2019.
[See also: As Freshly Scales Under Nestle’s Wing, Personalization Becomes Paramount]
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.
Always-On Analytics
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.
