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SALES-1 — eCommerce acceleration & predictive CRM.

Nestlé Vietnam · Posted 1 hour ago

Consumer goodsGenerative AIPredictive Analytics / ForecastingSearch & Knowledge Retrieval
Budget
To be determined
Timeline
Based on solution provider proposal
Apply by
22 Nov 2026, 23:59 ICT

Problem statement

Compare livestream, short-video and affiliate ROI; predict who will engage or buy and suggest the next best action. Today: • Livestream, short video and affiliate are managed as separate activities: livestream is constrained by host/studio capacity, short-video output needs to keep pace with algorithm demand, and affiliate investment wants a clearer view of creator ROI. Performance sits across platform portals, agencies and internal files, using different definitions. Category and competitor benchmarks are not connected to investment decisions. A connected view is needed to guide where the next investment goes across levers, platforms, categories and creators. • Current consumer models are mainly historical or based on static segmentation. They explain what consumers have done but have limited ability to predict who is likely to engage, churn, convert, or create future value. Without timely signals, teams often apply the same action to broad groups, miss the right moment to engage, and need to balance short-term growth with long-term relationship value.

Expected outcomes and success metrics

• eCommerce growth is increasingly driven by content-to-commerce. Winning requires faster learning and disciplined allocation across livestream, short video and affiliate - not simply producing more content. • One growth view compares GMV, contribution and ROI across livestream, short video and affiliate by platform, category, brand and creator. It recommends where to invest next versus category and competitor benchmarks; investment is tracked to contribution, creator portfolios are rebalanced regularly, and live/short-video output scales without the same increase in headcount. • Personalize by need and likelihood to act, not only by static segment. Focus investment on higher-value consumers and moments. Detect churn or declining engagement risk earlier. Reduce irrelevant contacts and communication fatigue. Measure incremental uplift more clearly through test-and-control design. Improve conversion, retention, and lifetime value while maintaining a relevant experience. • Priority journeys use verifiable predictions and next-best actions, with consent and privacy embedded by design. Success is measured through incremental conversion or engagement, churn reduction, customer lifetime value, opt-out and fatigue rates, coverage of permissioned data, and fairness across groups.

Target users and impacted teams

• eCommerce, CDT, BU (Business Unit), CMI and Finance • CRM (Customer Relationship Management) and consumer engagement teams • Business owners; privacy, legal and data governance teams

Data availability and readiness

• Permissioned first-party data (Nestlé: used for the Predictive Engagement Engine) • Platform, category, brand and creator performance data for livestream, short video and affiliate (as required for the Nestlé growth view) Note: Synthetic data could be potentially provided during the process, upon approval of the Nestlé team and in compliance with data law.

Integration, deployment and infrastructure

• To be determined Note: Nestlé's current environment includes Microsoft Azure and Microsoft Copilot. Solutions that can work with this environment are welcome, and final integration and deployment requirements will be confirmed with the Nestlé team.

Relevant AI technologies

Generative AIPredictive Analytics / ForecastingSearch & Knowledge Retrieval

Based on Nestlé objectives for comparing livestream, short-video and affiliate ROI and for propensity, churn and next-best-action CRM (Customer Relationship Management) engagement.