Hivery Отзыв

HIVERY is a multi-award winner pioneer of hyper-local retailing, combining artificial intelligence (AI), operations research, and human-centred design to help consumer packaged goods (CPG) manufacturers and retailers generate a return on physical space investments. HIVERY is transforming category management and retail trade promotion with innovative algorithms sourced from Australia's national science agency - CSIRO's Data61. HIVERY is venture-backed and headquartered in Sydney, Australia, with offices in the USA and Japan. HIVERY was founded on the vision that Data Has A Better IdeaTM - and we’re working together with our clients to uncover its full potential. We have 3 SaaS-based solutions 1) AI in category management HIVERY Curate is world’s first AI category management tool in development which helps optimise space and assortment for CPG companies and retailers. HIVERY Curate is the only category management solution generated that can: 1.1. Preform rapid category scenario Simulate multiple strategic scenarios and run playbacks to evaluate business impact and assortment decisions. It will transform your Joint Business Planning (JBP) sessions (in minutes, not months) 1.2. Generate space assortment aware PSA ready planograms in minutes. Generate fully store-level executable planograms that simultaneously understand space and assortment for each store quickly 1.3. Smart store-level planograms Factor your own custom merchandising constraints, goals and brand flow rules as into HIVERY Curate’s model while seeing the impact of transferable and incremental demand when adding or removing any SKUs AI in Vending Machines HIVERY Enhance uses your existing vending management system data and our powerful AI-driven engine to enhance and optimise the mix of product, space and price for each machine in your fleet. It factors only a few data variables to make recommendations that maximise profit. AI in trade promotional optimization HIVERY Promote solution assists CPG companies in predicting the demand impact of their promotional calendar. It models several demand signals, including product catalogue, store placement, seasonality, own and cross-retailer competitor price elasticities, and generates accurate demand predictions along with a range of KPIs. Ultimately, PE will incorporate its optimisation capability to deliver implementable promotional calendar corresponding to required business KPIs.