How To: Use AI price optimization for an engaging customer experience

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Customer preferences alter by the second. Getting in the buyer's good graces once does not guarantee lifelong loyalty. That's why retailers would do anything to lure shoppers. Even something as self-destructive as setting the lowest prices which they can't afford to maintain. Such tools as AI-backed pricing analytics software help businesses create pricing strategies which allow retaining customers and keeping margins at the same time.


How Machine Learning is reshaping Price Optimization Tryolabs Blog

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Setting the right price for a good or service is an old problem in economic theory. There are a vast amount of pricing strategies that depend on the objective sought. One company may seek to maximize profitability on each unit sold or on the overall market share, while another company needs to access a new market or to protect an existing one. In this blog post, we'll present the problem of price optimization for retail – which has its own particularities – and how retailers can take advantage of the tremendous power of Machine Learning (ML) technology to build effective solutions. Given that in these days it is very easy for a customer to compare prices thanks to online catalogs, specialized search tools or collaborative platforms, retailers must pay close attention to several parameters when setting prices.


Powerful pricing: The next frontier in apparel and fashion advanced analytics

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Leading apparel retailers are embracing advanced analytics and blending intuition with science to price smarter. The competitive landscape in apparel is shifting rapidly as new price leaders capture market share. The battle for value has never been harder fought. The very definition of value is evolving quickly, pressured by Amazon's entry into apparel, fast-fashion retailers, flash sales, and the arrival of ultravalue players. Between 2012 and 2017, only the value sector of apparel retail, including off-price players, showed any growth as both the middle and premium tiers shrank.


How retail uses machine learning to increase revenue - Elite Business Magazine

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The retail market is becoming increasingly competitive. Customers are expecting more personalised offers and are also more aware of their choices. Operational costs are rising and the amounts of data retailers need to factor in when setting prices are accumulating nonstop. As a result, businesses are hunting for new strategies to increase revenue. Currently, the pricing process is in chaos.


4 Best Practices For designing a winning CPG pricing strategy - Acuvate

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With so many variables it is extremely complex and time-consuming to determine competitive prices that add to the bottom line and also benefit the final consumer. With low-profit margins per unit, assigning the optimal price to a CPG is a matter of competitive advantage. A combined research by Nielsen, McKinsey, and GBA has revealed that'Pricing winners who adopted best practices in devising a pricing strategy were able to increase unit prices by 1.2 percentage points more than the category average. At the same time, they gained share by growing sales by almost a full percentage point ahead of their peers.' While some best practices are technology interventions, others are about partnerships.