Pricing optimisation using artificial intelligence and competitor data


Jason Tan

DDALabs.ai, Australia

: J Comput Eng Inf Technol

Abstract


Long gone are the days where comparing prices when making a purchase requires countless hours, travelling, and note-taking. Today, consumers can easily compare prices through online catalogs, search tools, collaborative platforms, apps, and more – all within a few minutes. That means, if your price isn’t right, you’ll lose out to the competition in a heartbeat. But just the same as consumers obtaining new tech to compare prices, companies are obtaining new tech to do the same and optimize their pricing strategy – all through data. Some of the biggest and most successful companies in the world are already doing this. Walmart and Amazon are two prime examples of companies that have mastered data-driven pricing. Through sophisticated algorithms that analyse data on competitor prices, demand, inventory, and other factors, they are able to adjust their prices minute-by-minute to make sure they are always offering the best price for both themselves and for their consumers. Do you compare? Do you embed analytics and pricing intelligence into daily operations like Big Tech? In this paper, Jason Tan shares his expertise and knowledge of embedding and automating data and analytics so organisations can dynamically optimise their revenue by going beyond dashboards. Jason will be sharing: • What a data-driven pricing strategy looks like • How to embed analytics directly into your business frontline • Verified use cases from the insurance and e-commerce fields • The world-class revenue optimisation engine used by insurers and leading retailers • A 5 modules implementation process and every single step in creating an end-to-end solution that you can take back and start implementing at your organisation • Why this will boost your revenue without significant sums of investment necessary

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