AI has the potential to add value to marketing and sales operations. According to a McKinsey survey, 40% of marketing departments using AI achieve 6% or higher revenue growth on average. In sales, respondents most often report revenue increases from AI use in pricing, prediction of likelihood to buy, and customer-service analytics. But AI is also credited with improving the scale and speed of price optimization, or the use of analysis to determine how customers will respond to prices for products across different channels.
Against this backdrop, Pricefx today launched what it’s calling AI-powered market simulation. Market simulation, which enables price optimization in the context of a product portfolio, as well as the competition, uses algorithms to predict the impact of pricing on customer purchasing behavior.
According to chief product officer Toby Davidson, the goal is to help businesses make better business decisions informed by predicted impact. “Market simulation provides our customers with the ability to evaluate data driven market impact to pricing changes they have, or are looking to implement,” he told VentureBeat via email. “Whether you are looking to grab market share through price or make sure you do not create a price war with your competitors and resulting margin and profit leakage, market simulation lets you evaluate the impact your decisions have on your customer base and product portfolio, and the potential reaction from your competitors — before they go live in market.”
Market simulation employs “multiagent” AI modeling of price elasticity among a company’s products and projects the demand impacts of various price changes. Through “what if” scenarios, market simulation guesses at possible competitive counter-moves and reflects customer behavior, in addition to the market response to price adjustments.
AI is inevitably subjected to bias and unforeseen confounders, which is why AI-driven hedge funds, for example, don’t reliably outperform the market. Indeed, for enterprises using predictive models to forecast consumer behavior, data drift was a major challenge in 2020 due to never-before-seen circumstances related to the pandemic. Organizations were forced to constantly retrain and update their machine learning models, and 12 months later, many are still wrestling with the challenge.
But there’s precedent for economy-simulating AI that works at scale. In August, Salesforce open-sourced the AI Economist, a research environment for exploring global tax policies. During experiments, Salesforce says the AI Economist arrived at a more equitable tax policy than a free-market baseline, the U.S. federal single-filer 2018 tax schedule, and a prominent tax framework called the Saez tax formula.
McKinsey forecasts that AI-based price and promotion have the potential to deliver between $259.1 billion and $500 billion in market value. It’s estimated that 55% of marketing decision-makers plan to increase their spending on marketing technology, including AI and machine learning, with one-fifth of the respondents expecting to increase by 10% or more.
Pricefx’s newly redesigned Plan, Price, and Profit solution sets include market simulation for subscribers of its Price and Profit packages. The market simulation feature is available beginning this week.
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