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Artificial Intelligence (AI)-Powered Analytics Drive Real-World Pricing Advantage

by: Matthew Hays | October 15, 2020
“We’re looking at a new AI-powered analytics solution.” That’s what manufacturers are telling us when we ask about their pricing strategy.

Though it’s still the early days of the fourth industrial revolution, implementation of AI is ready for takeoff. Market intelligence firm IDC forecasts that global spending on AI will more than double over the next four years, growing from $50.1 billion in 2020 to more than $110 billion in 2024.

“Companies will adopt AI—not just because they can—but because they must,” said Ritu Jyoti, program vice president, Artificial Intelligence at IDC. “AI is the technology that will help businesses to be agile, innovate, and scale…have the ability to synthesize information (using AI to convert data into information and then into knowledge), the capacity to learn (using AI to understand relationships between knowledge and apply the learning to business problems), and the capability to deliver insights at scale (using AI to support decisions and automation),” Jyoti added.

AI is proving to be the solution to a multitude of business problems. But a universal need that AI can fulfill across all industries is setting the right price.

Getting from Point A to Point AI

It all starts with your data. That’s the input for your AI machinery, so make sure it’s clean. Data mining tools can adapt to small gaps and smooth out irregularities, but large blind spots in data—or conflicting data—will generate misleading results.

And how can you get more data to feed the hungry AI machine? Enlist your distributors. Use your rebate program to incentivize them to share information with you. Here’s what you can learn from this approach:

  • Distributor inventory (inventory sales to distributor, minus rebate units claimed)
  • Customer geo-information (at minimum, ZIP codes should be reported)
  • Distributor selling price (sensing local market demand)
  • Product mixes (upsell, cross-sell or bundled promotion opportunities)

A smart manufacturer should be able to derive greater value from this data than the cost paid to obtain it, and you can exploit the data to identify trends, such as where you need to focus your advertising efforts, how best to motivate your distributors, and evaluate your pricing.

The Price is Right

AI applies machine learning (ML) to crawl through your growing (clean!) data set to find new trends and demands to fold into predictive calculations.

Manufacturers can also rely on ML to help them understand how their customers will react to varied pricing strategies and then identify the best price based on their goals. Knowing the potential impact of sales promotions or rebates, competitors, weather conditions, seasonal sales forecasts, economic conditions, operating costs, and regional demand all play into formulating pricing guidance.

ML is a powerful tool that can handle millions of SKUs and sales transactions to optimize prices regionally and dynamically, based on the manufacturer’s pre-defined rules. ML continually absorbs information, building its own pricing automation by using its algorithms to identify and learn from the data’s patterns.

One manufacturer using ML to optimize pricing and provide real-time price intelligence to its sales reps reported 35% of the ML-recommended prices were adopted. This manufacturer realized a $1.3 million revenue increase and a 10% increase in win rate.

Adding it all up

Growing a manufacturing business requires informed decision-making. Artificial intelligence can quickly provide key insights that identify business risks and opportunities with greater ease and efficiency. Manufacturers who use software that manages the full lifecycle of their pricing optimization programs will have a strategic advantage in the marketplace. In the end, better data leads to better insights and better insights lead to more profit. Vistex can help you make sure it all adds up.

To learn more, download the eBook, The Price is Right: Going from Reactionary to Strategic Pricing.