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Market trends and business perspectives

AI driving actionable sales intelligence in manufacturing

By Barrett Thompson, Zilliant Business Solutions

The manufacturing plant floor has been automated and optimized for years; yet revenue and profit growth remain stagnant.

Seemingly everything has been process-improved with lean manufacturing principles; however, the cost of doing business remains high and the C-Suite continues its demands for an increase in revenue per transaction and gross margins.

Two functions at manufacturing organizations are prime for process improvement:

  • selling; and
  • pricing.

A closer look at the selling function reveals that despite reducing labor costs via transformational automation solutions, sales teams still manage large, antiquated portfolios. They are expected to increase their book of business while retaining current customers.

Measuring sales reps, the way plant floor machinery is measured, with an overall equipment effectiveness (OEE) score, organizations quickly discover they are doomed to inefficient output. Sales teams are simply asked to handle too many accounts while being overloaded with information that lacks actionable direction.

Manufacturers and distributors with growing catalogs find the salesforce often lacks an in-depth knowledge of new products. As a result, they keep selling what they know at the expense of selling new products that may carry a higher margin or help expand share-of-wallet.

A lack of automated, data-driven, artificial intelligence (AI) virtually guarantees excessive customer churn. Much of this customer dissatisfaction stems from sales reps not knowing what their customers need and lack the time and tools to gain that understanding.

Similarly, sales managers need reliable tools that help their reps prospect the right opportunities, prevent customer defection, gain higher margins, and work more efficiently through automated processes.

Since it is impossible for sales teams to know about every potential threat and growth opportunity within their accounts at all times, automatic identification of cross-sell opportunities and customers showing signs of defection is a great place to start.

Human analysis cannot sufficiently pinpoint which customers are at risk of switching to competitors, or prevent defection across a large set of accounts, identify the customers that should purchase a product and know which customers are most ready to purchase additional products. The right AI technology can dynamically surface hidden revenue opportunities at scale.

Pricing is another manufacturing function that can be vastly improved with AI tools. Whether a customer decides to purchase online or direct, too often a “win-the-deal at any cost” strategy from a busy industrial sales leader starts a chain of cumbersome manual steps.

Approaches such as data-driven calculation of the right price, or the use of streamlines automation tools for deal approval that do not rely on ad-hoc excel spreadsheets and email, are two proven areas where immediate benefits can be found.

Productive price management can be achieved with an application that enables price managers to establish, manage, and automate the pricing process quickly and easily. Best-practice solutions simplify the management of price lists, adjust and publish prices accurately, and roll them out efficiently throughout the organization.

In the same way that consultative selling reduces churn, when price managers spend more time on pricing strategy and less time on manual tasks, the results are significant for pricing teams, sales teams, and the business overall.

Measure the Impact of Price Changes on KPIs

Only when pricing managers build logic and calculations with spreadsheet-like formulas, can they also simulate a price change impact to KPIs (key performance indicators) such as revenue and profit margin with visual analytics before publishing prices. These features ensure accuracy and confidence in the prices delivered to the rest of the organization.

Automating the pricing management function allows teams to manage the entire lifecycle of creating, rolling out, and measuring a price change.

By setting up an automated intuitive management solution, pricing teams schedule and automate updates to agreement lines affected by price changes, at scale. Pricing teams collaborate with sales to roll out changes that require review or approval with transparency for audits.

Full Integration with Advanced AI-driven Price Optimization

Within a pricing application, pricing managers have a choice. They can bring in pricing guidance that is calculated using either artificial intelligence price optimization, or a rules-based approach. This permits an organization to set pricing and leverage advanced pricing strategies and customer/order attributes.

C-Suite executives appreciate this impact as sales focuses on more complex orders and larger, more strategic customers get the required attention. Selling of smaller accounts can be moved to a lower cost to serve channel, lowering the cost of doing business. Most importantly there is a quantifiable reduction in customer churn by giving high value customers a personalized and consultative experience.

AI-based price optimization and sales management solutions that maximize the lifetime value of B2B customer relationships are straightforward despite the underlying complexity. These solutions turn disparate data into seamless actionable intelligence.

The intelligence is then delivered within existing field sales and service rep workflows, CRM applications, quoting tools, eCommerce channels, and more. Actionable intelligence accelerates profitable growth.

Next step: The Pricing RoadMap tool is a two-minute assessment.

Author Profile: Barrett Thompson, GM of Commercial Excellence leading Zilliant’s Business Solutions Consultant team aligning Zilliant solutions to customer needs. Over the past three decades, he has built and delivered optimization and pricing solutions to Fortune 500 businesses in diverse B2B manufacturing sectors. Contact Barrett at or call 00 1 (512) 531-8500.