B2B Price Optimization Best Practices

Highlights

  • Pricing optimization finds the highest sale amount a customer segment will pay for a product or service. It models the price factors that impact quantity sold, statistically measures how customers respond to sale amount changes and compares alternative pricing scenarios to achieve financial goals. It identifies the optimal sale amount and forecasts how price changes impact revenue and profits.
  • B2B price optimization is characterized by B2B selling of low volume, high margin deals managed by salespeople. Many times, B2B sales are for unique, highly configured or custom solutions.
  • Systemic and continuous revenue growth can be achieved with a combination of pricing strategy and optimization. Research shows this two step combination increases annual revenues by 2 to 8 percent and nearly all the increase falls straight to the bottom line.
Johnny Grow Revenue Growth Consulting

B2B price optimization is a powerful but underutilized revenue growth lever for most companies.

Research shows that those companies that implement active pricing programs achieve greater agility, extract more value from their goods and services, and drive more top line revenues and bottom line profits than those who do not.

It's simple math really. A 1 percent increase in price will generate a 20 percent increase in profit for a company with 20 percent profit margin.

But while the financial upside is significant, a thoughtful approach is needed to succeed. That starts with a price strategy and strategy starts by recognizing B2B optimization is very different than B2C price optimization.

Pricing Strategy

Why B2B Price Optimization is Different than B2C

Here's how B2B selling and optimization are different than consumer-based models.

  • B2B companies calculate sale amounts for products or services that are mostly sold by salespeople.
  • For buyers, B2B sales are considered purchases that incur more risk, consume more evaluation time and are often made by groups of people.
  • For sellers, sales transactions are often unique with custom pricing, negotiated terms and individual discounts.
  • Sellers have pricing discretion that may be different for each buyer. They also have some degree of flexibility to shift pricing or margins from one part of the sale to another. For example, they may discount shipping costs or throw in future maintenance services but hold tight on the product purchase amount.
  • B2B salespeople sell smaller volumes of higher margin solutions compared to B2C.
  • And those solutions may have options, be customizable or highly configured, and are therefore more sophisticated, or even complex. Sales transactions may include delivery, installation support or other ancillary charges or aftermarket fees.
  • Sales are measured as won or lost.
B2B versus B2C Price Optimization

It's all about the payback

Companies that attain intelligent, dynamic and optimal pricing realize a sustained and magnified impact on revenues and profits. However, adoption by Business to Business (B2B) and Business to Consumer (B2C) companies varies significantly.

There is a wide body of knowledge showing pricing optimization payback and ROI for B2C companies, and that probably explains why adoption is much higher. But recognize that price strategy and optimization are no less powerful for B2B companies. Consider the following research findings.

  • Analyst firm IDC reports that "most B2B-focused pricing optimization applications had a payback of less than 12 months, with some having paybacks of less than 3 months due to the product uncovering large opportunities from underpricing."
  • Gartner’s MarketScope report titled, Pricing Optimization and Management Software for B2B, found calculating optimal sale amounts "offers a compelling value proposition in terms of the ability to provide a significant and measurable positive impact on margin, revenue and profitability: A successful price operations and management implementation can increase margins by 50 basis points or more, and increase revenue by 2% to 4%."
  • In their published study titled, Profiting When Customers Choose Value Over Price, Business Strategy Review 22, no. 1, MIT researchers A. Hinterhuber and M. Bertini, found that "pricing has a substantial and immediate effect on company profitability … and that small variations in price can raise or lower profitability by as much as 20% or 50%."
  • In the book titled Revenue Management, author and researcher Jon Higbie, found that "companies implementing B2B pricing analytics achieve a 2 to 5 percent increase in contribution."
  • Our own experience is that when helping midsize B2B companies, a price strategy and optimization program can deliver a 90 day payback and immediate 2 percent or more recurring revenue increase that falls straight to the bottom line. We've also found that quantifiable pricing intelligence improves sales win rates by providing an unbiased estimate of the customers willingness to pay and further accelerates sales cycles by shortening the negotiation period.

See the research findings from Gartner and others that show B2B price optimization can increase margins by 50 basis points or more and increase revenue by 2% to 4%.

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B2B Price Optimization Calculations

Calculating the optimal sale amounts is done with price elasticity models that show how changes in sale amount impact the quantity sold. When built on customer segments and item clusters they forecast how different customers will respond to price changes for different items. They can also identify revenue uplift opportunities for each customer segment.

Pricing data models are needed to identify and weight the variables that most influence elasticity and customer purchase response. Those variables include, but are not limited to, the following:

  • Customer data, such as firmographics, demographics, behaviors, loyalty, customer relationship and customer value (i.e., customer lifetime value)
  • Customer segments, because building your customer price response model on customer segments will increase accuracy by focusing on the highest fit customers for any particular item, and deemphasizing customers who make one-time or infrequent purchases
  • Market data, such as market growth and potential for disruption
  • Brand value, as the value of your brand increases price elasticity, and makes your products or services more inelastic
  • Competitor data, such as competitor market share, brand, growth, location and item pricing
  • Transactions, such as opportunities, quotes, sale orders, Revenue per Capacity Unit (RPU) and repeat purchases
  • Inventory items, such as uniqueness, cost and availability of substitutes or alternatives
  • Inventory supply, such as capacity, stock levels, utilization (i.e., turns), seasonality, demand forecasts and future cost projections

When the above factors are assembled in a dynamic data model, price-level improvements can be calculated by customer segment, product, geography or any other factor included in the model.

Sometimes companies with high volumes of SKUs calculate price elasticity for their big ticket and high margin items and use an alternative approach for everything else.

For example, they may use quick to assemble item value calculations based on lead and opportunity scores, current demand, brand value, customer affinity score, unique value proposition and historical win rates. The resulting calculation is short of a price elasticity value but can be helpful to sales managers or salespeople when considering item and customer discounting.

Pricing Software

B2B Price Optimization Best Practices

I've been implementing pricing optimization models with clients for about two decades. Below are a few of the best practices I've learned.

  • Because salespeople have discretion for discounts, tradeoffs and terms, calculated optimal sale amounts are often a starting point and more suggestive than final. Price optimization software may also integrate with or be a part of CRM or CPQ applications to guide sales reps and compare different scenarios to achieve the best price. In fact, for highly configured items, using CPQ technology to assemble both components and pricing is another form of optimization.
  • While B2C pricing models often shield much of the Artificial Intelligence (AI) or machine learning logic that calculates sale amounts, black box deterministic pricing should not be used with B2B pricing. Sales managers and salespeople need to understand the factors behind the results so they can improve the calculations based on their firsthand knowledge and experience.
  • Because B2B companies incur far fewer sales transactions than B2C, there is less data to harvest and price predications will therefore have lower confidence levels. This is another reason to avoid black box price results and recognize that B2B pricing algorithms supplement rather than replace seasoned sales executives.
  • Sales deal desks improve B2B sales efficiency and effectiveness by bringing structure, collaboration and speed to complex and high value deals. They review and manage item price changes, discounts, terms and contracts. Their jobs are made easier when they have firsthand knowledge of price elasticity and customer response measures.
  • While not unique to B2B selling, pricing optimization must also consider human behaviors. For example, buyers are much more cost sensitive for goods or services they routinely or frequently purchase.

The Point is This

Starting with price strategies and optimization techniques designed for your industry is an essential prerequisite to aligning pricing with customer willingness to pay, calculating optimal prices for customer segments or target markets, and maximizing market share, revenue and profit.