Artificial intelligence and algorithmic optionality in pricing guidance play a key role in profitability, and understanding this gives your organization a competitive advantage. In this article, Aneesa Needel, Senior Product Marketing Manager at Vendavo, explains the difference between price elasticity and sensitivity in B2B and how to use them to optimize your pricing strategy.
What Is Price Guidance?
The ability to provide sales teams with the right price guidance for their deals at the right time is crucial to improved win rates, faster cycle times, better negotiations, and increased customer experience. Traditionally, pricing guidance uses historical trends and business guidelines so you can assign the right price for your products, segments, and deals at the right time, allowing your organization’s sales reps to review and use the target, stretch, and floor recommendations during negotiations.
Vendavo continues to be at the forefront of strategic price guidance that is strengthened by our combination of patented algorithms, artificial intelligence (AI) pricing software, and your business rules and methodologies. This article covers what you need to know about price sensitivity and price elasticity in B2B, pricing guidance, and how the right algorithms make a difference.
The Essence of Price Guidance and Negotiations
It is easy to fall into a “one-size-fits-all” pricing approach, or taking just a few attributes and variables to decide a target price. This is usually based on revenue targets, the costs of the product or services, or competition parity, to name a few, but companies are likely missing business this way.
While it is not wrong to provide pricing this way, you can do better for your organization and consider guided targets. Here are a few key thoughts on the process:
- Sales teams and reps often create pricing that is then approved or denied by the deal desk.
- Discounts or position on the price presented commonly feel arbitrary and not in the best interest of the company doing the selling.
- This may lead to more deals closed, but limits profitability.
Sales reps should have autonomy to discount and negotiate to do their jobs. Knowing the pricing guidance and approved targets to incorporate into their negotiations can further help them to be successful.
A supported negotiation is powerful, and the key is to capture customers’ willingness-to-pay. This can help you not only avoid missing opportunities you should win (and profitably), but also help you positively impact your profits, growth, and revenue.
Dell Technologies is a good example here. The company optimizes prices and ensures high quote velocities to improve margin. With Vendavo they’ve seen:
- 100+ increase in basis points to margin
- 90% of their quotes go out within four hours of a request
- 75% of quotes no longer require pricing approvals
They’ve transformed their organization by streamlining and optimizing their partnership between pricing and sales teams. To do this, they use a strategy that is driven by AI as well as their experience and expertise.
Humans at the Heart of Pricing Strategies
There are many simultaneous conversations happening around and about AI. AI and its components are important and have their place in pricing software solutions, depending on the needs and challenges that the software addresses.
As AI and its applications change, so do the people who both run them and work in roles that can be amplified – but not replaced – by AI. Human expertise, the experiences you have had with pricing and negotiations, will not be substituted at this time by the machine. If an algorithm kicks back that one of your segments would still buy at a 45% price increase, for example, that does not, in reality, mean you should immediately suggest the price at 45% higher, Instead, put in a business rule that aligns with company objectives and limit how quickly a price can increase. The goal should be to combine the strengths of both software solutions and humans.
Deal Price Optimizer has always been built with AI in mind, but we have a key differentiator: We believe strongly that pricing guidance is human-led and supported by technology to provide an optimal solution that exposes additional profitability and higher win rates.
The Role of Algorithms in Pricing
Algorithms are tools, not substitutes for strategic pricing decisions. Algorithms are the base of that AI, and they can often be overlooked. End users want to make sure the software is making their business decisions better and more profitable, and the algorithms that are being chosen matter. Choosing the wrong algorithm based on the data your company keeps means you could still miss out on profit opportunities with pricing.
For more than a decade, Vendavo has been recommending optimal pricing guidance that maximizes margin while minimizing the risk of losing customers during sales negotiations. This method of using our Power & Risk™ works well for most use cases. There are reasons that this should not be the only option available to those building pricing guidance into their strategy and environments, though. We also consider price sensitivity and price elasticity methods.
Keep this in mind, however: What matters more is that companies are sufficiently building their price guidance and negotiations.
Price Sensitivity vs. Elasticity: How These Concepts Affect Pricing Strategy
Two common questions arise when we start talking about the strategy involved in building pricing guidance:
- What is price sensitivity and price elasticity?
- Do these concepts affect my pricing strategy?
The fact is that they may not directly impact how your team and organization approach optimized pricing and negotiations in your business, but it is good to understand the options and how they impact your goals. We’ve introduced two algorithms to help our customers build on the options they have to make the best decisions for their companies.
- Price elasticity is a well-established economics principle created in 1890 by economist Alfred Marshall. As prices of products change, so does customers’ willingness to purchase them. Companies with a deeper understanding of their products’ price elasticity gain a competitive advantage as they can precisely predict how price changes impact sales and overall revenue.
Price elasticity has an extensive application in the B2C sector that is widely understood, and it is relevant in B2B, too. The difference is that B2B price elasticity requires good win/loss data that is unencumbered by multiple, intangible factors.
- Price sensitivity, meanwhile, signifies how sensitive a customer is to changes in price and proves valuable when comparing various segments to determine which, if any, is more price-sensitive. We cannot definitively determine how a price change will affect the likelihood of winning a deal when given just the invoiced transactions. Price sensitivity estimates can, for example, be leveraged to establish appropriate targets within a segment, allowing higher targets to be set in situations where price sensitivity is low, and vice versa.
As the landscape of AI and the market continues to expand and shift, Vendavo is continuing to stay ahead and innovate to ensure you can provide the right pricing guidance and recommendations to your sales organization in multiple channels. These are complex topics that need more than a short overview, so be sure to reach out to our experienced teams for answers to your questions and to discuss strategies and best practices.