In my experience as a business transformation solutions expert, I know that deals are only closed when both buyer and seller see the value. For the seller, this means optimizing revenues and margins. To do this consistently, enterprises must not only know what solutions to offer their customers but also be able to gauge their customers’ willingness to pay. In a competitive environment where many players offer similar services and solutions, the ability to consistently offer a price that is well within the customer’s zone of price comfort is vital to success.
Enterprises in the business to business (B2B) space generally have well-defined policies that govern not only pricing and margin requirements but also discounts, preferential payment terms, and so on. These policies are linked to criteria such as the existing size of the business relationship, value and profitability of the current deal, customer loyalty and prospects of growth. Pricing is guided by the need to achieve strategic objectives such as capturing market share, launching a new product or entering a new market. It is also impacted by tactical priorities such as acquiring a “must-have” customer or gaining a toehold in a new market segment. Also, pricing decisions need to reflect market dynamics such as competitor actions or changing customer expectations.
Informed but speedy decision-making on pricing is key.
B2B organizations depend on large and complex ecosystems for their success. These ecosystems could, for instance, include alliance partners, hardware suppliers, software service providers, distributors, implementation partners, etc. Then there is the complexity imposed by customers. Members of the ecosystem have their own priorities, preferences and processes and unless everyone operates in cadence at all times, chaos is bound to result.
In the business to consumer (B2C) e-commerce world, the speed of pricing adjustments is easily visible when we buy groceries, book cabs, make hotel reservations or buy flight tickets. I believe the agility associated with “dynamic pricing” will now be needed in the B2B space as well; as more and more B2B purchases go online, decisions around pricing will need to be made promptly. This poses a challenge for businesses because pricing is no longer a formulaic exercise based mainly on input costs. Decision makers responsible for pricing must analyze multiple data points and make judgment calls.
AI can help, provided it has the support it needs.
Artificial intelligence (AI) can give enterprises an edge in terms of making better-informed pricing decisions by sifting through the haystacks of data available to identify important factors at a given point of time. In turn, this helps make the process of analysis and decision-making faster, and even the ability to tweak prices as often as leaders deem necessary.
But just adopting AI tools or focusing on the algorithms will not help; it is important that processes and people in the enterprise are aligned for this solution to be successful. Here are some tips for enterprises to ensure their adoption of AI in pricing delivers.
• Ensure that your business model and pricing strategy are aligned with your growth plans. This may mean realigning how you sell your products and services to include bundling services with other elements, offering customers subscription-based models, software as a service (SaaS), more flexible bundling and more. This is important because each model will need different kinds of information and data to tweak pricing.
• Train sales teams to understand nuances of the new business and pricing models so that what they promise customers is in sync with the company’s new policies, procedures and offerings.
• Shift the conversation with prospects and clients away from discounts. Conversations between sales teams and clients are often focused on discounts. This is detrimental to revenue and margins because there is a tendency for sales teams to get into the mindset that discounts are essential for sales. Sales teams armed with new insights can guide the conversation to other elements of value in the deal.
• Enable the right data to be captured, giving your AI engine the latest information. Some of the data may be quantitative, while some may be more qualitative. Some data may need to be sourced from other systems such as the ERP (e.g., impact on revenue and margins, accounts receivable or bad debts) while other data may need to come from the CRM system (customer profile and history, competitor presence and actions, track record of customer wins and losses, categorization of customer or prospect, etc.). Unstructured data from social media feeds may also need to be factored into the decision making. The frequency of gathering such data is also an important aspect to ensure speedy and accurate pricing.
• Do not blindly follow what AI tools recommend. Human experience and judgment are still invaluable in making sense of what systems recommend. It is essential that your process includes some old-fashioned brainstorming around what might seem off or counterintuitive. AI is still not evolved enough to mimic human intelligence and experience.
• Periodically review the algorithms and rules used by your AI tools. Although AI systems are self-learning in nature, it may make changes more slowly than is optimal for your business. Worse, the market environment may change due to disruptive innovations, regulatory changes or competitor intent or actions that go beyond what your data reveals. Such “human intelligence” needs to be periodically incorporated into the rules that your AI tool uses.
Embrace AI for an edge in pricing decisions that will make your competitors look up to you. Work with all stakeholders to develop a compelling vision for pricing and identify what optimal pricing means for your organization. Assess your existing pricing structures, rules and sales processes that will be affected. Design a phased approach for transformation comprising of pilots and parallel sprints. Execute with precision and spend adequate time on testing and review post completion of each sprint. Devise end-user training initiatives to drive adoption of a new pricing solution and realize the outcomes envisioned. The AI revolution is here and it’s imperative for pricing to be part of it.
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