How AI will transform Strategic Selling

Strategic Selling is typically characterized by long sales cycles, multiple stakeholders and complex decision dynamics. With AI getting more and more into the spotlights of business transformation, we may ask ourselves how AI will transform the practice of Strategic Selling. Will AI be just another tool for the sales professional or will it fundamentally change their way of working?

Large and complex deals are about gathering insights, building sales strategies and interacting with stakeholders. Upcoming AI technologies, such as machine learning, natural language processing and predictive analytics may very well transform the Strategic Selling profession.

Starting with the time-consuming task of gathering insights, AI has a lot to offer. There’s usually a large volume of information that sales professionals need to gather and process. Think of relevant customer market trends, industry reports, customer financials and business strategy, competitor information and previous customer interactions.

By gathering large quantities of structured and unstructured data, AI can replace a lot of the work that was recently done manually. Moreover, AI can reveal patterns that used to escape the human eye. Use case are:

• Opportunity Qualification: predictive models can evaluate opportunities based on closing chance, estimated deal size, strategic fit, contracting procedure or any other characteristic important to the seller.
• Competitive intelligence: AI can reveal competitor pricing information, their recent sales strategies or competitor weak spots, that can be funneled into the deal team’s own sales strategy.
• Stakeholder Analysis: natural language tools can analyze communications, social media or customer organization data to identify decision-makers or influencers. This will most likely also shed a light on their own personal wins.

As a result, sales professionals can obtain actionable insights that enable them to develop an effective sales strategy more quickly and with significantly less effort.

Trust and credibility with diverse customer stakeholders are a prerequisite for any large and complex deal. Until recently, this required many hours of research and manual tailoring of proposals, customer presentations and other interactions. Today AI provides assistance:

• Generative AI can write emails, compose draft proposals or presentations that are tuned to the customer’s business language, addresses all requirements and checks whether all customer criteria have been met. It can flag critical requirements.
• Recommendation models can suggest which case studies, white papers, or customer stories are most likely to resonate with specific stakeholders. This will guide the sales professional to include them in the proposal.
• Conversational AI can provide support during live calls or demonstrations by offering real-time prompts in response to customer inquiries, previous interactions with the client, or references to competitors.

Such a level of responsiveness is certainly more attainable when sales professionals are well-trained in utilizing AI effectively.

The finalization of intricate deals frequently experiences delays, or in some cases, the sales process may be completely abandoned by the customer. This can occur when sales professionals underestimate the processing time on the customer’s end, overlook important decision criteria or stakeholders, or fail to align with the necessary procurement procedures. Predictive AI can play a crucial role in significantly mitigating this risk.

By analyzing historical deal data and live pipeline activity, AI systems can:

• Alert when opportunities run a risk of getting delayed.
• Suggest best timing for interventions, based on customer engagement signals.
• Identify shortcomings in stakeholder management before these individuals hinder or complicate the sales process.

With proper use of AI tooling, deal teams are guided to intervene proactively, thereby reducing delays and improving win rates.

As demonstrated earlier, AI is capable of managing the repetitive, data-intensive, and administrative tasks associated with selling. This enables deal teams to dedicate more time to areas where AI still falls short:

• Building authentic human relationships.
• Interpreting subtle personal dynamics from customer stakeholders.
• Finding best solutions for ambiguous or political situations.
• Taking the customer on a joint journey.

Strategic sellers who leverage the advantages of AI are likely to achieve greater success than dealmakers who primarily rely on traditional manual methods.

However, the implementation of AI in sales processes comes with its own challenges. Sales professionals must navigate issues such as:

• Privacy concerns: Analyzing customer communications or social profiles may raise concerns about their privacy. It may also lead to reduced customer trust.
• Bias: AI models built on historical data can perpetuate existing shortcomings and may fail to recognize new best practices that are emerging.
• Lack of transparency: Buyers might become wary of the selling organization’s true abilities if they feel that interactions are excessively automated or deceptive.

As a result, sales organizations must integrate new metrics into their governance frameworks. These should tackle privacy issues and guarantee transparency along with responsible usage. Additionally, bid teams will require training to utilize these new governance frameworks effectively.

As AI becomes integrated into the sales process, the capabilities of bid teams will develop. Contemporary sales professionals will have to:

• Assess AI insights: they must learn to question AI outputs and apply their own professional judgment.
• Incorporate AI tools: sales teams will need to be proficient in utilizing AI tools while ensuring effective collaboration with key organizational departments such as Marketing, Finance, Legal, and Operations.
• Monitor market trends: Sales professionals must not only incorporate AI-generated insights into their existing deal strategies, but they also need to identify new AI-driven practices and advocate for their integration into the organization’s sales processes.

Undoubtedly, training programs will have to focus not just on conventional sales skills but also incorporate AI literacy. One of our upcoming Insight articles scheduled for later this year will provide further details on how AI can support the training of sales professionals.

Consequently, AI is expected to significantly transform the landscape of Strategic Selling. Visionary sales professionals will utilize more data, uncover deeper insights, and free up time for tasks that only humans can accomplish. They will increasingly concentrate on cultivating enduring partnerships that provide value to both their clients and their own organizations.