March 17, 2025
Managing Partner
B2B sales leaders can unlock significant growth by combining strategic fundamentals with AI-powered, technology-enabled sales approaches.
Evolving competition and rising customer expectations are reshaping the B2B sales landscape. To navigate these shifts and accelerate growth, many sales leaders are turning to various technology solutions, including artificial intelligence (AI).
B2B sales leaders today find themselves at a pivotal moment. In our backyard of Kansas City and worldwide, growth remains uneven, competition intensifies, and customers increasingly adopt consumer-style behaviors. They want richer buying experiences and are willing to switch vendors to achieve them. In this environment, how can B2B sales teams stand out and thrive? Sound commercial excellence remains essential. Organizations must still craft thoughtful strategies, develop compelling value propositions, align with diverse channels, and maintain growth momentum. Yet, to stay ahead, these same organizations can leverage technology to pinpoint the right markets, discover and retain the best-fit customers, and ensure satisfaction across every channel.
Leaders now recognize the crucial link between innovation and strategic execution. Santiago & Company's latest B2B Sales Survey reveals that many are ready to adopt digital tools to enhance their sales efforts. However, just 20 percent say they regularly and effectively deploy technologies that drive outsized growth. This gap presents a substantial opportunity for those seeking to outpace their competitors. The potential rewards are significant. Top-performing B2B leaders often shift from an essential growth mindset to one that translates bold ideas into concrete action, thereby unlocking sustainable success. A Santiago & Company study on growth found that businesses surpassing their peers in growth devote more resources to digital transformations and AI to enhance sales and marketing. Those who excel at innovation can capture an additional four-percentage-point increase in cumulative total shareholder returns (TSR) over time.
Our team interviewed nearly 100 commercial leaders worldwide to understand how high-performing B2B sales organizations utilize technology to enhance accuracy and speed. These trailblazers apply tech and data to sharpen their view of new opportunities, reduce wasted effort, arm sales teams with meaningful decision-making insights, and optimize resources, pitches, and pricing. This cohesive approach often enables them to identify trends, focus on high-growth markets, and capitalize on specific customer opportunities before their rivals catch on.
In our discussions, we identified five main technology-driven strategies that help B2B players rewire their growth engines and outpace their peers:
AI provides a sharper lens on the most promising opportunities, directing sales teams toward high-impact actions and away from wasted effort. We see five principal use cases: identifying business adjacencies, enhancing engagement with micro-segmentation, cross-selling, guiding customer acquisition and retention, and managing churn.
Companies utilize AI to identify emerging opportunities that extend beyond their current scope. AI-equipped tools sift through massive data sets to pinpoint "white space" markets for existing products, reveal new verticals, or suggest fresh product ideas derived from proprietary capabilities. These models empower sales teams to prioritize targets, exploring where competitive advantages might overlap with new customers, mergers and acquisitions prospects, or partnership opportunities. AI tools also track online chatter, intellectual property filings, and investment patterns, offering early indicators of profitable market moves.
Machine learning (ML) enables advanced micro-segmentation by analyzing diverse data points, including industry, region, company size, and buying patterns, to identify customers most likely to convert. This approach enhances segmentation accuracy and identifies overlooked submarkets that may yield new opportunities. By tailoring value propositions and ranking leads based on potential, organizations can invest resources where they matter most. Sales teams can then develop highly targeted outreach strategies, which increase engagement and boost conversion rates.
By integrating general AI with external data sources, companies can develop a detailed market map highlighting ideal prospects, estimated spending, and current market shares. This comprehensive view also uncovers specific customer details, such as their operational context or regional nuances, enabling a more precise go-to-market strategy. After merging these leads into a customer relationship management (CRM) system, inside sales teams can rapidly qualify potential buyers and channel them into the sales pipeline. This expanded pipeline ultimately drives higher growth and reveals customer segments that might otherwise remain hidden.
Coupling AI with enriched transaction data gives organizations powerful insights into expanding their customers' product portfolios. By analyzing past purchase behaviors, AI pinpoints each account's most relevant cross-sell opportunities, sometimes uncovering previously unknown patterns or preferences. Sales representatives then receive automated prompts indicating which products will likely resonate with existing clients (see sidebar "Informing Sales Through AI-Driven Opportunity Identification"). This efficient, data-driven approach helps teams unlock additional revenue without overburdening customers.
Preventing customer churn is critical in competitive markets. AI can analyze a wide range of factors—including pricing models, service responsiveness, and product usage patterns—to determine when churn risks are emerging. Additionally, sentiment analysis and interaction tracking enable sales leaders to identify warning signs of dissatisfaction early. Armed with these insights, companies can proactively intervene by adjusting offers, enhancing service levels, or addressing product gaps before a customer leaves.
With sophisticated preferences and needs, organizations can't thrive on one-size-fits-all approaches. Instead, they must evolve to meet customers' unique demands. Two main tools stand out: personalized value propositions fueled by generative AI marketing and generative AI-driven customer experiences (CX). Companies can differentiate themselves in competitive markets by tailoring solutions to fit each segment. This level of specificity builds trust, deepens engagement, and often leads to stronger customer loyalty over time.
Companies are increasingly relying on generative AI to develop marketing content at scale that still feels tailored to each buyer. They adapt these messages to various personas at different stages of the sales journey and deliver them through each client's preferred channel. Automating these steps not only elevates relevance and conversion rates but also reduces the burden of manual content creation. In many cases, organizations are shifting to a vertical-focused model, dedicating resources to specific industries or market segments and tailoring their offerings to address particular challenges. This deep specialization, powered by gen AI, allows marketers to craft immersive customer experiences that resonate with precise needs. They can also iterate on messaging through real-time feedback loops, ensuring it consistently aligns with evolving customer pain points.
Customers increasingly expect quick, seamless solutions, and gen AI-powered chatbots embedded in existing portals can meet that demand head-on. These digital assistants resolve issues rapidly, providing a more convenient experience that frees sales teams to invest time in building deeper client relationships or handling complex transactions. Chatbots can proactively suggest relevant content to guide customers toward the next best step, improving overall satisfaction. They also help companies identify recurring problems, which can lead to product or process improvements (see sidebar "Improving Service with Chatbots"). Ultimately, this blend of efficiency and personalization positions B2B organizations to stand out in fast-changing markets. Read more about the next wave of chatbots in our article: "The Digital Hive: Unleashing the Potential of Networked AI Agents."
Price pressures are mounting as competition intensifies and operating costs rise. Consequently, many organizations are exploring a balanced approach that combines price optimization; dynamic organizations improve margins and customer satisfaction by scoring and real-time performance monitoring. These strategies protect margins and are adept at addressing market fluctuations. By embracing AI tools in pricing, companies can create more personalized interactions with customers, leading to stronger relationships and sustained profitability in the long run.
With digital pricing platforms, businesses can set, update, and track prices in real-time, responding instantly to changing demand or competitor actions. Algorithms fueled by micro market data and rule-based logic continuously refine list prices to preserve margin and relevance. This data-driven method allows organizations to shift away from gut-feel decisions, fostering transparency and accountability. In fast-changing markets, such agile pricing moves can provide a decisive competitive edge by ensuring each price point remains aligned with current conditions.
AI helps companies standardize discounts and set packages by evaluating clusters of similar deals to discern customers' willingness to pay. Armed with this insight, sales reps gain a clear pricing roadmap supported by guardrails that minimize guesswork. By shifting from seat-of-the-pants haggling to disciplined, data-based pricing decisions, organizations often see improved margins and elevated customer satisfaction. Dynamic deal scoring also streamlines negotiations, allowing sales teams to move swiftly and confidently during critical deal moments.
Beyond initial price setting, an increasing number of organizations employ digital dashboards and transaction databases to track margins as events unfold. AI quickly flags any profit leaks, prompting teams to investigate and address them before they erode overall performance (see sidebar "Price Management Tools to Increase Margins"). Through ongoing analysis of sales patterns and transaction-level data, executives gain a holistic view of how pricing strategies perform over time. This structured, near-real-time feedback cycle enables them to fine-tune their approaches based on concrete evidence, ensuring they stay ahead of market shifts while protecting profitability.
Sales teams leveraging AI can outperform their competitors by rapidly identifying key prospects, engaging them efficiently, and adapting strategies as conditions change. These tools not only streamline manual tasks, such as drafting proposals and managing leads, but also provide valuable analytics that inform decision-making on the fly. By reducing the administrative burden on sales professionals, AI enables them to focus on strategic conversations and foster deeper relationships. This strategic agility often translates into faster conversions and higher overall sales effectiveness.
Determining which leads deserve immediate attention can be challenging. While sales teams have traditionally prioritized deal size, modern machine learning (ML) models incorporate additional indicators, such as industry alignment, behavioral data, and growth potential, to pinpoint the highest-yield prospects. These insights then route each lead to the best-suited account executive, increasing the odds of securing a deal. Over time, the model continues to learn from outcomes, refining its lead-routing decisions and boosting overall efficiency.
Responding to a request for proposal (RFP) is often a lengthy process that demands precise information and customization. Generative AI shortens that timeline by generating early drafts rich with competitive intelligence, customer pain-point insights, and an authoritative product narrative. AI Agents can offer further support by fielding questions on forecasts, customer histories, and past performance indicators, thereby sharpening the relevance of an RFP. This approach eliminates repetitive tasks, enabling sales teams to spend more time tailoring responses to the client's unique needs and context.
Effective account planning frequently separates top-tier sellers from the rest. Traditionally, this has been a tedious, manual endeavor—assembling diverse data sets and collaborating with multiple teams. Now, Gen AI can rapidly gather external market research, CRM data, and pipeline histories to produce a cohesive plan that outlines a customer's profile, objectives, and next steps. By offering immediate, data-driven suggestions, AI enables teams to skip preliminary work and proceed directly to strategic planning and execution.
Greater efficiency with automated account planning: A telecom operator developed a generative AI tool that generated first drafts of account plans, consolidating customer data, forecasts, and immediate tasks for various teams. By housing the plan in the company’s CRM, they established a single source of truth. A chatbot supplemented the plan with ongoing insights and external data. Preparation time has dropped from ten-plus hours per plan to mere minutes, and the telecom expects a 5- to 15-percent uplift in sales within a year of rolling this out.
From the moment a lead is identified to ongoing post-sales interactions, consistent engagement can consume significant time. Gen AI accelerates these processes by drafting compelling emails, prompting relevant follow-ups, and guiding best-next-step decisions. This allows sales professionals to shift attention away from administrative tasks and focus on building meaningful relationships. By delivering a personalized experience at scale, AI-driven lead management creates stronger customer loyalty and can help drive repeat business.
As the B2B market evolves, equipping a talented and future-ready sales force becomes even more critical. Skill sets now encompass coding expertise, rapid problem-solving, and creative collaboration. Two digital levers—performance management and capability building—are helping businesses upskill their teams and elevate performance.
Organizations increasingly rely on digital dashboards to monitor progress in real-time, from global metrics to individual targets. These interactive platforms integrate forward-looking and historical data, allowing executives to review conversion rates, quarterly pipelines, or annual contract values. Pairing this level of transparency with a disciplined review process enables companies to identify what's working, address gaps, and implement relevant improvements promptly.
Boosting revenue with AI-driven voice analysis: A logistics business studied 80,000 recorded sales calls to detect patterns that influenced conversions. They implemented a gen AI voice analytics system, converting speech to text and then using language models to categorize callers’ intentions, track sales tactics, and highlight why orders were canceled. These insights uncovered ways to refine lead outreach, pitch strategy, and rep performance. Over 12 weeks, the company’s conversion rate jumped from 1.8 percent to 3.0 percent, suggesting a potential $120 million yearly revenue increase once fully scaled.
Upskilling often demands more than traditional training methods can offer. Companies are tapping gen AI to identify each seller's strengths and weaknesses, provide just-in-time coaching, and present targeted learning modules. Advanced voice analytics, for instance, can analyze thousands of sales calls to identify where conversations falter, why deals fall through, and how specific techniques are successful. These insights then guide more relevant coaching (see the sidebar "Boosting Revenue with AI-Driven Voice Analysis").
Technology alone, however, rarely guarantees lasting impact. To succeed, companies must pair innovation with a well-structured execution framework and attentive change management:
By weaving these pieces together cutting-edge technology, structured change management, and an invigorated sales force—B2B players can substantially enhance their odds of capturing the next wave of growth.
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