Learn how sales AI helps sellers improve automation, personalization and customer satisfaction.

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Empower sellers with generative AI to better serve prospects and sell more

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By 2025, 35% of chief revenue officers will resource a centralized “GenAI Operations” team as part of their go-to-market organization. As adoption accelerates, sales enablement leaders can drive responsible use of the technology to help achieve better sales outcomes. A key success factor will be to develop enablement programs based on use cases relevant to sellers’ roles as revenue generators.

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Download the research to learn to:

• Create content and training for revenue-generating roles
• Invest in generative AI literacy
• Experiment with prompt crafting
• Train sellers to create generative value messaging
• Evaluate technology and ensure compliance

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Harness sales AI capabilities to drive better sales outcomes

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The use of AI in sales has great potential to transform the function — from identifying opportunities and resolving challenges to boosting performance and client engagement. Focus on these key areas:

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01: Efficiency

Reduce sales cycles and improve customer engagement with AI in sales

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Advanced sales AI technologies such as natural language processing (NLP) and generative AI create significant opportunities to improve sales efficiency and customer engagement. These technologies work best when used to support B2B sales reps in their daily sales tasks and to increase customer engagement.

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Following are some of the areas where AI in sales promises the greatest impact:

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Demand generation.

Cleansing your CRM data is a first step in activating AI tools that automate digital marketing processes and enable chatbots and virtual customer assistants (VCAs) to have real-time customer interactions. AI also automates content distribution for buying tasks and helps to personalize responses to convert more leads.

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Deploy predictive lead qualification, guided selling and AI-based opportunity scoring across the B2B sales organization to:

• Better understand and predict customer behavior with data collection across the entire revenue production life cycle
• Improve engagement with hyperpersonalization that shares the right content at the right point in time during the buyer journey
• Convert more leads into wins with better opportunity scoring
• Improve sales and marketing alignment by bringing together all interaction data for a continuous customer experience

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Forecasting.

An immediate opportunity for AI investment, predictive forecasting offers:

• AI-based expected revenue for future periods
• Predicted revenue shortfalls/excesses versus assigned quotas
• Predicted revenue shortfalls/excesses versus sell-submitted forecast levels
• Forecast indicators at the opportunity level, used to help sales teams determine if specific deals should be included or excluded from specific forecast categories

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Improvements here may increase sales process efficiency, prioritize the right customers and deals, and ultimately decrease the cost of sales and cost of revenue acquisition. These savings could then be used to fund additional AI investments in sales and marketing.

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Conversation intelligence.

This rapidly growing area leverages NLP to understand speech and text-based communication across different platforms such as CRM, emails and call logs, to serve different sales use cases, such as:

• Analysis of call recordings. Instead of listening to hours of call recordings to identify coaching opportunities, sales managers can rely on conversational intelligence to analyze all available call recordings and identify what their high performers do differently.
• Deployment of virtual agents. Deploy conversation intelligence as a virtual agent to interact with customers and serve as an initial point of contact, funneling the customer to the right person within the sales organization. It can even follow up to gauge progress on the opportunity.
• Automated note taking. Automate note taking during client conversations, reducing sellers’ burden and allowing sellers to focus on the client.

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