Picture this- A sales rep juggling with multiple leads, struggling to prioritize follow-ups, and relying on instincts to close deals. The result? Missed prospects, wasted time on cold leads, and inconsistent sales pipeline. How can the sales team overcome the challenge of identifying high-value leads, and personalize outreach to close deals faster? The answer lies in leveraging AI.
Enterprises are leveraging Predictive AI to analyze historical and current pipeline data, provide sales team with meaningful insights that can improve customer conversion rate. On the other hand, Generative AI plays a crucial role in tailoring sales pitches based on past customer interactions to deliver highly personalized content that delivers value and increases the likelihood of conversions. With AI in sales, businesses can adopt a data-driven approach to manage the pipeline efficiently and enhance lead conversions.
“It’s about making connections through the data that you might not have made as a human being. AI has the uncanny ability to tease out things about the consumer you might never think about.”- Ryan Bezenek, vice president of IT, Ariat International.
Einstein AI, a tool that salespeople can directly use in their CRM ease their dependency on third party tools. Built directly on Salesforce, it uses predictive AI capabilities to understand customer behavior and analyze engagement patterns, helping sales teams to prioritize promising leads. Additionally, with Einstein’s generative capabilities, sales teams can craft personalized pitches that instantly resonate with prospects, driving stronger connections and faster results.
In this blog, we’ll explore real-world use cases showcasing AI’s impact on sales and outline key steps to build a robust strategy for AI in sales.
Four Real-World Use Cases for AI in Sales
AI empowers sales to move beyond instincts in managing multiple leads or prioritizing follow-ups. Leveraging AI, teams can work smarter, target more effectively, and close deals faster to boost sales revenue.
Here are key sales challenges/use cases Einstein AI solves with ease!
1. Prioritize Lead Scoring
AI leverages data science and machine learning to analyze vast data sets, pinpointing high-potential leads accurately. By assessing factors like behavior, demographics, and past interactions, predictive AI assigns scores that prioritize leads most likely to convert. 80% of reps working on teams using AI say it’s easy to get the customer insights they need to close deals, compared to just 54% at orgs without AI. Notably, high-priority leads receive top scores as AI analyses your business’s patterns of lead conversion. It ranks the current leads based on the similarities with past converted leads. With AI-driven lead scoring, you eliminate guesswork, save time, and optimize efficiency by targeting the right leads and close deals faster.
Einstein Lead Scoring Dashboard
Image Source: Salesforce.com
2. Evaluate Deal Health
Predictive AI in sales helps teams stay ahead by assessing the health of every deal in the pipeline. It analyzes historical data to evaluate key factors like deal stage, engagement levels, engagement trends, and communication patterns to provide a comprehensive health score for each opportunity. These insights help sales reps identify deals at risk, prioritize those with the highest scores, and use Generative AI to recommend highly tailored actions to keep deals on track. Leveraging AI, your team can proactively address roadblocks, and make smarter sales decisions, ensuring no opportunity slips through the cracks.
Deal Health Insights Using AI
Image Source: trailhead.salesforce.com
3. Enable Opportunity Scoring
Salesforce Einstein uses predictive AI to assess various deal factors such as stage, engagement, and historical trends, automatically assigning scores to opportunities. This allows sales teams to identify and prioritize the most promising deals, ensuring efforts are focused on where they’re most likely to win deals. By leveraging these insights, teams can close deals faster, improve win rates, and allocate resources more effectively.
Einstein Opportunity Scoring
4. Unlock Predictive Forecasting
Sales teams can use predictive forecasting to evaluate customer behavior based on past interactions. AI analyzes historical data, current trends and external factors to forecast future selling opportunities. Armed with these insights, your sales team can get more visibility and build a smarter pipeline. By anticipating future performance, you can better plan your business decisions, optimize resources, manifest cross-selling and upselling opportunities, and steer your sales efforts towards success.
Smarter Sales Insights with Predictive Forecasting
How to Create a Strong Implementation Strategy for AI in Sales?
Many organizations struggle with AI implementation -whether it’s messy data, outdated systems, or a siloed sales team unsure of how AI can help! These challenges can leave AI’s true potential untapped, but with the right approach, it can be a game-changer for sales success.
AblyPro makes AI in sales implementation effortless. Using our 3A’s approach, we identify key areas where AI adds value—like lead scoring and sales forecasting. We cleanse and prepare your historical data for AI-driven predictions, ensuring it’s ready to drive results. As your extended team, we guide you at every step, so you can focus on closing deals faster.
Final Words
AI in sales is the ultimate game-changer that empowers your team to create smarter and streamlined pipelines. It eliminates guesswork in lead prioritization with accurate scoring, ensures smarter deal management with real-time insights, forecast sales with precision and more. By addressing inefficiencies and saving time, AI empowers the sales team to do what really matters- build strong relationships and close deals faster.
Author
Global COO, AblyPro
For 20 years, Neeraj has worked alongside a multitalented team to help associations and nonprofits drive digital transformation within their organization, enabling them to be more innovative, agile, and donor/member-centric. As AblyPro’s Global COO, he leads an internal task force that shares lessons learned, best practices, and practical applications that specifically relate to associations and nonprofits. With 300+ developers by his side, Neeraj provides clients with the resources and capacity to power up their teams.
