Blog · 2024-11-19
AI for sales: How to win more deals with AI
Key concepts of AI and how they are transforming sales processes from lead generation to closing deals.
This write-up explores how AI is transforming how sales teams get work done. Through practical example use-cases, you'll discover how AI impacts:
- Lead generation
- Personalised outreach
- Sales forecasting
- Training and performance analysis
You'll learn how your sales team can use AI to automate tasks, personalise engagement, and provide sharper insights—so you can focus on building relationships and closing deals.
The changing landscape of sales
Sales has always been a demanding and competitive field. In fact, 53% of sales pros say it's harder to sell in 2024 than it was just a year ago.
AI helps combat that demand and competition in many ways—and has been doing so for a long time. But recent advancements in AI have brought new tools, faster processes, and workflows that weren’t possible before.
Thanks to the recent explosion of generative AI, sales teams can now excel at handling workloads, closing deals, and managing higher customer expectations.
If you're in sales, you've likely felt the pressure to be more efficient and more personalised in how you engage with leads. That's exactly what generative AI is designed to help with. It automates time-consuming tasks, helps personalise your outreach at scale, and gives you sharper insights—all so you can focus on closing deals and building relationships.
In summary…
Reps find selling tougher now than ever, but generative AI is helping by automating tasks, personalising outreach, and providing better insights. This means sales teams can work more efficiently and close deals faster.
What is generative AI?
Broadly speaking, generative AI is a type of AI that can create useful content for you based on the data it has been trained on. It can create text, images, voice replicas, and videos. In terms of sales, generative AI can be useful for things like emails, proposals, data insights, customer interactions, and more.
Generative AI is a newer form of AI that gained popularity from 2020 onwards. It became more prominent in 2022, thanks to tools like Jasper and Copy.ai. The launch of ChatGPT in late 2022 really accelerated this trend, making generative AI mainstream for sales and marketing professionals.
In summary…
Generative AI creates content like text, images, and videos based on its training data, and is useful in sales for tasks such as emails, proposals, and customer interactions.
The evolution of AI in sales
1. Traditional AI
Around the early to mid-2010s, AI started becoming more accessible to sales teams through CRM platforms like Salesforce and HubSpot. Integrated AI features like predictive lead scoring would analyse customer behaviour to help prioritise leads and forecast sales. Traditional AI is great at processing information but doesn't create new content.
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2. Generative AI
Generative AI takes everything traditional AI does and adds creativity to it. It doesn't just predict outcomes, it also creates. Think of gen AI more like an assistant that helps you generate new material, not just analyse data.
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3. Autonomous AI
Looking further ahead, autonomous AI can make decisions and take actions on its own. Imagine an AI that not only drafts your emails but also sends them, follows up at the right time, adjusts the approach based on the client's response, and even schedules meetings. It's the next evolution, where AI moves from assisting to acting without constant human intervention.
🔎 Using AI for lead prospecting
How it works:
Finding good leads takes time, and guessing which ones are worth your effort can be a gamble. AI can analyse vast amounts of data quickly to identify the leads most likely to convert. It looks at things like job titles, online behaviour, or company growth to find prospects that fit your target profile.
Recommended tools
Sales teams can use AI tools like ZoomInfo or Clearbit to identify ICP companies. The AI within these tools scans sources like websites, public databases and news articles, then gathers useful data like company info and contact details for key decision-makers,. It then builds a list of qualified prospects, ranks them based on buying signals, and sets follow-up tasks.
Or with a platform like Apollo, you can search their comprehensive database and use the built-in AI to get recommendations of suitable prospects. This takes the guesswork out of knowing who to contact.
LinkedIn is a popular place for lead prospecting too, but tools like those mentioned above are restricted from accessing it. Instead, you can use LinkedIn Sales Navigator to prospect leads on LinkedIn.
Why it's effective:
Automating lead discovery through public data sources, alongside LinkedIn Sales Navigator's professional network insights, helps sales teams receive timely, high-quality leads without the need for manual research.
🤖 Practical example:
Your sales team uses Clearbit to discover leads in the healthcare sector. Clearbit's AI scans company websites, news sources, and public databases to find firms with 500 employees or more. It gathers public contact details of decision-makers, like CFOs and IT managers.
At the same time, the team uses LinkedIn Sales Navigator to find more prospects based on specific job roles and industry criteria, adding another layer of targeted leads.
This combined data is synced with your CRM, giving the sales team a comprehensive list of qualified leads ready for outreach.
👋 Using AI for personalised outreach
How it works:
Generative AI makes outreach more personal by analysing lead data to craft messages that fit each lead's needs. It automates email writing, adjusting tone and content to make communication more relevant and engaging. This frees up time for sales teams and helps them build stronger connections with prospects.
Recommended tools:
AI tools like Outreach.io or Gong can automate email campaigns by generating personalised messages for each lead.
Gong uses insights from sales calls, emails, and CRM data to tailor the outreach based on the prospect's stage in the buyer journey, interests, and known challenges. The AI adapts tone and content to match each prospect, so your outreach feels personal and relevant, even at scale.
Why it's effective:
Personalisation boosts engagement. Instead of generic mass emails, AI-driven outreach makes leads feel like the message is crafted just for them, addressing their specific challenges.
Plus, AI handles this at scale, so your team can connect with hundreds of leads while continuously refining the emails for better results.
🤖 Practical example:
A lead attends a product demo call with your sales team and mentions concerns about scalability.
After the call, they receive a follow-up email that seems perfectly tailored to their needs. It includes case studies showing how similar companies solved the exact scalability challenges they're facing. The timing feels spot-on too—it arrives just when they're thinking about the next steps.
What the lead doesn't know is that Gong's AI analysed their conversation, identified key concerns, and automatically crafted the email. Gong also predicted the best time to send it based on the lead's past engagement, making the outreach feel personalised and relevant.
The result? The lead feels understood and is more likely to respond, moving them closer to a deal.
📊 Using AI for sales forecasting
How it works:
Sales teams can use generative AI to spot opportunities and flag any potential risks. By providing past data and info on current trends, the AI can make helpful predictions. Then, using this insight, sales teams can adjust strategies, manage resources well, and face challenges more confidently.
Recommended tools:
AI tools like Clari and Aviso use machine learning to track interactions across emails, meetings, and more. They update sales forecasts in real time, adjusting as new data is gathered. The AI helps by:
- Analysing your sales pipeline to highlight strengths and areas that need attention
- Identifying deals that are at risk
- Suggesting actions to improve your chances of closing deals successfully
This keeps your forecasts accurate and helps you focus on the deals that matter most
Sales teams can also use AI chat assistants like ChatGPT or Claude to get insights on their CRM or pipeline reports. These tools don't have native forecasting capabilities like Clari, but they can be helpful for things like:
- Interpreting existing data
- Generating summaries
- Answering complex questions
For example, sales reps can upload data to Claude and ask questions like, "What are the key blockers in our current pipeline?" or "Which deals have the highest risk of not closing this quarter?".
Why it's effective:
Sales forecasting tools help teams identify trends and risks earlier by providing deeper visibility into the sales pipeline. AI tools like ChatGPT and Claude can quickly process complex information and give human-like responses, making data more accessible and understandable for sales teams.
🤖 Practical example:
Your sales team uses Clari for forecasting. The AI continuously tracks deal progress, and highlights that a deal worth $100,000 is at risk because communication has slowed down. It suggests scheduling a follow-up meeting with the decision-maker. Your team acts quickly to prevent the deal from slipping through the cracks.
Clari also revises the overall forecast based on real-time updates across the pipeline, providing leadership with a clear, up-to-date revenue projection.
Meanwhile, your sales manager asks ChatGPT: "What are the common factors among deals that failed to close in the last six months?" The AI processes CRM data and identifies a lack of follow-up meetings and communication gaps in the late deal stages. ChatGPT offers actionable suggestions your team can implement.
👟 Using AI for sales training and performance analysis
How it works:
Generative AI helps sales teams improve by analysing interactions and identifying effective techniques. It evaluates calls, emails, and other customer interactions to highlight patterns and provide feedback on tone, phrasing, and response timing. This data-driven approach helps make every conversation more effective.
Recommended tools:
AI tools like Gong, Chorus, or Salesloft analyse sales calls, emails, and customer interactions to give insights into performance. They transcribe conversations, identify patterns, keywords, and engagement cues linked to success. These tools can highlight common objections, effective phrases, and the best timing for responses.
Some AI platforms also assess soft skills like tone, pace, and empathy. This helps sales managers spot areas for improvement and tailor training to address specific skill gaps, enabling reps to keep improving.
Why it's effective:
AI analysis provides objective, data-driven insights that can be hard to capture manually. AI can track metrics like, talk-to-listen ratios, response rates, and closing phrases, and can give actionable feedback on individual and team performance.
Sales teams can then use these insights to:
- Refine techniques
- Adopt best practices
- And identify high-impact strategies.
This not only leads to better sales conversations but also reduces the need for manual reviews. AI tools enable ongoing, scalable training by automatically highlighting and sharing successful approaches.
🤖 Practical example:
A sales manager uses Gong to review recorded calls from a high-performing rep. The AI identifies that the rep uses a specific sequence of open-ended questions to keep prospects engaged. Gong highlights this pattern and suggests it as a best practice for the team.
Later, the AI flags a common customer objection around pricing that regularly comes up in unsuccessful calls. The manager uses this to create a targeted training session focused on handling price objections. With AI’s help, the team benefits from real-time learning and improved sales techniques across the board.