Sales AI: How Artificial Intelligence Is Reshaping the Future of Selling

As we approach the mid-2020s, nearly every industry has adopted artificial intelligence (AI) to streamline and improve processes, including sales. AI doesn’t eliminate the need for human sales reps. Instead, it provides sales teams with valuable insights and frees up time spent on manual tasks so teams can focus their attention on converting leads. In fact, 79% of sales teams agree that AI allows them to spend more time selling.  

At Smith.ai, we take pride in combining AI and real human interaction in our Virtual Receptionists, Voice Assistant, and Outreach Campaigns to deliver the best experiences to win more leads. Below, we’ll cover how AI can benefit sales teams, how you can integrate AI into your sales processes, and tips for effectively executing sales AI. 

What is artificial intelligence (AI) in sales? 

AI in sales refers to adopting and applying AI tools and technology to improve various parts of the sales process — like lead qualification, lead intake, sales outreach, and sales forecasting. AI uses advanced algorithms and machine learning models to automate tasks, analyze data, and provide sales teams with valuable insights to help them improve their sales efforts and close more deals.    

According to HubSpot’s State of AI report, automating manual tasks, gaining data-driven insights, and writing outreach emails are the most popular ways sales professionals use AI today.

How AI can benefit sales teams 

Here are some of the many benefits of implementing sales AI: 

• Improves decision-making: AI can provide data-driven insights, helping sales teams make quicker and more informed decisions during sales calls and improve their overall sales strategies. 

• Boosts revenue: AI technology, like conversation analytics tools, can provide sales teams with personalized insights on customers, helping them strategize targeted selling opportunities to increase sales and revenue. 

• Enhances the customer experience: By analyzing customer and lead data, AI tools can provide personalized recommendations, content, and messaging to improve the overall customer experience. 

• Eliminates time-consuming tasks: AI can handle routine and time-consuming tasks, like logging and gathering lead data or sending follow-ups, increasing efficiency amongst sales team so they can concentrate their efforts on higher-value tasks.

7 ways to integrate AI into your sales process 

Here are seven ways your team can apply AI to sales operations, enhancing efficiency and overall performance. 

1. Lead qualification and scoring 

Tools like AI-powered voice assistants can speed up the lead qualification process and help capture important information on leads by asking qualifying questions. 

For instance, a project management software company's AI voice assistant may ask qualifying questions about the lead’s goals, preferences, and budget to determine their level of interest and purchase readiness. The AI technology can pick up keywords to determine whether a lead is a good fit and suggest the appropriate next steps — like booking a demo or routing to a live agent for more information. 

AI-powered tools can also score leads based on historical data and predetermined criteria — like demographics, engagement, and buying behavior — so sales teams can prioritize leads with a higher chance of conversion. 

At Smith.ai, our Voice Assistant can have natural conversations with inbound leads and capture important information needed to score them. Our live agents then have all the information they need to proceed with qualified leads. 

2. Sales forecasting 

With its advanced analytics and data processing capabilities, AI can analyze historical sales data and customer interactions to identify trends and patterns and use that information to forecast future sales outcomes. 

For example, AI sales forecasting tools like Aviso can analyze the duration of past sales cycles and identify the most common stages where deals are closed. This gives sales teams a more accurate sales forecast so they can tailor their strategies based on the anticipated timeline. 

Since these forecasts are based on large amounts of historical data, they give sales teams more accurate and reliable predictions — helping businesses set realistic goals and allocate resources effectively. 

3. Cross-selling and upselling 

You can also use AI tools to analyze customer data, making it easier to identify upselling and cross-selling opportunities. 

For example, AI tools can recommend additional products or services to existing customers based on their purchase history and preferences. They can also analyze customer conversations to uncover pain points and identify how additional products or services can help solve customer problems. 

4. Conversation analysis 

Many CRMs, like Salesforce Einstein, have built-in conversation analytics features that can evaluate conversations — like sales calls or chatbot interactions — to provide insights into things like: 

• Customer sentiment: When analyzing customer interactions, conversation analytics tools pull keywords and phrases and use natural language processing (NLP) to identify either negative or positive sentiment — which can help with decision-making during the sales process. 

• Customer pain points: From these interactions, these tools can identify customer pain points so sales teams can use them to make tailored sales recommendations. 

• Agent performance: Conversation analytics tools can also evaluate agents’ conversations with leads and customers — providing sales teams with insights into what strategies are working and what areas could use improvement. 

5. Price optimization  

AI can analyze market conditions, competitor pricing, and past deals to help teams create better pricing strategies. For example, dynamic pricing tools like Accenture utilize AI algorithms to scrape pricing data from competitors and offer recommendations for competitive pricing. Let’s say a competitor lowers the price of a similar product or service; these tools may recommend a price adjustment to remain competitive in the market.  

With historical sales and customer data, AI can also provide personalized pricing recommendations for each lead, helping teams close more deals by offering customers a price that’s hard to beat.  

6. Automated email campaigns 

When it comes to outreach campaigns, AI can help sales teams in two ways: automation and personalization. 

• Automation: AI-powered email marketing tools can automate the delivery of personalized email sequences, ensuring timely follow-ups with leads. For example, once you’ve wrapped up a call with a lead, AI tools can send an automated email with additional content to guide them further down the sales funnel. 

• Personalization: AI can also help craft highly personalized outreach messages by analyzing customer data. This helps tailor your messaging to customer preferences and needs, increasing the chances of engagement and conversion.

At Smith.ai, we can help you nurture leads by sending personalized email follow-ups on your behalf to move leads closer to conversion. 

7. Lead nurturing 

When nurturing leads, it's essential to deliver relevant content and information to increase the likelihood of conversion. AI can automate the nurturing process and deliver relevant content and follow-up messages to leads over time, gradually building their trust and interest.

For example, an e-commerce site that sells fitness equipment may utilize AI for lead nurturing in the following ways: 

• Buyer behavior: AI algorithms can identify patterns and preferences in buyer behavior based on historical data. In this case, AI tools may recognize a frequent site visitor who has made multiple visits to the home gym equipment page but has yet to make a purchase. 

• Tailored content: With the help of AI and the backlog of data gathered, it makes it easier for sales reps to tailor messaging and send personalized content that will entice a buyer to make a purchase, like articles or videos.

• Personalized product recommendations: AI tools can then make recommendations based on this data to help push leads to a purchasing decision. For the user showing interest in home gym equipment, the AI system might suggest related products, like dumbbells or cardio machines.   

Tips for executing sales AI

Ready to enhance your sales processes with the help of AI? Before you dive in, here are a few tips to help ensure seamless implementation: 

• Start with simple tasks: When implementing AI, hone in on simple tasks first, like automated email responses or data entry, to give your team more time to focus on tasks that require human interaction. 

• Integrate with your existing tech stack: Find AI applications that seamlessly integrate with your existing sales tools to help streamline workflows and increase team efficiency. 

• Develop performance metrics: KPIs and performance metrics are critical in understanding the effectiveness of your AI tools. For example, analyzing at what point customers prefer to speak to a real agent after conversing via chat is a good chatbot metric to measure.  

• Balance human and AI interaction: AI is meant to enhance workflows, not fully replace human agents. Use AI tools to help with more time-consuming tasks, like compiling lead lists. 

• Update your AI strategy: Revisit your strategy often to ensure you still align with business objectives, provide your customers with the best user experience, and adapt to evolving AI technologies. 

Optimize your sales process with Smith.ai 

Striking a balance between AI and human interaction is essential. Human involvement is needed, but AI can help sales teams work more efficiently and achieve better results. 

At Smith.ai, we pride ourselves on balancing AI and human interaction. Whether our live agents are using AI workflows to help personalize conversations or our Voice Assistant helping to qualify leads, AI makes the process smoother for our customers (and yours!). 

Curious about how we can help you implement sales AI? Visit https://smith.ai/booking for more information.