How to Use AI in Sales: Top Strategies, Examples, and Tools – eWeek

Seeking ways on how to use AI in sales? Step into the future of sales with AI-driven techniques.
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AI helps the sales process by automating routine tasks, analyzing customer data, and optimizing sales strategies, which enables businesses to improve the accuracy of prospect targeting and personalize customer interactions. AI not only accelerates sales workflows but also provides deeper insights into customer behaviors and trends.
In a technical sense, AI in sales is the application of machine learning algorithms and AI-based analytical techniques to enhance several aspects of the sales process. In terms of revenue generation, AI can “hyper-charge” the sales process – so it’s no surprise that AI is quickly become an essentially sales tool.
To help you better implement AI in your sales processes, we’ll dive into various aspects of this rapidly growing sector, from the top strategies to the advantages of AI in sales. We’ll also look at some top tools and some leading examples of AI in sales.
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There is a wide – and growing – array of strategies for leveraging artificial intelligence in sales, ranging from researching the best tools to monitoring the success of your campaigns.
To effectively integrate artificial intelligence into sales, it’s crucial to first identify specific goals and challenges. AI can significantly impact areas such as lead generation, customer relationship management, and sales forecasting.
Pinpointing where AI can be most beneficial allows organizations to tailor their AI implementations to address particular pain points, enhance efficiencies, and drive revenue growth. This strategic alignment ensures that AI tools are deployed in a way that directly supports overarching business objectives.
To start, conduct a detailed analysis of your current sales metrics and processes. Engage with your sales team for their insights on challenges and bottlenecks, and use advanced analytics to track and identify patterns that could benefit from automation or enhanced analytics.
Once goals are established, the next step is to research and select the right AI tools. You can approach this by making a checklist of features and functionalities that are crucial for your sales processes and comparing how different AI tools stack up against this list. Also, consider the long-term scalability and support options of these tools to ensure they grow with your business needs.
Tools like Crayon for competitive intelligence or Salesforce for customer relationship management offer various features adapted to a variety of sales needs. Evaluate AI sales tools based on their ability to meet your sales challenges, integration capabilities with existing systems, user-friendliness, and scalability. Choosing the right tools gives you a higher chance of succeeding at your AI sales initiatives.
Al in sales: Crayon
As you research AI sales tools, you’ll encounter a broad array of tools that accomplish many tasks. Finding the best tool for your needs often requires trying a demo version. Image: a dashboard in Crayon Sales. 
Integrating AI tools into your sales strategy involves more than just technical installation. It requires aligning the AI capabilities with sales processes to enhance decision-making and operational efficiency.
You’ll have to configure AI tools to optimize data inputs, set up dashboards for real-time insights, or automate routine tasks to free up sales representatives for more complex interactions. You can begin integration by setting up the AI tools to automate data entry tasks and generate predictive analytics for processes like lead scoring. This can also involve customizing the user interfaces and dashboards to ensure they are intuitive for your sales team for a smooth transition and immediate uptake.
Proper integration means that AI tools will complement existing workflows and enhance productivity without disrupting these existing systems.
To gain a deeper understanding of today’s AI software for sales, read our guide to AI Sales Tools and Software
To maximize the benefits of AI in sales, comprehensive training for the sales team on the new tools is crucial. This training should cover how to use the AI tools effectively, understand the insights they provide, and apply these insights to daily sales activities. Training empowers sales representatives to leverage AI capabilities fully, enhancing their productivity and enabling them to make data-driven decisions.
The most effective approach to training is to develop a comprehensive training program that includes hands-on workshops, interactive simulations, and regular follow-up sessions. Focus the training on practical applications of the AI tools in daily sales activities to help your team understand and leverage their full capabilities. Schedule regular training sessions and provide resources for self-learning to ensure ongoing skill development.
Finally, encourage your team to experiment with different features and to provide feedback on their experiences, which can be used to further tailor the training program.
After implementing AI tools, continuously monitoring their performance and impact on sales processes is vital. Track metrics such as engagement rates, conversion rates, and overall sales growth. Insights gained from these metrics can help identify areas where AI tools are succeeding or where further optimization is needed.
Regularly refining AI configurations and functionalities based on real-time data and feedback ensures that the sales strategies stay effective and on par with changing market dynamics.
Where adjustment is necessary, you can adjust your AI strategies based on ongoing feedback to optimize tool performance and ensure they are meeting the evolving needs of not only your sales team but also your customers. This dynamism will help to sustain the effectiveness of your AI integrations and support consistent sales success.
Consider doubling down on AI for enhanced customer personalization. AI can analyze customer data and behavior to create highly personalized interactions and offers in a fraction of the time and with greater accuracy compared to any human agent. The approach here involves implementing AI-driven analytics to segment customers based on their behavior and preferences.
Take advantage of this segmentation to tailor marketing and sales strategies that resonate with each segment. And continuously update the data inputs to keep the personalization relevant and effective. From this, you stand to significantly improve customer satisfaction and loyalty, as well as have the opportunity to stand out in a competitive market and drive increased sales and customer retention.
To learn about AI for customer relationship management, read our guide: Top 8 AI CRM Software 
Before fully developing your AI sales approach, it’s helpful to get an overview of how AI can be used in sales – and the many advantages it offers over legacy sales techniques.
AI significantly enhances customer interactions by analyzing data to provide forecasts, optimize lead scoring, and improve engagement. By integrating AI, sales teams can identify which leads have the highest conversion potential and tailor their approach to meet the unique needs of each prospect.
For instance, AI-driven analytics can predict customer preferences and behaviors, which in turn directs sales teams on how to offer personalized recommendations and solutions that resonate more effectively with each customer.
Moreover, generative AI has opened new avenues for enhancing customer communications. These AI systems can generate personalized email content, chat responses, and even recommend new sales strategies based on evolving data patterns.
Additionally, generative AI is learning and evolving daily, to the point where it’s getting harder to distinguish whether you’re interacting with a person or AI. The perks of this level of personalization are the improved customer satisfaction and increased sales that result from making interactions more relevant and timely.
AI streamlines sales operations by automating routine tasks, allowing sales teams to focus more on strategic activities.
For example, AI can automate the qualification and follow-up processes, which then ensures that sales staff spend their time engaging with leads most likely to convert. Further, AI can optimize scheduling and workflow management for less downtime and greater efficiency of sales operations.
In addition to routine automation, another approach to streamlining operations is through generative AI. It enables the generation of highly engaging and contextually appropriate sales presentations, proposals, and promotional materials for specific customer profiles. This capability not only enhances the quality of materials sales teams have at their disposal but also significantly cuts down the time they spend creating these materials.
AI also plays a crucial role in optimizing pricing strategies, which of course has a significant impact on sales outcomes. By analyzing historical sales data, competitor pricing, and market trends, AI models can recommend pricing strategies that maximize profitability and market share.
Here’s basic insight into how it works: AI-driven pricing tools analyze vast amounts of market and internal data to identify optimal pricing points. These tools can help predict how changes in pricing could affect sales volume and revenue, which allows businesses to proactively adjust their strategies in real-time based on predictive analytics.
Such AI-driven insights help sales teams make informed decisions about when to adjust prices, launch promotions, or offer discounts since pricing strategies need to always be competitive, in line with overall business goals and in touch with the market.
To see a list of the leading generative AI apps, read our guide: Top 20 Generative AI Tools and Apps 2024
As transformative as it is, adopting AI in sales presents several challenges that businesses must navigate to reap the full advantages. These concerns range from data quality issues to major ethical concerns.
One of the primary challenges in implementing AI in sales is the quality and integration of data. AI systems must be fed high-quality, comprehensive data if they are to function effectively. Poor data quality or issues with data integration can lead to inaccurate AI predictions and recommendations, potentially shooting down sales efforts rather than helping them.
To overcome this challenge, companies need to invest in robust data governance practices. This includes regular audits of data accuracy, consistency, and completeness. Additionally, ensuring seamless integration of AI tools with existing CRM systems and data warehouses is crucial. Businesses may need to upgrade their infrastructure or employ middleware solutions to facilitate effective data integration and real-time analytics.
Another significant barrier is the resistance to change within organizations, particularly from sales teams that may feel threatened by AI automation. The fear that AI might replace jobs or undermine the value of human input can fuel reluctance in adopting new technologies.
Clear communication about the benefits and goals of AI implementation is key here. Training programs and workshops that demonstrate how AI tools augment sales capabilities rather than replace them can help in mitigating these concerns. Involving sales teams in the decision-making process regarding AI tool selection and implementation strategies can also foster a sense of ownership and acceptance.
The use of AI in sales also raises ethical and privacy concerns, particularly related to customer data. Misuse of AI tools can lead to breaches of customer privacy and potential legal issues.
Therefore, It’s imperative for businesses to adhere strictly to data protection regulations such as GDPR and CCPA when implementing AI in sales. This includes obtaining necessary consents for data collection and use, ensuring transparency in how AI algorithms utilize customer data, and implementing strong cybersecurity measures to protect the integrity of data.
For more information about generative AI providers, read our in-depth guide: Generative AI Companies: Top 20 Leaders
Real-world applications of AI have significantly impacted how sales processes are conducted across various industries. Here’s how companies are successfully integrating AI into their sales operations.
Companies like IBM and Walmart are utilizing AI to enhance their sales forecasting capabilities. By leveraging machine learning models, these companies analyze historical sales data, seasonal trends, and consumer behavior to predict future sales with high accuracy. This predictive capability allows them to optimize inventory management and allocate resources more effectively.
AI tools are being used to automatically summarize key points and action items from sales meetings and calls. Tools like AssemblyAI offer video and call summarization features that help sales teams quickly understand customer needs and follow up effectively.
Tools like Gong and Chorus.ai analyze sales calls to provide insights into customer interactions. These platforms use AI to identify patterns, suggest improvements, and even offer real-time guidance to sales reps during calls. This analysis helps refine sales techniques and improve overall sales performance.
AI is increasingly being used to recommend next best actions for sales reps. This includes suggesting follow-up tasks, identifying upsell opportunities, and advising on deal closure strategies based on predictive analytics. For instance, companies like Verix provide platforms that enhance commercial operations with AI-driven insights, boosting sales outcomes in industries like pharmaceuticals.
Generative AI platforms are now commonly used to craft compelling sales emails and subject lines that are more likely to capture the attention of prospects. Tools like OpenAI’s GPT models are trained to generate engaging and contextually relevant content, which can raise open rates and conversions.
Companies are using AI more and more to access advanced data enrichment and analysis to understand their market better and refine their sales strategies. Salesforce Einstein, for example, uses AI to enhance customer data by appending it with publicly available information and insights generated from behavioral data, providing sales teams with a richer, more comprehensive view of their customers.
AI-powered conversation intelligence tools like Chorus.ai and Gong.io are transforming sales by analyzing sales call recordings and providing actionable insights. These tools transcribe calls, pinpoint key moments, and analyze the effectiveness of sales pitches, helping sales teams improve their communication strategies and ultimately close more deals.
AI is used in sales enablement to automate content delivery and training. Seismic, a leading sales enablement platform, uses AI to automatically recommend the most effective content to sales reps based on specific deals, ensuring that they are always equipped with the most relevant and impactful sales materials.
AI tools are critical to improving pipeline management and forecasting accuracy. For instance, Clari uses AI to analyze sales pipeline data and predict which deals are most likely to close, allowing sales teams to focus their efforts where they are needed most and adjust their strategies to maximize outcomes.
AI is being leveraged to streamline and optimize sales engagement processes. HubSpot’s AI functionalities, for instance, help businesses automate lead prioritization and email scheduling, ensuring that engagement efforts are timed perfectly to maximize response rates and engagement success.
The future of AI in sales is being created even as you read this – the sector is growing at an exponential rate. From the benefits of hyperpersonalization to the remarkable advances in generative AI, the future of AI in sales may even have a sci-fi aspect to it.
The trend of AI-driven hyperpersonalization in sales utilizes deep learning algorithms to analyze detailed customer data and enable businesses to deliver highly personalized customer experiences. These AI systems can predict purchasing behaviors, personal preferences, and even sentiments based on customer interactions, allowing for tailored offers and communications.
This technology is extensively utilized in industries such as retail and e-commerce, where businesses like Amazon and Netflix have pioneered its use to recommend products or content based on individual user behaviors and preferences. Such systems analyze past purchases, browsing histories, and even customer interactions to tailor offers and communications.
In the near future, we can expect hyperpersonalization to extend to real-time adaptive interactions where AI can instantly adjust offers and content based on immediate customer behaviors or environmental factors such as time of day or current events. This will enhance the customer experience, increasing both engagement and loyalty, and is expected to become a standard practice in industries ranging from e-commerce to B2B sectors.
AI is streamlining sales operations by automating routine tasks and optimizing the sales funnel. Current AI software handle everything from lead scoring to customer segmentation and are poised to expand further, potentially managing end-to-end sales processes without human intervention.
In sectors such as automotive and financial services, companies are deploying AI to automate lead qualification, customer segmentation, and even direct customer communications, which significantly enhances operational efficiency. For instance, AI tools like Salesforce and HubSpot are not only streamlining these processes but also providing actionable insights that improve decision-making. This technology has led to faster sales cycles and more effective resource allocation.
Going forward, it wouldn’t be a surprise to see AI integrating deeper into sales platforms, providing real-time analytics and more accurate predictive insights that will make sales strategies much more successful and preemptively adjust them based on predicted market changes.
AI optimization
A dashboard in Salesforce that handles opportunity management, including suggestions to answer all client questions and inquire about discounts. 
Generative AI is making significant strides in automating the creation of personalized marketing materials. Marketing departments in industries such as fashion and consumer goods are increasingly relying on generative AI to produce tailored content that resonates with diverse consumer groups.
For example, generative AI tools are being used to craft unique promotional emails, social media posts, and even personalized video content at scale, which has proven to drive higher engagement rates and strengthen brand loyalty.
A notable tool is OpenAI’s Sora, a tool for generating text-to-video content that is set to instantly enable sales and marketing teams to create dynamic visual content that directly appeals to individual customer preferences and behaviors. Looking forward, generative AI is expected to become more sophisticated, with capabilities extending to creating interactive content that can adapt based on customer interactions in real time. This will make marketing efforts more engaging and so much more responsive, potentially increasing conversion rates and enhancing customer relationships.
Al in sales content creation
This image from the generative AI program Sora is an example of how AI tools can easily create engaging content for sales purposes. 
Currently used across various industries, from retail to manufacturing, AI forecasting models analyze vast amounts of data, including past sales, market conditions, and even consumer behavior, to provide precise predictions that help businesses plan more effectively.
Today, we see AI platforms like Gong utilize predictive analytics to provide detailed insights into revenue forecasting by analyzing buying signals across sales pipelines. Retail giants like Walmart and online marketplaces leverage AI to optimize inventory management based on predicted consumer demands, significantly reducing wastage and improving profitability.
Based on the above, the expectation is that in the near future, AI in sales forecasting will adopt even more sophisticated machine learning models that predict sales outcomes as well as provide prescriptive recommendations on how to achieve optimal results. These advancements will enable businesses to not only forecast future trends but also dynamically adjust their strategies in real-time based on AI-driven insights. It will make them more responsive to market changes and improve overall business agility.
The integration of AI into sales is transforming traditional roles as AI’s ability to automate routine tasks such as lead scoring, customer segmentation, and ad content creation is undeniable.
Companies like Google are already implementing AI to take over these types of jobs, indicating a trend towards automation of certain sales functions. For example, AI tools have been used to automate responses to RFPs, a time-consuming task that can now be handled more efficiently by machines.
However, rather than solely replacing jobs, AI is also enhancing the roles of sales professionals. By automating the more mundane aspects of the job, AI allows salespeople to focus on higher-level tasks such as relationship building and strategic planning. This shift may even be seen as positive among sales professionals, who would appreciate the increased efficiency and the ability to focus on more impactful aspects of their work.
However, as AI continues to evolve and become more competent at tasks of increasing complexity, the future of AI in sales may be a mix of both job displacement and augmentation. While some roles may diminish as AI takes over routine and administrative tasks, new opportunities are emerging for sales professionals who can leverage AI to enhance their strategic capabilities. The key challenge will be adapting to these changes by upskilling and integrating new technologies to make sales roles more strategic and impactful.
Based on the evolution of AI that we’ve seen through the years, it’s not likely we will face an undeniably disruptive version of AI that can completely cut out human labor from sales processes. It’s more realistic to expect a technology-driven sales environment where AI complements human skills, rather than replacing them entirely.
Salesforce icon.
Salesforce Sales Cloud provides an integrated platform that offers both CRM and AI capabilities. It allows sales teams to manage customer interactions more efficiently and gain insights that drive smarter, data-driven decisions. The use of Salesforce’s AI component, Einstein, helps in automating tasks such as data entry and lead scoring and offers predictive insights that improve customer engagement strategies.
HubSpot icon.
HubSpot Sales Hub offers a comprehensive suite of tools that includes CRM, sales engagement tools, and powerful analytics. This platform is designed to supercharge sales processes by providing everything sales teams need to manage their pipelines, connect with customers, and close deals more effectively. HubSpot’s integration of AI enhances these capabilities by automating tasks and providing detailed analytics to refine sales strategies, which yields better alignment and increased sales efficiency.
Apollo.io icon.
Apollo.io serves as an all-in-one sales intelligence platform that significantly impacts how companies prospect, engage, and drive revenue. With its AI-driven insights, Apollo.io helps sales teams streamline their engagement processes and improve their outreach strategies. The platform’s ability to enrich data and provide actionable intelligence allows sales professionals to target the right prospects effectively and close deals faster.
Generative AI is used in sales through automated content creation and providing data-driven insights. It can be used to create personalized emails, generate engaging content for marketing campaigns, and even develop sales scripts that are tailored to individual customer interactions. Companies like Salesforce utilize generative AI to drive personalization at scale.
An effective AI strategy for sales and marketing involves integrating AI tools that can analyze large volumes of data to provide insights, predict customer behaviors, and automate tasks. The strategy should focus on enhancing customer engagement, improving lead generation, and optimizing marketing campaigns through predictive analytics and machine learning. Tools like HubSpot and Marketo offer AI functionalities that assist in these areas by automating campaign management and providing actionable insights to sales teams.
Generative AI for B2B sales focuses on creating personalized customer experiences and streamlining the sales process by generating high-quality content tailored to business clients. This includes crafting personalized emails and proposals and even creating reports that are specific to the needs of B2B clients.
In short, yes. AI is increasingly being recognized as the future of sales due to its ability to streamline operations, enhance decision-making, and improve customer relationships through more personalized interactions.
AI’s role in sales is expanding as technologies become more sophisticated, allowing for greater automation and more accurate predictions of customer behavior. This shift is enabling sales teams to focus more on strategy and relationship building, while AI handles data-driven tasks, making the sales process more efficient and effective.
Integrating AI into sales brings endless opportunities for digital transformation to reshape the landscape of customer engagement and operational efficiency. By using AI, sales teams are not only enhancing their ability to understand customer needs but are also streamlining their sales processes, from lead generation to closing deals.
As AI technology continues to evolve, it’s looking likely to take a bigger role in driving sales innovation. And the sooner we learn how to take advantage of this technology instead of rivaling it, the faster we’ll reap its full benefits.
For a full portrait of the AI vendors serving a wide array of business needs, read our in-depth guide: 150+ Top AI Companies 2024
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