In the dynamic B2B sales sphere, building meaningful connections with potential clients is a constant challenge. Many companies offer similar products or services. Thus, multiple businesses are vying for the attention of the same potential clients.
In such a competitive environment, capturing the customer’s interest becomes even more critical. Sales outreach is pivotal in this process. Businesses have to reach out to prospects and establish mutually beneficial relationships. Moreover, sales teams must often adapt their outreach methods to newly emerged trends and requirements.
To overcome these challenges, many businesses are turning to Artificial Intelligence. With AI in B2B sales, companies can revolutionize their outreach efforts and achieve improved conversion rates. According to Gartner, by 2025, 75% of B2B organizations will complement traditional sales approaches with AI. For example, with an aim to improve and automate communication, businesses can adopt tools such as Regie.ai, which allows for creating personalized messages and predicting the best time for productive engagement. Moreover, solutions such as Chorus by ZoomInfo can help to analyze calls and emails and transform all the data into valuable insights for your sales team.
The purpose of this article is to explore the transformative potential of AI in B2B sales. We will study how AI technologies can enhance outreach campaigns and boost conversions. Read to the end to see real examples of how leading companies use AI for sales prospecting.
How can a B2B company use AI in sales?
Identifying and qualifying leads
AI has transformed sales prospecting and streamlined lead-generation efforts.
Through web scraping, this technology can collect publicly available information about potential prospects from various sources. With a tool like Bardeen.ai, you can gather all the data in a few clicks, streamlining your sales processes. For example, you can extract information from LinkedIn and automatically add it to Airtable or Google Sheets.
AI can analyze online activities like website visits, content downloads, and search behavior. This information helps to gauge one’s interest. By identifying specific actions that indicate purchase intent, AI can flag those leads as highly qualified. For instance, more than 60K businesses use Leadfeeder to identify their web visitors. With this platform, you can create feeds with filters applied, e.g., visit length, page views per visit, page URL, etc. Then, the tool will help you identify particular company names of workers most likely interested in your services.
As a result, businesses can rely on AI B2B lead generation and focus their efforts on high-potential leads. By qualifying them effectively, organizations ultimately improve conversion rates and sales outcomes.
AI in B2B sales allows businesses to engage with prospects on a more individualized level.
AI systems can consider factors such as a prospect’s industry, job role, and interests.
Tracking customers’ behavior and engagement patterns makes understanding their preferences easier. As was mentioned above, with AI apps such as Regie.ai or Smartwriter.ai, you can generate customized content for cold outreach emails or messages with this information.
For instance, the Regie.ai Chrome extension helps you research your prospect without leaving the Gmail draft. You can simply type in the email and click the right-corner button. Soon, you will see a window with communication advice, personality analysis, and other information. Then, the tool can generate messages based on your value proposition and selected data points. Choose one of the options, and you are good to go!
AI-powered recommendation engines can analyze customers’ preferences and past interactions. Then, they suggest the most effective communication methods and timing. This way, businesses conduct cold outreach through channels more likely to engage prospects. As a result, response rates are increasing.
Personalization increases the chances of capturing prospects’ attention and generating positive responses.
Sales forecasting and predictive analytics
AI in sales forecasting includes advanced algorithms and data analysis techniques.
AI predictive models consider variables such as seasonality, market conditions, competitors, and other external factors. Then, AI makes forecasts and predictions based on the processed data. Thus, companies can project sales performance with a higher degree of accuracy.
AI also analyzes historical sales data and customer behavior. With this information, organizations can predict future demand for products or services. This way, businesses can optimize inventory management, production planning, and resource allocation.
Moreover, AI can effectively perform “What-If” analysis. Among the best solutions for sales forecasting are Gong.io, Aviso, and Clari. These AI-powered systems can assess the potential impact on sales outcomes in different scenarios. Hence, businesses can make more informed decisions based on the forecasted results.
Although these three tools have the same functionality in terms of sales projection, the difference lies in Clari having more ease of use, setup, and admin. At the same time, Clari has a higher score in product direction, according to G2. Also, Aviso and Clari have more enterprise clients, while Gong’s segment is mid-market businesses.
Overall, with B2B sales analytics, businesses can gain valuable insights and make more accurate marketing projections.
Streamlining follow-ups and nurturing leads
AI may create automated drip campaigns and personalized follow-up sequences.
AI algorithms can analyze the leads’ demographics, engagement levels, and buying signals. Based on their conversion potential, AI assigns scores and prioritizes clients. Thus, sales teams can directly follow up on high-quality prospects with a greater chance of converting.
Also, AI tools can automate drip campaigns, a series of pre-scheduled and personalized emails or messages. This technology can analyze prospect data to generate relevant content. Moreover, AI dynamically adjusts the sequence based on client responses and interactions.
Automating this process allows sales teams to nurture potential customers systematically without manual intervention. Due to efficient multi-channel automation workflows, Campaigner users get up to 6 times more interactions with clients and prospects.
NLP for customer service
AI-powered chatbots and virtual assistants are instrumental in enhancing customer service. The human-like interactions are possible thanks to Natural Language Processing (NLP).
AI chatbots can respond to requests in a conversational manner. NLP enables them to comprehend messages and provide helpful assistance. Tidio became a great helper here as it allows for providing natural conversations, while combining AI and human support. By leveraging NLP algorithms, the bots can deliver automated 24/7 online support.
Companies can use NLP to analyze client sentiment expressed in text-based interactions. AI algorithms determine whether customer messages convey positive, negative, or neutral emotions. Hence, organizations can identify potential issues and take proactive measures to address concerns.
To integrate NLP chatbots, businesses can collaborate with development agencies or hire freelancers. Alternatively, they can opt for team augmentation services to strengthen their staff with skilled AI professionals.
AI-driven sales coaching and training
B2B AI can enhance the skills and performance of sales professionals.
Coaching platforms can provide personalized feedback to individual sales representatives. For example, in addition to accurate sales forecasting, Gong.io can analyze recorded sales calls. Then, the algorithms highlight areas for improvement in communication. Artificial intelligence can also provide recommendations on how to grow B2B sales, handle objections, and use closing techniques.
Using this technology, companies can offer their employees real-time guidance. AI can study ongoing conversations or presentations. Then, a sales representative can get contextual prompts and suggested responses.
Moreover, AI platforms can help incorporate gamification elements to increase motivation among sales teams. They include challenges, leaderboards, and rewards. Healthy competition drives continuous improvement in sales performance.
Best Practices for Successful AI Implementation
Implementing AI in B2B sales can bring significant advantages but requires careful planning. To ensure effective integration, companies should follow key best practices.
- Clearly define objectives and goals. Identify specific areas where AI can enhance sales processes. Understand what problems AI should help solve and its implementation’s primary goal.
- Identify the right AI solutions for particular needs. Conduct thorough research to determine the most suitable AI tools for B2B marketing. Different AI systems exist for lead generation, customer profiling, predictive analytics, and sales automation.
- Ensure quality data. Implement robust data governance practices to maintain data integrity and compliance. Leverage data cleaning, standardization, and data collection, storage, and usage protocols establishing.
- Foster collaboration between sales and AI teams. Encourage open communication between these teams. Sharing insights helps to optimize the use of AI in B2B sales processes.
- Continuously monitor and evaluate AI performance. Establish measurable metrics, KPIs, to evaluate the impact of AI on sales outcomes. Constantly review and refine your AI algorithms.
Real-World Examples of AI in B2B Sales
Mack, a truck industry company, uses AI in its marketing processes. The company leverages sales automation to score leads and drive engagement from multiple sources. Mack has created a long-form video series, “Road Life,” to reach the prospects. To watch the series, users must leave contact information such as name, email, and mobile number. This initial engagement serves as the entry point into the lead nurturing process.
Mack Trucks utilizes Eloqua, an AI-based marketing automation platform, to evaluate the gathered information. The scoring system helps prioritize and categorize prospects based on their level of interest.
Drift leverages AI in its sales processes through its Revenue Acceleration Platform. Drift’s Conversational AI analyzes customer conversations, identifying key topics and frequently asked questions. Marketing teams use this information to take appropriate action.
Moreover, Drift utilizes AI-powered Virtual Selling Assistants (VSAs) that chat with visitors in a human-like manner. These VSAs can accurately answer unexpected questions and seamlessly transition between topics.
Compared to traditional approaches, Drift’s AI-powered solution stands out with its ability to deliver personalization at scale. AI generates a qualified pipeline, enhances the customer experience, and improves prospecting efforts.
HubSpot utilizes AI in B2B sales across various aspects, including data cleanliness, content optimization, and sales enablement. HubSpot automates the process of scanning business cards and correcting any errors in the contact information.
Moreover, this company uses an AI chatbot, HubBot, on the website. This bot handles the users’ questions. If more complicated issues arise, human representatives can take over from there.
Additionally, HubSpot leverages AI for sales enablement by creating predictive lead scores. AI technologies recommend optimal send times for sales emails and enhance the CRM with key data points.
Artificial intelligence is a game-changer for B2B companies. It offers innovative ways to generate B2B leads and improves sales outcomes.
AI simplifies the lead prospecting process. In particular, AI in B2B sales enables personalized communication and engagement with prospects. Moreover, AI can identify and qualify leads. With advanced technologies, companies can also predict sales performance and prioritize their communication.
To use AI in B2B sales effectively, we recommend understanding the main goal and defining the most relevant tools. Also, ensure data reliability and compliance with governance practices. To align sales strategies, provide collaboration between the sales and AI teams. In the end, analyze the effectiveness of AI B2B-marketing and make the appropriate changes.
Looking ahead, we can expect continued advancements in AI for B2B sales. Artificial intelligence will become even more adept at predicting customer behavior. Chatbots and virtual assistants will be more sophisticated in understanding human language. AI will integrate with emerging technologies such as augmented reality (AR) and virtual reality (VR).
How can AI be used in B2B sales?
AI in B2B sales can:
- help with lead generation
- predict possible sales
- provide personalized communication
- generate content for emails and messages
Will AI ever take over sales?
AI is developing quickly, but it would be unlikely for it to ever replace sales representatives. For machines, it can be challenging to build trust with customers. The best way to approach B2B sales is by combining human skills and AI technologies.
What is the future of AI in sales?
Artificial intelligence will help companies to close more sales. More companies are incorporating AI in the sales process to improve their performance. Furthermore, using VR and AR technologies with AI will improve customer engagement and increase your sales.
Vitalii Makhov, CEO at DOIT Software, an IT Staff Augmentation company. The DOIT Software team is passionate about building bold systems and solving business challenges for startups, product companies, and digital agencies.