Business-to-business (B2B) sales and marketing are two of the most challenging sectors for companies to crack. There’s an entire ecosystem of suppliers, customers, and partners, with a large and growing number of channels through which deals get done. The cost of entry is high, and the rewards are often elusive. In the digital age, regardless of the size of your organization, be it a small-medium enterprise or an established player looking to scale the B2B market, the prospect of competing against the might of the digital Goliath is daunting. However, with the right B2B AI use cases, you don’t need to be the top digital native company to compete. You just need to find the right services that can drive tangible results for your business.
In this blog post, you’ll discover the top applications of B2B artificial intelligence in sales and marketing. We’ll discuss the value AI can bring to your company, how AI can be used to automate tedious and time-consuming tasks and the types of AI that can be delivered to support your business. Let’s begin.
B2B AI Use Cases #1: Automating Content Marketing
Content marketing is essential for both new product launches and increasing the lifetime value of your customer base. However, the sheer effort required to produce high-quality content can be a major barrier to entry for businesses. With AI marketing tools, you can automate the production and management of content to scale your marketing campaigns across the entire customer journey. You can use machine learning and natural language processing algorithms to produce and deploy content at scale without having to hire additional staff. Further reading: How to Design an AI Marketing Strategy.
For example, you can use artificial intelligence in marketing via materials and email campaigns using a natural language generation tool. The tool can recognize the language used in your company’s emails and content, and produce content using words and images appropriate for your business. You can also use AI to recognize patterns in your company’s customer conversations and produce content designed to address common questions and complaints.
B2B AI Use Cases #2: Improving Customer Service
Customer service is among the top reported pain points across industries. Traditionally customer service has been exclusively based on human-to-human interactions —a customer reaches out to a service agent when they have a question or a problem. However, in many cases, customer service is neither pleasant nor efficient, resulting in poor customer experience.
By implementing AI-assisted customer service, you can address common issues and questions from your customers, while reducing the number of support interactions required to resolve issues. For example, you can use AI systems to automatically assign common issues to the correct team member, use chatbots, knowledge portals, etc. This can significantly reduce the amount of time spent managing issues, which will improve service quality for your customers.
B2B AI Use Cases #3: Closing Deals
Closing deals is an important part of sales and marketing, but it’s also one of the most challenging. In many cases, the hardest part of a deal isn’t the negotiation—it’s the closing. Depending on the deal, this may involve contract management, legal negotiations, or delivery terms and conditions.
But regardless of how you close a deal, the process is often difficult, time-consuming, and error-prone. With AI, you can use tools to identify critical steps in the deal-closing process, such as automating processes around the key players in the deal, where and what to meet to close the deal based on past blueprints, etc.
B2B AI Use Cases #4: Identifying sales leads
One of the prevalent B2B AI use cases is to predict what leads will be most interested in your company’s products or services. For example, if your sales reps are targeting companies that manufacture access network equipment, you could search through their digital channels for terms like short reach, fiber to the home, contractors, etc., which indicate someone who’s actively looking for new suppliers.
AI powered customer insights and lead generation tools like LeadFuze can help you with organizing demographic and live customer-related anonymized high quality data. A combination of AI and traditional human touchpoints makes lead nurturing more effective than ever before.
B2B AI Use Cases #5: Product and service recommendations
Companies long have used their sales and customer data to understand what products are selling well, which channels are driving revenue, and which leads are converting into customers. What if you could use that same data to recommend more of what’s selling to your existing customers?
That’s exactly what artificial intelligence has done for the technology giants like Amazon for personalized shopping recommendations, and can do for you today. The technology can track who buys what, why they bought it, how often they purchased it, etc., and then make recommendations about new products or services for existing customers. In doing so, AI reduces churn rates because existing customers feel like there’s always something new to buy from you – a win-win for everyone involved.
B2B AI Use Cases #6: Predicting Customer Lifetime value
Using AI to predict a customer’s lifetime value is an important predictive analytics use case for sales. If a company can predict which customers are going to be more valuable, they can invest their time and energy into closing these deals quickly.
For example, let’s say you have two prospective customers who have requested demos of your product: one is large enough that you need to spend more time with them as a company, but one is small enough that you could bring them on as a reseller relationship instead. You’re faced with choosing whether or not to do business with both at once or focus your efforts on just one account. Artificial intelligence can help you make that decision by providing information about how much each customer is worth so you know where to put your attention.
B2B AI Use Cases #7: Drive New Business Development
Business development is another critical success factor for sales and marketing strategy. You can use AI to support this critical function by automating the process of identifying and nurturing potential new opportunities by maximizing customer experience.
For example, you can use machine learning models to identify key decision-makers in companies that might be prospective customers. You can also use AI to identify prospective customers through various analog and digital channels and engage with them accordingly.
Summary
The future of sales is being shaped by AI, which stands to revolutionize how businesses are run. The most successful companies are already making AI investments in this area. They are integrating AI into their sales reps training and operational efforts, to automate manual tasks like lead tracking, set dynamic pricing, etc., whereas artificial intelligence marketing is prevalent, too—including personalization at scale.
To stay competitive and relevant in your industry, it’s wise to embrace AI technology for both sales and marketing efforts now. This post offers examples of seven real-world AI use cases in sales & marketing that will help you get started quickly. Now is a great time to understand and tackle the underlying challenges in AI marketing, and take advantage of these trends while they’re still gaining traction—and while you can set yourself apart from competitors using old-school tools alone.
