Numerous industries are changing due to advances in machine learning and artificial intelligence. One of the main areas AI and machine learning software companies work with businesses is B2B transactions.
However, it can be challenging for businesses to decide which B2B sales areas are best for implementing AI capabilities. As a result, this article discusses popular applications of AI in B2B sales to help sales executives make informed investment choices.
What Is The Procedure For B2B Sales?
Two categories can be used to separate B2B selling:
Within sales that are run by a CRM program, like Salesforce
Field sales that involve in-person customer meetings
For both, finding potential clients who could be interested in the goods being offered is the first step in the sales process. Following that, leads are rated according to their potential, with some of them qualifying as opportunities. The sales staff then uses offerings and services to turn these opportunities into actual sales.
Numerous technologies, such as workers or digital assistants that can schedule meetings and generate emails, are available through this sales funnel to support sales teams in automating certain tasks.
This is where artificial intelligence comes in. Machine learning systems are used in the majority of modern sales tools. Companies may generate, score, and convert leads with the help of AI suppliers.
In B2B Sales, Who Are The Stakeholders?
In comparison to B2C salespeople, B2B salespeople typically entail a more involved procedure and need greater effort. B2B sales are therefore slower. This is because, in B2B transactions,
Sales are typically larger in volume.
Errors in the procurement process might result in job losses for several parties.
B2B acquisitions often involve five different kinds of stakeholders:
Buyer: Conducts market research and creates a shortlist. usually initiates contact with sales representatives and connects them with other relevant parties. This could come from the business, the process/transformation unit, or the IT department.
Users: Those who will put the product to real use. They might enter the process at a later time, depending on the particular good or service.
Advisors include dependable staff members, outside experts, and industry analysts with hands-on expertise. By adding new vendors to the shortlist or endorsing existing ones, they have an impact on the decision-making process.
The one who makes the final decision: The one who accepts or rejects the purchasing proposal. Following this phase, the tech procurement procedure begins, and compliance officers assume a significant role.
Compliance: Those in charge of the procurement, legal, IT, and information security departments guard the business against potentially hazardous purchases.
Why Is It Crucial To Incorporate AI Into B2B Sales Processes?
Among B2B businesses, the notion of integrating AI technology into sales processes is becoming more and more common. 30% of all B2B businesses were predicted by Gartner to use AI in 2020 to improve at least one of their core sales processes.
AI can increase the overall effectiveness of sales operations and automate a variety of manual duties that B2B sales representatives are accountable for. For instance, the typical sales representative who uses CRM enters activity and contact data for 5.5 hours every week. An average of $13,200 is spent yearly by businesses on all these activities for each CRM user.
Businesses can use AI to automate the data entry process into CRM systems, freeing up sales representatives to work on more valuable tasks.
Which B2B Sales Trends Are We Seeing?
1. The Shift To Digital
B2B sales teams have already put digital transformation on their agendas. The COVID-19 epidemic, however, has made digital transformation even more crucial. Mckinsey reports that sales leaders view digital channels as being roughly twice as essential as they did a few years ago.
Personalized client journeys remain a popular topic in sales offices even with the growing significance of digital interactions, as B2B consumers demand more personalization.
Therefore, enhancing the customer experience is one of the objectives of digital transformation initiatives. Businesses can use technologies like website/campaign personalization software to offer their customers customized goods and services.
2. Data-Driven Sales Are The Result Of AI And Analytics
Even though the 2000s saw the rise of digital transformation, machine learning and artificial intelligence (AI) can further automate and enhance digitalized processes.
The need for data is growing as a result of artificial intelligence advancements and their impact on analytics. Companies are adopting analytics technologies for a variety of purposes, such as consumer intelligence and pricing optimization. Businesses are creating data-driven sales strategies for optimum conversion by leveraging these technologies.
3. Alignment Between Marketing And Sales
As lead creation techniques get better, so does the accuracy of determining quality leads. The most likely-to-buy leads should be the primary focus of sales teams. As a result, the teams in charge of marketing and sales must agree on the caliber of leads produced.
4. Hiring & Preparing Talent For Superior Sales
Mckinsey’s research on the future of B2B sales indicates that the difference between firms that grow quickly and those who grow slowly comes down to a company’s ability to recruit and develop the proper personnel. Only 22% of slow-growth organizations made major investments in sales training during the same timeframe as 48% of fast-growing companies.
5. Data Privacy Merits Honorable Mention
The GDPR and other data protection laws require businesses to handle client data with greater care. Salespeople in business-to-business transactions ought to instill trust in clients about data privacy. Businesses can safeguard consumer and corporate data by implementing AI data security solutions or privacy-enhancing technology like data masking.
What Applications Of AI Are There In B2B Sales?
Businesses can use AI in four primary categories for B2B sales:
Estimating the amount of demand
Allowing sales representatives to concentrate on the ideal customer
Set up meetings and use chatbots to handle sales activities to increase automation.
Analyzing data to have a deeper understanding of clients
You can read our post, in which we enumerated the top 15 AI use cases in sales, for other applications of AI.
Please visit our sales section to learn more about AI in sales. An informative article about lead generation can also be found here.
Remember to have a look at our list of suppliers of sales intelligence software, which can be sorted and filtered.