Implementing Artificial Intelligence plus Machine Learning means Scaling B2B Sales

In our world everywhere you go or whatever you do there is a digital interaction which causes endless data to accumulate. This data can be used to increase sales and to improve personalized

marketing and services that are expected by today’s customers. To translate this data into sales growth you need to use Artificial Intelligence (AI).

AI is based on the concept of having computers think like humans including performing tasks like rationalizing, designing, learning and understanding language. The logic behind AI is machine learning technology, which is aimed to make our life easier and more productive.

Machine learning is a subcategory of AI focusing on using statistical tools to create intelligent computer systems to deduct from big databases using algorithms adapted to the data creating behaviors with minimal programming. This technology anticipates expected behaviors of B2B and B2C customers so businesses can be proactive and use CRM system more effectively.

57% of buyers (B2B included) depend on suppliers to foresee their needs. Customers know you have their personal data from their purchase history and they expect you to use it in order to help them to make current purchase decision easier for them and even offer them the products that fit their needs the most. They expect every interaction along the purchase process to be fast, smooth, clever and personalized.

The same principle works for B2B sales process. Most complex B2B deals take months or years to close since they include many human interactions like Q&A, issues, solutions and forecasting plans. It’s expected that even post Covid-19 pandemic this process will remain virtual and digital. By personalized approach closing deals process may be shortened.

Customers are engaging at specific times and for specific reasons along the buyer journey. However, usually a CRM measures the progress of a deal through stages, but the level of engagement happening, the content generated and shared by the buyer is not often tracked at all. This information is critical for the identification which leads have better chances to be converted into a customer. Implementing AI and machine learning is expected to take B2B companies’ sales process a big step forward, enabling businesses to scale their efforts, measure more efficiently, and close more deals.

To make the best out of AI you need a team of professional data scientists and developers that access the suitable data, arrange it in the correct way, develop the right models and at the end incorporate the personalized estimates and convert them into the CRM system to provide the optimal end-user experience.

What is the impact of using AI on B2B sales?

B2B S&M departments were early adopters of digital transformation which helped them to personalize their engagements with customers which is very important especially with their longer sales cycles. According to McKinsey research, B2B sales teams that adopted new technology tools to improve sales models show growing revenues at twice the rate of GDP. According to the research, data-driven decision making adds a 2%-5% rise in sales.

AI helps B2B marketing team to focus on the most valuable leads. AI tools facilitate the flow of marketing information to sales, saving precious time by helping sales teams find out who to contact and when. AI helps identifying which of the potential lead actions are indicators of the buyer intent, marking the correct time to approach the potential customer.

Maximizing B2B marketing ROI

AI can handle a high volume and low variety of tasks. Most AI solutions available for B2C marketing are optimized to do this at the lowest cost possible. This explains why most B2C marketers are able to present positive ROI on the investment in marketing automation technology. However, it’s not the same for B2B marketers as B2B and B2C marketing are different.

B2B marketing presents a few challenges that are exclusive to this arena. To overcome these challenges, B2B organizations utilizing ABM (Account Based Marketing) which is a marketing strategy that is based on choosing a few specific target accounts and applying highly personalized marketing strategy for each account. This strategy is effective for companies that sell big products and services. ABM reduces the sales cycle and increases the conversion rate.

How Application of AI affects B2B Marketing?

• High qualification leads – AI tools are able to analyze and assess leads’ purchasing intent by analyzing large volumes of data pertaining to an account such as social media activity, search key words and market trends. In B2B business this capability can differentiate between sales cycles of a few months to one that lasts several years.
• Super personalization – AI based ABM tools can help marketers to personalize marketing strategy even within accounts to different stakeholders in the same potential company based on demographic, firmographic and behavioral data. This high distinguished marketing personalization enables S&M team to create personal relationships with many stakeholders which translates into faster conversions.
• Multichannel Integration – By using AI-based ABM you ensure that every interaction with potential customer will be “aware” of all past interactions with the same lead which makes this interaction improved and more likely to end in conversion.
• Campaigns performance – AI based ABM can follow marketing campaigns performance enabling cost optimization of advertising budget.