Artificial Intelligence Machine Learning

How AI and Machine Learning are changing the B2B Marketing Landscape in 2020

How AI and Machine Learning are changing the B2B Marketing landscape in 2020

Currently, the great machine learning algorithms powering AI have equipped some B2B marketers with fresh and effective insights into their enterprise. AI technology is growing at an alarming rate across all industries. Sales productivity has reduced by 12% over the past five years, and the major cause of this is the investment in sales and marketing productivity tools.

We are of the strong opinion that machine learning-based marketing solutions provide nothing but a change in the improvement of productivity. Gradually, we are getting to the future in which all interactions with technology not only in marketing will be instilled in AI.

How to make AI-Drive Sales

Theoretically, lead qualification and scoring assist the sales teams in arranging their efforts in the order of importance, successfully targeting the best leads and eliminating the worst. Practically, this process has not worked effectively.

Marketing-qualified leads (MQLs) and lead scores have been based on a few ideas and assumptions, making use of a small number of behavioral clues. The results can be anything but dependable.

The issue isn’t insufficient information, but there’s a central resource of powerful, useful data taking control over businesses’ systems and also in third-party databases. The issue is analyzing every information, hundreds or thousands of data points, in millions of various combinations. 

Examining those multitudes of connections and discovering the patterns that signal readiness to purchase is greater than the reach of our natural braids. It can’t be done by ordinary humans. But can be achieved by Infer’s AI-powered predictive software with supernatural accuracy.

AI Improves Lead Quality- Soaring and Scoring

Almost everyone is fully interested in generating lots of leads. It is the main force beyond most marketing playing towards numbers games. The more interested prospects you possess to play with, the bigger your potential for making great sales. Except the prospects are not significant to your business initially.

Aside from generating leads, another important element of B2B sales and marketing is lead scoring. In every lead generated in a month, how many of them will translate to sales?

With sufficient time and resources, the concluded goal of adequate understanding lead source quality and scoring is a more effective, automated sales process.

AI is here to engage businesses with its ability to assist B2B marketers in discovering earlier which of the prospective are possibly going to buy. When you think that the average number of people that are associated with a B2B purchase is 6.8, this is contrarily a burdensome process.

Making use of AI for the lead scoring process gives companies the power to account for behavior across various stakeholders. The predictive analysis serves as a measure between great amounts of customer data and actually what to do with it.

AI can control and track trends and patterns, making it less difficult for marketers to concentrate on relevant matters other than trying to perfectly fit a one-size-fits-all approach for all the leads that come to their ways.

AI provides useful customer insights 

Raising an efficient plus productive lead generation begins with having a foreknowledge of the customers’ preference. You want to align with their taste at every sales level, for their utmost satisfaction.

What are their pain points? What type of solution do they want? How will they explain the problems they are faced with?

AI is changing our ideas towards what a client desires with the help of machine learning. A better example is social listening combined with AI detection; it assists in accessing the specific language used across various social platforms to identify trends and common keywords.

Currently, some AI-based companies are creating software to identify voice patterns.

For people selling making use of the phone, this could assist in measuring a prospect’s level of interest to better identify where to make extra efforts around following up.

AI can help with personalization

About 57% of buyers, including B2B, rely on suppliers to expect their needs. Generic pitches won’t cut it for B2B marketing in 2020 and later on.

Truth be told, relating information to your prospective customers in such a way that it will be on time and suit their needs perfectly isn’t a big deal. Particularly with the amount of data you’re receiving.

The science of big data in B2B marketing entirely about centralization. Companies must have to move from siloed marketing and sales systems to get the best out of customer data.

They will have to collate and use machine learning to discover patterns across the entire process. This process is how freshly popularized account-based marketing (ABM) moves towards an increase.

Immediately you have teams drawing insights from a source; they can work in harmony to develop an effective targeted, personalized message, focusing on specific business needs and use cases.

A more personalized buying experience for B2B clients changes into smaller sales cycles. At an early stage, trust is established, and also, the research time is reduced, and the main concentration will be on implementation.

AI can create an enhanced buying experience

As a B2B business owner, knowing where your clients are in the sales funnel enables you to determine what strategies to utilize, and also when and where it can be utilized.

And the proof surrounding personalization is already out there in the form of increased conversion rates.

For instance, Amazon accounts 35% of its revenue with great targeted cross-sells and upsells. It’s very effective to relate with a customer as if you are together in a room, listening and translating everything you’ve heard from them into effective steps that will be carried out successfully.

AI can help nurture a customer relationship 

The major aspect of B2B marketing is customer relationship management, both before and after-sale.

Marketing teams find it difficult to reply to emails from their clients efficiently. Although increasing customer relations ordinarily by 5% can result in a 25% – 95% increase in revenue.

Although, rising AI software solutions are making it a reality for companies to have a two-way conversation without requiring the help of a real person. It will help in analyzing customer responses to identify intent and create responses that will keep conversations active.

Companies like Epson are already enjoying the rewards of this technology. They’ve experienced a customer response rate increase of 240% with a qualified lead increase of 75%.

Chatbots are another, more frequently used application of AI among B2B companies.


Other than just acquiring more data, B2B marketers are identifying the need for actionable insights. The reason has been that 2020 will be the year that marketers will focus on automation and personalization to specify where to spend their time and who to spend it on.

With the stage in which bureaucracy companies operate under and complications behind established data systems, efforts to adopt rising technologies will not be perfected across the board. I understand that Welcoming robot overlords powered by AI and machine learning into your B2B business sounds frightening.

But considering the world has got the first robot citizen, it is easier to predict that the adoption of AI and machine learning in the B2B industry will begin to speed up gradually.

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