Maximizing B2B Marketing ROI With AI and Machine Learning

The use of AI in B2B marketing can help businesses identify their ideal prospects, convert them into leads, and seamlessly guide them through the sales funnel in a more expedited and efficient manner than is allowed by traditional processes.

AI has already become an integral part of modern-day marketing. However, the greatest leaps of AI in marketing have been largely limited to Business-To-Consumer (B2C) operations. That’s because AI’s basic ability to automate repetitive tasks has found many applications in B2C endeavors, where scale is the biggest challenge.

Be it automated mass emailer distribution or chatbot-based customer service, the uses of AI are largely dependent on its ability to handle a high volume and fairly low variety of tasks. Most solutions available for B2C marketing are optimized to do this at the lowest cost possible. As a result, most B2C marketers are able to justify their investment in marketing automation technology. However, the same cannot be said for Business-to-Business (B2B) marketers. While the essential elements remain the same, B2B marketing is not the same as B2C marketing. And so, what may work for B2C marketing may not necessarily work for B2B. This includes the use of AI in B2B marketing. That’s because B2B marketing presents a few challenges that are unique to this field. To overcome these challenges, businesses are now adopting a more targeted way of generating leads and sales in a B2B context—Account-based Marketing (ABM).

Account-based Marketing for B2B Growth

Account-based marketing put simply, is a marketing strategy that involves selecting a specific number of target accounts (organizations) and treating them as individual markets to apply highly personalized marketing and sales strategies for each account. This is an especially effective strategy for companies that sell big-ticket products and services. As a result, while the effort and resources invested per target account may be higher than those for typical B2B strategies, ABM shortens the sales cycle and increases the conversion rate. However, ABM comes with its fair share of challenges too.

Challenges in Account-based B2B Marketing

B2B marketing, in general, is complex and challenging. Account-based B2B marketing initiatives—tech-driven or otherwise—often come up against an extra layer of complexity for the following reasons:

The Narrow Target Audience Base

B2B marketing efforts, more often than not, are targeted towards hyper-niche markets. For B2B vendors, the target market may comprise a few hundred or, at most, a few thousand customers (companies). Due to its all-or-nothing approach towards identified leads, ABM must only be applied to leads that can be easily converted and can justify the heavy marketing investment. And identifying such accounts from among the deluge of businesses that crowd every industry today is harder than finding a needle in a haystack.

Need for Deeper Personalization

When you sell to an individual customer, you’re often selling to a single person. Even at this scale, personalization can be quite challenging. Now, when you sell to an enterprise, you are selling to the CEO, the CFO, the procurement department and a host of other stakeholders—all at the same time. Each of these stakeholders has different motivations and needs for making a purchase in any product category. You can imagine how difficult it will be if you want to customize your communications for every stakeholder involved. When you want to sell a product or service to an organization, your marketing efforts need to address every stakeholder’s needs. And typical marketing automation tools won’t be of much help in this scenario, as they do little more than basic pencil-pushing. And although they can be used for B2B marketing, it would still require a lot of manual effort for execution. For instance, you may still need manual effort to identify the different members within the account you are targeting and then design and distribute communications for each individual. Since most non-intelligent automation tools offer little scope for extensive personalization, you cannot get the kind of functionality you need to cater to B2B targets. By using such tools, you end up missing out on deeper personalization opportunities. Consequently, you end up with substandard results, and therefore, lose out in terms of ROI.

High Variability in Customer Touchpoints

Another challenge to account-based marketing is the fact that the strategy involves using an omnichannel mode of communication. And just to be clear, omnichannel isn’t the same as multichannel. While a lot of businesses may have a multichannel outreach strategy, they do not unify these channels and their data for cohesiveness in marketing. So, your email customer support may not know what your social media support team is up to—even when they are handling the same customer. Your chatbot may not know that the customer it is dealing with has had previous interactions with your representatives at a recent trade show. Bridging the gap between these siloed channels and giving all the members in your target accounts a seamless experience is something traditional marketing automation tools cannot do. Bringing these channels together and then orchestrating communication activities optimized for every interaction is a task that is simply too much to expect of most off-the-shelf marketing solutions. These are just the two of the biggest challenges to executing effective ABM strategies. You’ll notice that the challenges arise from the presence of a large number of variables that need to be analyzed and acted on. This is where advanced tools powered by AI can be real game-changers.

Applications of AI in B2B Marketing

To derive true value from AI in B2B marketing, businesses can leverage the technology in the key challenge areas of account-based marketing.

Lead Qualification

In B2B sales, a marketer’s ability to distinguish a hot lead from a lukewarm one can be the difference between a sales cycle that lasts a few months and one that lasts multiple years. This is where analyzing the intent of your leads can be of great value. Knowing leads’ intent requires you to analyze large volumes of data pertaining to an account such as social media activity, search keywords and market trends, among others. Artificial intelligence can be used to do all the heavy lifting to analyze this data and assess the intent of leads. Specialized AI tools can analyze intent data to help B2B marketers identify the accounts most likely to convert at any given time. Such insights can help marketing teams to prioritize target accounts for intense outreach campaigns and lead to faster conversions.

Content Personalization

The role of personalization and targeting in marketing is unquestionable. Only the marketers that understand their target groups the most are able to craft sales- and profit-generating campaigns. But even the most accomplished marketer will tell you how difficult it is to personalize without investing nearly unjustifiable amounts on tools for analytics and marketing automation. And this problem is amplified manifold when it comes to B2B and ABM. AI-based ABM tools can help you plan and execute highly personalized marketing strategies for every account. Even within accounts, you can identify key people and provide them with personalized content based on their demographic, firmographic and behavioral data. As a result, your sales team can build relationships with multiple stakeholders within the target account and make conversions faster and frictionless.

Multichannel Integration

As mentioned above, the segregation of channels of communication and data collection is a major challenge in ABM. By using an AI-based ABM tool, you can make sure that all your past interactions with your customers inform all your future ones. For instance, every time your chatbot interacts with a lead, it will be already informed of all the previous interactions with them. Using machine learning, the chatbot can improve its communication with the lead, offering them a satisfying experience every time. Sales teams can use such insights to turn every customer interaction—regardless of channel— into a step towards conversion.

Additionally, the use of AI in B2B marketing and ABM can also help in tracking the performance of all marketing campaigns to optimize costs. AI-driven analytics can help them manage their marketing and advertising budgets to generate further ROI on campaigns.

The most effective way of implementing AI-based ABM for every B2B organization will differ and largely depend on how the sales funnel is structured for that industry. This means that the business requirements for their AI-based ABM tools must be customized to cater to their specific needs, requiring heavy upfront investment. However, while AI-based B2B sales and marketing tools may require heavy investment upfront, they can easily justify their costs if implemented the right way.