“Tell me what I want to buy (watch, listen to), so I can buy it.” This idea drives a large part of digital marketing today. Customers want a personalized experience wherever they are, and companies from Facebook to Netflix to Amazon have been more than happy to oblige.
But it’s more than just product and service recommendations that consumers want personalized. They also want 24/7 contact with their providers for resolving everything from billing issues to technical problems. Personalization needs to be an end-to-end service throughout a customer’s experience with your brand.
B2B customers, it turns out, are no different. This really should not be surprising — business customers are just ordinary consumers in a different environment. So how should businesses leverage the desire for personalization to build their B2B sales pipeline?
Artificial intelligence (AI) and machine learning (ML) can help businesses take the masses of data they have about existing and potential customers and turn it into actionable business intelligence. Augmented analytics can improve every aspect of the sales cycle, from lead generation to lead conversion to post-sales support.
Getting Started with AI-Augmented B2B Marketing
Before digging into the mechanics of implementing AI and ML in your marketing efforts, you need to define what you are trying to achieve. Analyzing data just because you have it is not an effective approach to marketing.
LinkedIn’s VP of Artificial Intelligence, Deepak Agarwal, emphasizes the importance of specific goals for AI use in B2B marketing: “In our experience, machine learning can deliver the greatest value when you can clearly define an objective that you are trying to optimize around – and you can design a mechanism to collect data at scale that gives you valuable information around that objective.”
So before going further, ask yourself what you are trying to accomplish. Are you trying to build your customer pipeline? Increase sales conversion rates? Improve retention of existing customers? Answering these questions will guide the rest of your decisions, including what sources of data you use and what models you will apply in your data analytics.
Tracking your goals and ROI is also essential. Rely on AI-based financial software that comes with features such as project tracking and custom reporting for real-time analysis of whether you are meeting your goals. This will also help you to more effectively keep tabs on cash flow trends and the overall financial health of your business.
What Can You Achieve with AI-Augmented B2B Marketing?
Having set your goals (preferably SMART goals), you can then assess where AI and ML can best augment your existing efforts.
Providing effective recommendations
While personalized recommendations are perhaps the most obvious use of AI in B2B marketing, their importance should not be ignored. Targeted, customized marketing can drive traffic to your sites, and more importantly, drive the conversion of prospects who reach your sites.
It might be informative content that helps your customer understand why your products or services will help them, or it might be attention-grabbing ads that address specific needs identified by your data analytics. Personalizing the buying experience builds a stronger bond between you and your customer.
Building a better sales pipeline
Building a solid sales funnel is a fundamental activity for B2B marketers. Part of that effort is defining who you think your ideal customers are, who your traditional customers are and how the two differ. With AI, you can turn your customer data into detailed buyer personas that give you insight on how to best target prospective customers and new markets. You can also use AI for predictive analysis of future market trends.
Considering that businesses often pay $100 or more per lead alone, investments in lead generation systems driven by AI can quickly recover their costs. Couple augmented lead generation with a deeper understanding of market forces, and you can build highly effective targeted marketing campaigns.
Automating content creation and SEO
Any online business with a presence on the web or social media should understand the importance of SEO. This should be one of your top priorities when starting a new online store or business; after all, how can customers buy from you if they can’t find you? But for many, the process of content creation (whether advertising or informative posts) is overly time-consuming. And many businesses still are not terribly good at SEO.
Fortunately, AI and ML have helped to create very effective content generation and SEO automation tools. With features ranging from building blog posts to generating SEO keywords to automated ad tagging, these tools allow your marketing team to focus their time on time with customers rather than on tedious, time-consuming background tasks.
Better responding to your competition
With AI, you can also obtain a greater understanding of what your competitors are doing that is particularly effective and make more informed decisions about what you should be doing to compete more effectively. And importantly, you can do it with real-time data analytics so that your decisions are more timely and don’t risk missing market trends.
Do you need to alter the features of a product? Do you need to change your pricing strategy? What are your customers looking for from you? Using AI in your data analytics can help you answer these and many more questions.
Keeping customers happy
Keeping existing customers satisfied is just as important as creating new customers. Being able to quickly respond to customers when they have a question or a problem is crucial to customer retention. And, AI has its place in your customer interactions.
AI is being used effectively for customer communication through an ever-growing number of chatbots and AI-augmented help systems. With these systems, you can provide 24/7 access to your customers, and you can frequently deal with many of their issues without the need for human intervention. Even if your customer eventually needs to talk to an actual person during business hours, they will know that you made efforts to address their needs at the most crucial times.
Of course, post-sales support is not the only customer retention issue. Future sales to your existing customers are also one of the most important considerations for your company’s continued success. Use AI to mine your data and determine what your customers want from you going forward.
Issues to Keep in Mind
In building the most robust and effective AI-augmented marketing campaigns, it is important to remember that AI does have some limitations.
One of the most common concerns about AI is the inadvertent insertion of bias into the analytical models. Your marketing team must be aware of the potential for bias and structure their models accordingly. Having diverse marketing and AI implementation teams is one excellent way to minimize unintentional bias.
The good news is that your marketing team can use AI itself to help minimize bias. Your market researchers can use AI to improve the quality of data used in your marketing efforts and remove observer bias from your data analytics.
Data privacy is also a significant concern. Make sure that your data collection efforts are all compliant with any data privacy laws in your jurisdiction and that you have appropriate security protections in place for your customer data.
Perhaps most importantly, AI should never become a substitute for human interaction. AI has not reached the level of reflecting emotions or empathy. Even should it ever reach that point, most people still appreciate human contact. So use AI to improve your marketing efforts, but don’t let it take over your campaigns.
It is past time for B2B marketers to start applying marketing tools that the B2C world has used quite effectively to its advantage in recent years. Particularly given the mountains of data available to businesses, there is every reason to use that data to build customer bases, drive sales and improve customer retention. AI and ML are some of the most effective tools for turning extensive, diverse data into marketing campaigns that generate customers and sales.
Nahla Davies is from Brooklyn, New York. Since 2015, she has worked with enterprise clients around the world developing RegTech protocols and best practices. She shares her insights at nahlawrites.com.