Introduction AI in Account Based Marketing
With everything you know about Artificial intelligence now, the image of sentient machines taking over the world and ruling humanity is probably not what comes to mind whenever the subject of AI comes up. You also probably know that its applications are quite simple, and in the things around us such as: entertainment (Netflix), or internet searches (google assistant, Siri), shopping (Amazon, Alibaba), etcetera. Such b2c companies use AI to simplify their operations and make more accurate product recommendations.
Others like IBM, are pushing AI’s limits further with initiatives like project debater, an AI system that debates humans on topics. But a more practical application for AI in b2b is in marketing. According to Gartner, by 2020, most enterprises will not require humans to form relationships with their customers but will instead rely on AI. Coupled with efficient marketing practices such as Account Based Marketing (ABM), AI can eliminate process and people redundancy and lead to more efficient workflows.
In this article, we will discuss what it means to introduce AI into Account Based Marketing, and dive deeper into how AI can improve the characteristics that ABM is known for, namely:
- Timely communication
- Account-based research
- Holistic sales and marketing lead generation approach
- Better program implementation
Artificial Intelligence in Account Based Marketing
Below are areas of ABM that benefits greatly from the power of AI:
Account Profiling and Lead Generation
Profiling customers is a key step in ABM implementation. Before you interact with an account (or customer), it is important to know and define them. With the power of AI, you can crawl the internet and multiple data bases to find information that’s useful for customer profiling.
This way, you can allocate the most important resources to nurturing and building a relationship with those accounts and eventually close them.
Additionally, with AI, you can further segment data mined from CRM platforms instead of the generic fields that the data comes with. This helps with better lead qualification and allows you to create hyper-individualized experiences.
Creating Personalized Content
Knowing and understanding your buyers’ pain points and interests is the first step necessary for understanding and providing the kind of personalized experience that customers want.
Once you have clear customer profiles, you can create content that directly represents individual user interests. Personalized content is key for your account-based marketing strategy to succeed. Not only do you need to personalize blog articles, but also email and ad copy. Personalization can introduce complexity in your marketing efforts, which is in fact why 59% of b2b marketers don’t personalize. AI solves this problem by providing you the technological capability necessary to deliver what clients want.
Smart Email Marketing
Digital marketing cannot be accomplished without automation. Now, AI can make your automation even more intelligent. You probably use examples of this daily. For instance, whenever you receive an email, you get pre-drafted replies that you can send instead of having to type a response. If you have hundreds of emails to go through daily, or if you need to reply to email on the go, such a capability saves time and improves your email response time. Research shows that the odds of contacting and qualifying a lead decreases by more than 10 times just 1 hour after receiving an email.
Email campaigns cannot run efficiently without the necessary tools for optimizing the process. Mailchimp is an example of an email marketing tool that has AI capabilities. Other great examples include Automizy, Adobe, Wylei, among others. If you are looking for ways to generate leads with dynamic emails, try out some of these tools.
Analytics & Reporting
The main thinking behind account-based marketing is that marketing needs to move from lead generation programs that are volume-based, to individually-targeted marketing. this process can only be made possible by the utilization of large amounts of structured and unstructured data, both at company and individual level.
For instance, purchase-intent data provides insight into buyer behavior that highlight their present and future needs. When you infuse such insights into your marketing strategy, this will result in more targeted ads and content, hence better conversion rates.
But for intent data to have such benefits, it must be collected and analyzed in real time. Such analysis must also be predictive. AI is how you introduce the predictive insights from your data and achieve ABM optimization.
With AI enabled tools, you can
- Merge data from disparate sources and thereby eliminate data silos and its associated complications.
- Move from simple reporting and descriptive analytics, to predictive analytics.
- Analyze social media data of your competitors to gain insights into their strategies.
- Interpret unstructured data such as images
- Conduct real-time tweaking of recommendations, to ensure that your leads are getting what is relevant to them and are not being targeted with irrelevant offers.
Tools like Sales-Force Einstein, Unmetric, dynamic yield, among others, are very good at doing most of these tasks and can be a great way to improve your account-based marketing.
Creating Trust and Building Relationships
Whereas marketing automation creates efficiency, it doesn’t account for truly knowing your buyers. AI is the missing element that introduces relationship-building into marketing. With AI, you can build intimacy between your brand and your customers. AI can accommodate a limitless number of rules (10 billion) to ensure that you create the best possible personalization. Human beings cannot process such a large volume of rules but with artificial intelligence systems, you can.
The Future of AI in Account Based Marketing
Account Based marketing was first introduced in the business world in 2004. But only recently did B2B marketers start to take note of its importance and adopt it into their marketing strategy. ITSMA research findings show that 50% of ABM programs are under one year old and that only 17% have been in effect for more than three years. They however predict that as ABM has proved to be effective (with double digit ROI in around 50% of instances implemented), its increased adoption is expected.
For instance, in a recent survey by Demandbase, 80% of the participants said that they are currently implementing or have plans to use AI for marketing or sales purposes. Those who have implemented AI say that they hope to reap its benefits within 1 to 2 years.
However, although there is great optimism for AI use in marketing, there are barriers to its adoption, top among them: budget constraints, lack of skills and not knowing where to start. These barriers are worth considering as you plan to implement AI into account-based marketing.
Although AI is still a new area, you can still harness its capabilities to exploit the insights within your data, and thereby open more revenue generation opportunities. MarketingProfs conducted a survey and tracked increased performance across key performance metrics among businesses that implement AI in ABM:
- 59% higher closing rates
- 58% higher increase in revenue
- 52% more conversions
- 54% increase in traffic and engagement
That said, it’s worth noting that if your customers don’t trust what your AI systems are doing, it might be difficult to move your account-based marketing to the next level. As such, only adopt and use AI powered systems that are trustworthy and that tell your prospects or leads why they (the AI systems), are doing something. Good AI should also allow for feedback from its users.
To promote trust, your AI solutions have to fit into your audience’s daily lives, the role played by the solution should be clear, and they also have to be easy to use. For instance, the algorithms used by Netflix or Amazon.