The application of AI marketing technology
is picking up pace because of its many advantages. According to a 2020 Deloitte survey, 74%
of AI adopters agree that AI will be a part of all their enterprise applications by 2023.
What does an AI-based marketing strategy
look like, and how do you make the most of it? This article gets into the nitty-gritty of AI marketing technology
and how to implement it in ABM so you can maximize your business performance and outputs.
AI’s Role in Marketing
Thanks to its accuracy, B2C businesses use AI marketing technology
to target their customers with product or service recommendations. The following are some use cases of AI-based B2C marketing:
AI helps businesses with their 1-to-1 marketing strategies by personalizing their content to cater to every segment.
Emails informing customers of upcoming sales, special access, or exciting offers are sent out via AI technology. Weekend offer emailers, special discount codes, and new product updates are a result of event communication automation so that customers can be informed before time about upcoming events.
Trending topics, investments, event promotions, webinars, customer feedback, product availability, bestselling combo, weather reports, and new blog post updates are provided in real-time to maintain an active connection with customers.
Businesses do this by using the ‘open time content’ AI technology. Manually executing 1-to-1 marketing strategies is nearly impossible, impractical, and does not see much success. AI helps streamline these strategies and executes them effortlessly.
What Goes into Creating an Effective ABM Strategy?
For an ABM strategy to work, businesses need to follow these steps:
Preparing for the ABM Strategy
Organizational readiness is crucial for implementing ABM. Make sure you have a budget and an achievable timeline to execute the strategy, team members who can anchor it, and an understanding of ABM metrics so you can make the most of it.
Synergy Between Marketing and Sales Teams
Your sales and marketing teams should be in sync and not at loggerheads due to account-level communication issues. Discussing the benefits of ABM with both the teams beforehand and coming to a strategic agreement to implement ABM can help them align their goals while executing the ABM strategy.
Identifying Target Segments
Your ABM strategy can do wonders for your business only if you have a precise segmentation of data. Use dimensions like business size, annual revenue, current spending, projected spending, targeted products, geography, open opportunities, closed opportunities, etc., to identify your target segments.
Zeroing-in on a Priority
Having a clear priority helps you streamline your ABM strategy. It should either be acquisition (acquiring new accounts), retention (retaining existing accounts), or expansion (expanding the scope of accounts). Without a clear priority, any ABM strategy may not yield expected results because the efforts won’t be concentrated towards a single goal.
Leveraging AI in ABM Strategy
In an interview
with Media 7, Daniel Englebretson, founder of Khronos, spoke about AI’s impact on the future of ABM.
“From my perspective, B2B marketers have faced countless challenges that have formed the basis of new technology – problem brings a solution. I expect AI will solve identity resolution, resolve data challenges, and enhance targeting. I expect AI will address 1:1 content at scale, unlocking the rapid deployment of 1:1 brand experiences.”
Introducing AI into your ABM strategy can help you in the following way:
Once you know your customer’s pain points and interests, you can focus on providing them personalized solutions, products, or services they desire. Of course, personalizing content is complex, but AI makes it easier by offering the technological capacity to deliver what your customer wants.
Efficient Resource Management
Without customer profiling, an ABM strategy cannot achieve the expected output. AI can assist with data crawling the internet to find out important customer information. Also, it segments data acquired from CRM, which gives you more information about a customer than any other generic data. This data is helpful for lead qualification and creating heavily personalized content for a customer.
Since AI does all the heavy lifting, you can allocate your resources to building and nurturing a relationship with the customer.
in ABM generates automated insights for lead generation. It also highlights campaign performance related to specific, high-value accounts and suggests steps to engage a prospect.
Digital marketing and automation
are a dynamic duo where AI brings about intelligent marketing automation. Efficient email campaigns are run when executed by automation. Email marketing companies like MailChimp target customers based on insights to achieve more conversions. When AI and big data use CRM data, large chunks of user information can be collected from different platforms. This information can help with formulating a successful ABM strategy.
ABM Optimization and Predictive Insights
To analyze intent, AI processes data in real-time and gives predictive insights to help with ABM optimization. As a result, it is easier to merge data from different sources with AI-enabled tools, achieve predictive analysis, manage recommendations in real-time, and understand competitor strategies through social media. AI can also interpret images correctly.
Use AI for building a strong relationship with your customer. Personalizing communication by using customer data can be easily achieved with AI.
What Is the Future of AI-enabled ABM Strategy?
ABM, with an AI marketing strategy
, has a bright future ahead of it. Demandbase recently conducted a survey in which they found that 80% of marketers had plans to integrate AI into their ABM marketing strategy. Another survey conducted by MarketingProfs concluded that businesses that used AI in their ABM strategies had 59% higher closing rates as compared to others. They saw a 58% increase in their revenue and a 52% increase in their conversions.
Ways Salesforce's AI Einstein Aided U.S. Bank in Growing Revenue
The U.S. bank used Salesforce’s sales cloud AI, Einstein, to boost their revenue. Their lead conversion rate increased 2.35 times after implementing Einstein. They were able to create a model to predict lead conversion. They did this by using Einstein to search through customized historical lead data.
“We work to build high-quality, personalized relationships between our customers and their financial advisors or commercial bankers. There is nothing that replaces that person-to-person interaction. What AI allows us to do is augment that relationship. We can provide our teams with better data and smarter insights, which helps them establish stronger relationships.”
– Srini Nallasivan, Chief Analytics Officer, U.S. Bank
Summing It Up
AI-based marketing can enhance your ABM strategy only if qualitative data is available. Therefore, businesses will need to have clear marketing goals and turn data into an asset.
What are the challenges in the AI-based ABM strategy?
Managing, protecting, and enriching data obtained from CRM and other customer support systems can be challenging.
How can AI help in strengthening your ABM strategy?
AI helps with personalizing content, automation, ABM optimization, and providing predictive insights for lead conversion.
What does a strong AI-based ABM strategy do for your business?
A strong AI-based ABM strategy helps with account profiling, analytics, reporting and hyper-individualized content, which leads to increased lead conversion.