AI In Accounting Marketing

AI-Accounting-marketing_LI-532x266 AI In Accounting Marketing

In a recent podcast with the Association for Accounting Marketing, I shared many tips about what, how, when, and why artificial intelligence might be used in accounting firms, particularly in their marketing efforts.

Listen to the podcast here.

Below is the script from the session.

What’s the difference between AI and Machine Learning?

AI is the over-arching method of using computer programming to capture data, think analytics and algorithms. It does not inherently provide patterns and personalization unless programmed to do so. It’s just data collection.

Machine Learning is a subset of AI. which allows systems to automatically learn and improve from experience without being explicitly programmed to do so. Imagine that your website could populate different products based on an individual visitor’s purchase history without any human interaction other than what was originally programmed.

One real-world example of AI in marketing is the way some companies have replaced chat features on websites with AI bots to target different customer segments and to personalize the conversation.

AI, through ML,  holds the ability to leverage data to interpret human emotion and connection. By accurately interpreting engagement in websites, online advertising, social media, and even email, AI  can provide the path to a more personalized customer journey.

Do I Really Need AI in Marketing?

Chances are you’re probably already using AI and machine learning to buy media. The reality is, the competitive landscape has been irrevocably changed by the impact of these technologies, so the answer may be yes. A marketer is as effective as the quality and quantity of the data he/she has access to, so if keeping up with the industry depends on the ability to transform stored data into actionable intelligence, then AI is going to be a necessity.

What do I need to be prepared to answer about the investment in AI and its impact on the firm’s bottom line?

  • How do we use the technology to broaden the mouth of our marketing funnels and speak to a wider audience?
  • How do we use it to communicate more intimately with each and every prospective customer?
  • And critically, how are we going to measure its impact accurately?

What are three to five use cases for AI in accounting marketing?

In a study by the Marketing Artificial Intelligence Institute, here are some of the many use cases they’ve identified for AI in marketing.

  1. Analyzing existing online content for gaps and opportunities.
  2. Adapting audience targeting based on behavior and lookalike audiences (think Facebook, Google Ads, Instagram, etc.)
  3. Optimizing and automating the process of buying and selling digital ads thus making ad buys more efficient.
  4. Defining topics and titles for content marketing for editorial calendars.
  5. Constructing buyer personas based on needs, goals, intent, and behavior.

What are some tools available today that could help marketers immediately?

There are hundreds of tools out there, in fact at Engage in June, I’ll be sharing several of them with attendees. In the meantime, here are seven I’ve been looking at.

  1. Boomtrain, Phrasee, and Persado are some tools that AI applies to email marketing.
  2. Tools like Wordsmith, Articoolo, and Quill are already being used by the Associated Press and Forbes to create news, which leads to clicks on their websites. Using templates and fill-in-the-blanks to enter data and keywords can create unique content that gives the impression a human wrote it.
  3. Salesforce Einstein – A layer of artificial intelligence that delivers predictions and recommendations based on your unique business processes and customer data.
  4. Adext is an Audience Management as a Service (AMaaS) that uses deep, transfer and machine learning to automate the handling and optimization of your ads on platforms like Google AdWords and Facebook Ads.
  5. X.AI – An artificial intelligence personal assistant who schedules meetings for users.
  6. Answer the Public – It’s perhaps one of the best but most underutilized sources of research for content ideas. It’s great for voice search questions that you can then add to your SEO for search rankings.
  7. Facebook bot tools and other bot tools, like bot, are easy to use and budget friendly.

What steps can marketers take now to prepare for AI in their firm, even if they’ve already begun to implement it?

It’s a complex and timely process. In a nutshell, here are several steps to consider:

  1. Research and learn what AI tools mean for marketing in your firm.
  2. Identify the personnel to help you manage and deliver on the tools, including IT, legal, sales, and HR.
  3. Clearly define a use case and find an advocate.
  4. Verify that you have the data needed for implementation, including data exploration and normalization.
  5. Evaluate software and companies.
  6. Invest
  7. Implement, test, and optimize
  8. Scale, expand, and grow

I’ve heard this term, but really don’t know what it means. What is data normalization?

It’s the process of organizing data into columns and rows while reducing duplicates and eliminating data anomalies. Basically, it’s ensuring the data you’re collecting is formatted the same way, with the same field-naming conventions in all tools. For example, in all your software, the name field is first-name and last-name, two different fields using a hyphen in each field name.

What questions should I ask MarTech vendors to help vet them prior to purchase?

  • Why do I need AI to solve this problem?
  • Do I have sufficient data to use AI?
  • What type of talent or personnel can your company provide to help us understand the tech and use?
  • What are the gestation period and potential ROI from your solutions?
  • How or where will the tech touch customers and what possible negative outcomes might happen?
  • Do you have references in the accounting and finance space I may speak with?

What are some of the barriers to AI marketing?

AI sounds great, doesn’t it? As someone who loves looking at data and determining its story, AI does have its barriers to implementation, including:

  • The ability to support the large amounts of data required for it to be effective. For example, if your website does not generate enough traffic to meet the minimum requirements from your AI tool, AI marketing may be a non-starter.
  • Finding the right personnel, who understand the data, implementation, and business to implement it is tough.
  • The technology on its own is not going to boost conversions or drive sales. Savvy marketers continue to find smart ways to use AI to improve user experience and kick sales into a whole new ballpark, but by far, the most common applications are personalization and targeting.
  • Identifying where and how it can plug into our marketing strategies.
  • Costs and finding the right tools are also challenges we face.


While barriers exist, there are many different ways to implement AI incrementally to minimize risk. Consider incorporating different aspects of AI into existing marketing efforts and building large-scale projects into your marketing roadmap down the line. In the end, you may find that the increase in productivity you gain makes artificial intelligence marketing all the more attainable.