How Accounting Marketers Can Leverage AI and ML

Even though artificial intelligence (AI) in its purest sense has been around since the 1950’s, machine learning (ML), the aspect we are all investigating today, is still rather new.

As accounting marketers, there are many ways we can take advantage of AI and ML in our day-to-day tasks, as well as in our strategic planning and processes.

For starters, does my firm really need AI/ML in its marketing efforts?

Chances are you’re probably already using ML to buy media. Remember, a marketer is only 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 and ML are going to be a necessity.

What are some use cases where I could implement ML into our processes?

There are a seven tasks where you could leverage this technology, and in some cases outside of an enterprise/firmwide tool, such as:

1. Creating and generating content;
2. Content curation and personalization;
3. Email marketing;
4. Digital advertising;
5. Searches;
6. Web design; and
7. Chatbots

I’ve heard of data normalization, but don’t know what it means. And, is it really necessary?

Data normalization is 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.

It’s necessary for a couple reasons. First, to ensure the data your collecting and inputting into the tools has the same data structure, e.g., phone numbers are formatted the same way across all data source’s phone number fields. Second, when validating the information, the sorting tool is able to identify duplicates, incorrectly formatted fields, spam, and junk content.

What type of metrics can I measure with AI that I may not be able to pin point now?

Data tools are great at helping marketers pinpoint growth patterns, missed opportunities, and potential trends. Here are several things you can measure with a variety of tools, including:

• Sales revenue;
• Cost per lead;
• Customer lifetime value;
• Inbound marketing ROI;
• Traffic-to-Lead ratio;
• Lead-to-Customer ratio;
• Landing page conversion rate;
• Organic traffic;
• Social media traffic; and/or
• Mobile traffic, leads, and conversion rates.

If you’re already monitoring your website or social media analytics some of those metrics will be familiar. That’s because Google, Bing, and many popular social media platforms and tools have been using AI and ML for several years.

What questions should I be asking vendors as we consider an AI or ML tool?

If you haven’t engaged your tech team before, now’s the time. Use their expertise to help you vet vendors and to help determine what will and will not work with the firm’s existing systems.

Here are some questions to add to your vendor vetting list to help weed out any fly-by-night contenders.

• 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 is 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?

There are many more questions I’m sure you have. You may get more answer by listening to the March AAM podcast “AI in Accounting Marketing.”

By: Becky Livingston, President and CEO of Penheel Marketing 

2019 AAM Summit Pre-Conference Post 

Becky will present on this topic at the 2019 AAM Summit in the session “Rise of the AI Marketing Machine – Driving Growth in Accounting Firms,” on June 12.