5 Easy Tips for Implementing AI into Your Marketing Mix

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By Michael Rodriguez
Republished with permission from Demand Gen Report

The B2B industry has seen an influx of AI solutions and programs that promise to streamline processes and marketing strategies. While AI has been helpful, there has been a lot of confusion around what it does, how to choose the best AI solution to implement for success.

I recently had the opportunity to sit down with Seth Earley, CEO of Earley Information Science, to discuss his new book “The AI-Powered Enterprise: Harness the Power of Ontologies to Make Your Business Smarter, Faster, and More Profitable” and how to optimal use of AI in B2B.

Earley provided some insights that I found to be helpful for marketers looking to implement an AI solution, including:

  • The importance of training your AI solution;
  • The impact friction has on marketing and implementing an AI;
  • How AI can improve your ABM data and optimize your strategy;
  • How to improve processes through AI implementation; and
  • How to find the best-fit AI for your business?

Construct an Ontology to Train AI

When implementing an AI solution, a business needs to make sure that the AI has a database it can pull from.

Earley explained that constructing an ontology is a great way to remove potential roadblocks to the AI’s implementation. An ontology organizes all business information into hierarchical categories, allowing AI solutions to prioritize content data, product metadata and account data by relevance, association, etc. With access to a business’ ontologies, the AI can operate independently to maintain business operations/processes.

Ontologies also function as a translator, according to Earley, with AI solutions using the business’ stored information to help buyers find the exact information buyers are searching for. AI solutions use ontologies to taking buyer input, such as key term searches, and run them through the business’ database, providing the exact product or information the buyer wants even without them explicitly stating it.

“The ontology really is the key to defining all of that data and defining all of that information,” Earley explained. “It becomes a reference point because AI doesn’t know what products you have, it doesn’t know what your solutions are. It doesn’t know what’s important to your customers.”

For AI to properly utilize the structured data and predictive analytics in their ontologies, Earley stated that businesses need to train the AI solutions they implement. The AI’s functionality hinges on cognitive programming, which trains the AI to create skills that track a buyer’s previous transactions or the platform’s purchasing trends.

“You have to tell the AI what’s important,” said Earley. “You have to tell it the names of your solutions, and your products because without that, it just doesn’t know.”

Avoid Friction That Hampers AI Implementation

Much like communication issues with real sales reps and marketers, AI implementation can also be hampered by friction.

When marketing an AI solution, friction from manual processes slows down the organization’s ability to market its product, creating inefficiencies in its marketing strategies. The workflow is disrupted by miscommunication, missing or non-existent data or contacts, scheduling conflicts and more. It can easily be remedied by establishing a process and automating it.

“What happens if you don’t have a process?” Earley asked. “Then it’s the Wild West. People and different groups will do whatever they want. They won’t use the same terminology. They won’t use the same article. That compounds problems, fragments the customer experience, causes higher costs inefficiencies, and really detracts from the company’s brand value.”

AI can streamline internal operations flow, automating the outreach, fact-checking and data-compiling processes to allow marketers and sales reps to focus on lead generation and follow-up. Businesses can also optimize their customer lifecycle maps by using AI solutions to measure the functionality and success of the overall marketing strategy.

“It’s intentional decision making around the tools that we have, the technologies, the investments, the changes,” Earley commented. “When we have a much more intentional process for not only choosing the tools — but evaluating, managing, configuring them and optimizing them — that’s going to pay huge dividends across the organization by improving lots of processes.”

Reevaluate AI with ABM Data

Account-based marketing focuses on identifying target accounts based on intent data, highlighting common characteristics among accounts in order to create successful ABM plays.

By implementing AI, the existing data can be summarized and analyzed more efficiently, helping marketers prioritize account intent data and assist in account targeting, according to Earley. AI solutions bolster a business’ knowledge of its accounts and potentially uncover correlations among target accounts or hidden characteristics in the market.

“Many times, AI tools can uncover those hidden characteristics or hidden attributes,” said Earley. “It can make more sophisticated correlations and provide recommendations about buyers. It can help in terms of targeting. It can also help in terms of prioritizing who is likely to buy in those organizations in terms of roles and in terms of segments and so on.”

Marketers can optimize their strategies based on the new information and focus on how to reach higher-value targets, improving their ability to penetrate the market while implementing an AI.

Make AI the Sales Rep

Implementing an AI solution can help marketers get the jump on buyer expectations and needs. They can optimize the buyer’s journey by anticipating their questions using prior sales data and predictive analytics.

Earley added that AI can track a buyer’s preferences, take them into account for later purchases and provide product recommendations to help guide buyer intent in the present or future buyer’s journey.

“We want to be able to understand that customer to such a great degree that we can create offers, anticipate their needs and give them things that they don’t even know that they need at that time,” Earley added. “It’s anticipating what they need, surfacing and personalizing information based on their digital body language.”

Choose Your Ideal AI

Earley acknowledges that marketing technology has significantly grown, and the number of AI solutions currently on the market are plentiful.

When searching for an AI solution that best fits your needs, Earley suggests a little self-reflection. Ask yourselves some basic marketing questions, such as:

  • What business problem do I want to solve?
  • What friction points exist that I want to correct?
  • Where can I do a better job engaging the customer/market?

These questions allow marketers to map out their needs and find and implement an AI solution to solve them. This can be anything from fix sales challenges, to compiling data or and streamlining processes.

“You can’t automate something you don’t understand,” Earley stated. “You can’t automate a mess. Get clear about the process, about the business objective, about the very specific piece that you’re going to improve, and then test out tools that will support that piece of the process.”

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