Artificial intelligence has flipped the consumer buyer’s journey on its head. It creates hyper-personalized recommendations based on vast amounts of data, meaning each consumer has a journey tailored to their needs, knowledge level, and preferences. It’s incredibly effective and enables better B2C marketing than we’ve ever seen.
Savvy B2B marketers are starting to follow suit, recognizing the need for this level of personalization in the B2B space. There are a few reasons for this.
First of all, B2B buyers are in control of the information they consume. Nearly 7 in 10 B2B buyers prefer to independently gather information online before making a purchase. In fact, only 17% of their buying time is spent meeting with potential vendors, according to Gartner. It’s clear: Buyers are running the show.
Additionally, B2B marketers generally lack the precious data that enables them to create a frictionless buying experience. They need deeper insights about their audience so they can stop forcing buyers down a journey where the recommended content offerings and concurrent steps aren’t really needed or wanted.
The good news is, artificial intelligence can solve for this.
But after you’ve vetted vendors and are ready to implement a solution, you need to have a few things in place to really see value from implementing AI.
When you’re evaluating AI solutions for your B2B marketing practices, start by determining the parts of the journey that could benefit from intelligent automation. Determine the questions you’d like AI to answer, or the problems you’d like it to solve.
And then, take a step back and look at your data.
How much proprietary data do you have? How many custom data points can you provide to train the AI solution? And what is the quality of that data? Depending on the tools you choose, this factor could make or break your results.
Once you have a strong sense of the exact tasks AI will handle for you, the challenges it could solve for, and a realistic idea of the data you’ll have to use, you’re ready to vet vendors, choose a solution and pilot the project.
The piloting phase is exciting, but can be a little stressful—or even disappointing. But that’s all part of the process in this digital transformation.
First of all, for the best outcome, the entire B2B marketing team should be involved in pilot projects. Learning and adopting AI requires education and interactive training, and is an opportunity to foster enthusiasm around the idea, as opposed to fear.
Also, C-suite support is crucial. The truth is, early failures are a very real possibility when piloting AI. The first few projects may not produce the results you hoped for, but that can’t be the reason you stop trying.
AI is an investment in transformative B2B marketing, and executive-level understanding of AI is critical to continuous improvement as you determine the best way to move forward. Ultimately, you will see a strong ROI with AI adoption—but saying exactly how or when is difficult from the start.
AI has the capacity to enable B2B buyers to make informed, enthusiastic purchasing decisions. But if you don’t do some careful planning, level-setting, and team-wide education in the evaluation and piloting stages, you may not be giving your organization a fair shot at AI success.
To see an AI solution for B2B audiences, check out this profile on how PathFactory hyper-personalizes the B2B buyer journey using AI.
PathFactory is a partner of Marketing AI Institute and/or a sponsor of our Marketing AI Conference (MAICON). View a list of Institute partners here and MAICON sponsors here. If you’re interested in becoming a partner or sponsor, find details here.