From the AI Proving Ground, Promising Use Cases for Marketing Teams

AI in marketing

As someone who works in the world of digital technology, I have kept close tabs on advances with artificial intelligence (AI), curious how it ultimately might fit into our professional and personal lives.

In late 2022, triggered by the buzz around OpenAI’s release of its generative artificial intelligence (genAI) tool ChatGPT, my curiosity morphed into a mission to learn all I could about AI. In the process, I also wanted to determine if my company, Unanet, and the marketing team I lead, could benefit from AI, machine learning (ML) and other intelligent technologies – which I’ll collectively refer to here as AI.

As I climbed the AI learning curve, that “if” quickly turned to “how, when and where.” It became clear early in my journey that there were a wide range of ways my team could put AI to work. Now, close to a year into that journey, we’re seeing substantial returns on the time and resources we’ve invested along the way. The Unanet marketing team has implemented intelligent tools in a variety of use cases.

The benefits of AI are undeniable. It provides insight we likely wouldn’t have otherwise unearthed. It has helped us optimize processes, gain efficiency, and increase productivity. It has allowed us to weave greater personalization into our marketing efforts. It’s augmenting human expertise and helping people do their jobs better.

Yet there are no guarantees when it comes to AI. One of my most important takeaways from this journey is that to maximize your AI investment, you need to approach integrating AI with a thirst for knowledge. You also need an internal compass to keep you focused on finding AI use cases that align to your business goals and resolve a business issue for you, your customers and/or your partners. Perhaps most importantly, you need a clear plan. In our case, the plan for piloting AI unfolded in five stages:

Stage 1: Identify specific areas of your marketing organization where AI can meet a need or solve a problem

This is about methodically finding specific use cases where AI can bring value, resisting the temptation to invest in the shiniest new AI toys. As much buzz as some of these tools may generate, they may not be the most appropriate tool for your needs.

I’ve learned that embracing AI in a marketing context should first and foremost be about people — enhancing the expertise of teams, making strategies more intelligent and informed, and elevating the creativity that fuels campaigns. The chief goal with AI should be to complement your team’s creativity and execution. A genAI tool, for example, can enable your team to accomplish things faster, with better overall quality. At the same time, this can make their lives and jobs easier, freeing them to focus on higher-value creative pursuits.

To those ends, take stock of your existing martech stack by answering the following questions:

  • What tools do you already have in-house that have embedded AI capabilities? Audit your existing martech stack.
  • Are there efficiency gaps that AI can fill, and/or opportunities to streamline or improve the way you operate?
  • Are your team members equipped with the skills necessary to adapt to and leverage AI effectively? How ready are they to incorporate a new tool?

Once you’ve answered these questions, get clear about your AI-related objectives. Ensure they align with your business goals. The objectives you set for your AI initiative should be about finding tools that complement your team’s strengths and align with the direction you want your marketing team to go.

Next, bring your team into the AI dialogue. Fill them in about your goals in exploring AI, how doing so will benefit them in their work, and how, with their help, you plan to track their use of AI tools and their impact. Ask them what they want from their AI tools.

Stage 2: Do your due diligence, assessing the available tools

My personal due diligence entailed soaking up all I could about using AI in a marketing context. I dug deep into the resources offered by organizations like the Marketing AI Institute and took an online eight-week course on the subject to build my foundation of knowledge.

During that immersion, I learned how important it would be to zero in on the capabilities with the most potential value to my team in their day-to-day roles, seeking out tools that would ultimately increase my marketing department’s ROI.

Collectively, our team looked at the platforms available to us and where we needed assistance. We identified copywriting as a major need. We wanted the ability to quickly develop on-point content that could match our brand voice and tone. This wasn’t about quantity; it was about quality. The aim was to refine and target marketing efforts more effectively, not to produce content or data at scale indiscriminately. We also focused on efficiency, with an eye toward using AI to automate time-consuming, manual processes.

Besides copywriting, we identified a few other areas where we believed AI could really add value, such as with video, visuals and creative, where it could quickly scale and size of images for various communication channels and speed up video editing. We also engaged our legal and IT security teams to ensure the AI tools we were considering met data protection laws . We needed to preserve the privacy and trust of our customers, as well as the confidentiality of our internal information. We committed to following strict ethical standards in our usage of AI. Doing all this early in the process helps to avoid problems later.

Then, after evaluating various platforms, we performed a proof-of-concept test to evaluate those we found most promising, asking the following questions:

  • Does the platform/provider have a strong professional reputation?
  • Does it offer the right features and capabilities?
  • Does it have a strong AI roadmap that aligns with our goals?
  • Does it have a dedicated customer success manager (CSM) and adequate training resources?
  • Is it secure and compliant, with the appropriate data-protection policies in place?

Stage 3: Start piloting

This phase began with training to learn the functions of the copywriting platform we had chosen as our first system to pilot. We wanted to ensure we were using the tool correctly to maximize its value. Once we began using it, we established a Slack channel to share our experiences and best practices. We also stayed in close contact with representatives from the platform providers, offering feedback and asking questions.

We started small with a tool that readily integrated with our martech stack – this is key –  and didn’t try to do too much too soon. We set up controlled experiments with the tool and tested it with clearly defined objectives, success metrics, and the participation of cross-functional teams.

This “pilot before purchase” approach worked well, enabling us to test several solutions before going all-in on a comprehensive suite of AI tools, and helping us identify where we could capture quick wins with the platform.

Stage 4: Get your team excited, engaged and enabled

This is a critical step in maximizing the value an AI tool delivers.  When your team feels empowered and part of the process, they’re more likely to actually use the tools at hand. Part of empowering them is underscoring just how valuable their human expertise and creativity are, and that AI tools are here to help them do their jobs better, not to replace them. When you talk about AI within your team, frame it as a support system whose insights and recommendations are designed to serve their nuanced strategic thinking, judgment and creativity.

Besides consistently reinforcing these messages, committing to ongoing, role-specific AI education and training for team members is another crucial part of the journey, as is encouraging experimentation and learning from pilot failures. You’re engineering a cultural shift where the goal is to get and keep people engaged in the AI journey. So address any concerns head-on, maintain an open dialogue with them, give them a voice in the entire process, regularly showcase wins and how AI is benefiting them and the business, and recognize them for team and individual achievements along the way.

Stage 5: Harness existing martech AI capabilities

Incorporating AI into your marketing team’s work doesn’t always entail adding new software or technology. In fact, the platforms you already use may include AI features and functionalities, some of which you may not even be aware of. To learn about them, review product documentation and/or release notes, or ask your customer success representative. If you do identify functionalities that could benefit your team, start implementing them following the aforementioned guidelines.

Another important takeaway from my AI journey is not to let yourself get distracted by the firehose of hype around new AI features. By experimenting in a low-pressure environment using a careful, measured approach and communicating clearly with your team, you can get more and more comfortable using AI. Learning and implementing AI is like any other tool – with patience and planning, you and your team members can incrementally shorten the learning curve.

Then comes the most exciting part of the journey: watching AI’s work, and experiencing the benefits. Throughout the pilot, my team and I committed to regularly communicating about how we were using the AI tool, sharing successes, challenges, and wins.

We also committed to tracking performance against predefined KPIs to measure the impact of our AI investment, and to gathering qualitative feedback to measure the extent to which people are getting comfortable with AI, as critical as the employee experience is to the long-term success of an AI initiative. My advice: Analyze outcomes, document lessons learned, and use these findings to refine your AI strategy for broader rollouts.

In our case, the AI pilot proved to be a resounding success. On the content side, for example, we sliced the time to create blog posts from existing content in half. We also developed new capabilities to quickly build out email programs and to easily tailor existing campaign assets to specific verticals and customer personas. On the creative side, AI-enabled automation has cut ad production time by 500%. With our annual user conference, we’ve been able to glean a ton of actionable insight from attendee feedback that we otherwise might have missed. The list of wins is lengthy — and growing.

And our AI journey continues. The success we’ve enjoyed to this point has only encouraged us to keep seeking new ways for AI to help us innovate and grow. With a thoughtful approach to integrating AI, you’re not just chasing the next big thing. You’re building a smarter, more creative, and more productive future for your marketing team and the entire organization.

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Carrie Mahon
Carrie Mahon is chief marketing officer at Unanet, a leading provider of project-based ERP and CRM solutions purpose-built for government contractors, and architecture, engineering, construction, and professional services firms.