AI isn't a goal (or a strategy): Aligning AI with Your Marketing Strategy, Part 2

Let’s face it: AI is here to stay, and despite the hype, it’s really good at a lot of things. However, amidst the fervor for adoption, it’s crucial to remember that AI itself is not the ultimate objective of any marketing strategy. Instead, it serves as a powerful means to achieve broader business goals. So, let's look at leveraging AI as an augmentative tool rather than an end goal in itself.

?? Want to take this further? This is what I do: I work with orgs on AI adoption and marketing ops strategies that incorporate AI. =>Let's talk.

Let's balance the hype with a dose of realism.

Reality check: ?Remember: Integrating AI into your marketing strategy isn’t about chasing the next big thing. It’s about carefully choosing and applying tools that complement and enhance your existing efforts.

With a clear understanding of where AI fits into your strategy, the next step is choosing the right AI tools. Not all AI is created equal, and the wrong tools can add complexity without real benefit.?

Example: You decide your email marketing could use a boost from AI. The right tool would not only automate email schedules based on customer behavior but also provide analytics on open rates and conversions, offering insights that help refine your approach over time.        

Let’s look at how to pick wisely.

Match Tools to Needs

In the labyrinth of AI solutions available today, it's easy to get lost among features that sound impressive on paper but may not align with what you actually need. The key is not to let the allure of "advanced" features cloud your judgment. Focus on the core requirements of your business and seek AI tools that are adept at meeting those specific needs.

Example: Suppose your marketing analytics team is overwhelmed with data but struggles to derive actionable insights due to the sheer volume and complexity. Here, an AI tool specialized in data crunching and pattern recognition would be ideal. Such a tool could automatically analyze customer data to identify purchasing patterns, predict trends, or even flag anomalies that warrant further investigation, thereby directly addressing the need for comprehensive yet comprehensible data analysis.

Ease of Integration

The integration of an AI tool into your existing systems should not be akin to fitting a square peg into a round hole. An AI solution must seamlessly mesh with your current technology stack to avoid disrupting your operations. Tools requiring extensive overhauls or specialized training might introduce delays and steep learning curves that could negate the efficiency gains AI is supposed to bring.

Example: Consider an AI-powered content management system (CMS) that promises to streamline content creation and distribution. If integrating this system means overhauling your existing digital asset management setup, the transition costs could outweigh the benefits. Instead, look for an AI tool that complements and easily integrates with your existing CMS, perhaps through plugins or API integrations, ensuring a smooth adoption process and immediate efficiency gains.        

Listen as Michael True of Prescient AI talks about using #AI to determine which of your #marketing dollars are working.

Scalability

When selecting an AI tool, think long-term. It’s essential that the AI solution can scale as your business expands. Investing in a system that cannot handle increased loads or adapt to new business requirements will only lead to future headaches and additional costs down the line.

Example: If your e-commerce platform uses AI for personalized recommendations, ensure the system can handle a growing number of users and SKUs without performance degradation. As your product range expands and customer base grows, the AI must continue to deliver personalized experiences efficiently, without requiring frequent costly upgrades or replacements.

Vendor Support and Community

The quality of vendor support and the presence of an active user community are crucial factors in choosing AI tools. Robust support can drastically reduce downtime by resolving technical issues swiftly, while an active community can offer practical advice and innovative uses that enrich your AI implementation.

Example: Selecting an AI tool for social media sentiment analysis should involve evaluating the vendor’s support structure. Can they provide immediate assistance if the tool fails during a major marketing campaign? Similarly, a vibrant community can share insights into best practices for sentiment analysis across different platforms, helping you to leverage the tool more effectively and avoid common pitfalls.

By expanding on these considerations, you can ensure that the AI tools you choose are not just technologically advanced but are also the right fit for your business needs, easy to integrate, scalable for future growth, and supported by reliable vendors. This strategic approach helps maximize the effectiveness of your AI investments and ensures they deliver real value to your marketing operations.

Conclusion

Remember, AI is part of the journey, not the destination. It should make your marketing smarter, not harder, helping you to not just meet but exceed your strategic goals. Keep it sensible, keep it aligned, and watch as your marketing strategy becomes more powerful than you ever managed before—AI-assisted, not AI-dependent.

In the next edition, we'll look at agentic AI and the role it can play in augmenting your existing stratetics.

Stay tuned as we explore more about how to meaningfully incorporate AI into your marketing work and go past the hype. Sign up for this newsletter and you can see more on my website at https://www.gregkihlstrom.com