For a while now, I’ve been reading and writing about artificial intelligence. As a marketer, the thought of being able to personalize every little detail of my campaign delights me. But what I’ve learned over time is that if you haven’t taken the right first steps, your whole AI implementation can and will fall apart.
As marketing leaders, we all want to ride the AI wave. However, implementation isn’t so simple -- according to a recent Salesforce report, nearly 40% of marketers say they don’t know how to maximize new AI capabilities. In my opinion, this is due to a lack of proper planning and strategy ahead of the AI implementation.
Though you may not realize it, there are different types of AI. For those using marketing automation, you’re actually already utilizing AI technology. Maybe you also use ChatGPT in your daily life. But when I say that we all want to implement AI in our marketing strategies, I’m referring to more robust systems like predictive and generative AI. In fact, the 9th Edition State of Marketing report noted that 71% of marketers intend to use both predictive and generative AI within the next 18 months.
How can I incorporate AI into my marketing?
Before adopting AI, and to ensure success with predictive and generative AI, it’s crucial to lay a strong foundation. AI can offer transformative benefits, but its implementation requires careful planning and consideration. It’s important that you ask yourself the following questions:
- What specific problems or challenges can AI help me solve?
When I think of AI for marketing, I think of 3 pillars: data, segmentation, and personalization.
- Data
AI can gather data from a variety of sources, including social media, website analytics, CRM systems, and third-party data providers. This comprehensive data collection gives us a 360-degree view of the customer. With AI you can identify patterns, trends, and insights that inform marketing strategies and decision-making.
Don’t forget that data quality is the cornerstone of effective AI. AI tools can help clean and organize data, removing duplicates and inconsistencies, which improves the accuracy and reliability of insights generated.
- Segmentation
Marketers can divide audiences into distinct groups based on demographics, behaviors, and preferences to target them properly.
- Personalization
We can also use AI algorithms to analyze our customer data and recommend personalized content, such as blog posts, articles, or videos based on individual interests and past behavior. Additionally, we can tailor our campaigns with AI-driven tools.
- Data
- How will AI integration align with my overall marketing strategy?
Ok, I’ve already listed a handful of possibilities with AI. But integrating AI into your marketing strategy requires careful planning and alignment with your overall business goals.
- Ask yourself:
- Do I have all my data sources identified?
Surely, you manage social media channels and a CRM, and you have you’re own data base and third-party data providers. It’s important to list all your sources, and to understand how you have them integrated. - Do I have a considerable audience to create different segments?
Segmentation is key for success in marketing, you must have a wider audience and the information needed to create segments. - What type of information am I gathering from my audience?
Similar to the previous questions, you need to understand what information you are collecting. Is it relevant for your campaigns? Will it help to create better experience for your customers? If not, you need to re-think what questions you should put on your forms and do it wisely. - How can I personalize all the content?
After you have the segments, you need to create the strategy. Using dynamic content is a good way to personalize based on the information you have.
- Do I have all my data sources identified?
- Ask yourself:
Once you've covered all of this information, you might realize that it's a lot of work and data to analyze. You might be left wondering how you can integrate all the data in one place. Salesforce Data Cloud is a good choice because you can consolidate data from various sources and leverage advanced segmentation tools to create precise audience segments based on demographics, behavior, and more.
- What is the timeline for implementing AI solutions and seeing results?
Based on the problem you have identified and your specific needs, you can estimate a rough timeline. Understanding the timeline for deployment and the benefits is crucial for setting realistic expectations. Remember that starting with quicker, easier solutions can provide immediate ROI and build the necessary foundation for more complex implementations.
Create a detailed timeline outlining specific weekly actions and incremental steps to ensure a smooth implementation, an agile approach is ideal to avoid spending a lot of time on possible solutions that then you realize are not the best ones. Remember the golden rule: always set clear, measurable objectives for AI implementation. Finally, establish a robust framework for monitoring and measuring success.
- Are there any regulatory or compliance issues we need to address when using AI?
When implementing AI, it's crucial to understand the complex landscape of regulatory and compliance issues. AI technologies often involve the collection and analysis of vast amounts of data, including personal information. I recommend that you ensure compliance with data privacy regulations, such as the General Data Protection Regulation (GDPR) in Europe, or the California Consumer Privacy Act (CCPA) in the United States. These laws dictate how you collect, store, and use personal data.
Develop guidelines to ensure that your AI systems are used ethically. This includes avoiding biases in AI algorithms that could lead to discriminatory practices. Maintain transparency with your customers about how their data is being used. Clear communication builds trust and helps mitigate potential legal issues.
- Do I have the human resources?
Implementing AI is not just about technology; it's also about having the right team to manage and leverage these tools effectively.
Do you have team members with the necessary skills in data science, machine learning, and AI? If not, you may need to invest in training or hire new talent. AI projects often require collaboration between various departments — marketing, IT, and data analytics. Ensure that your teams can work together seamlessly. AI tools need continuous monitoring and optimization. Make sure you have dedicated resources to manage and update your AI systems regularly.
- Do I have the budget?
AI implementation can be costly, and it's essential to have a clear understanding of the financial investment required.- Here are some budgeting considerations:
- Calculate the costs associated with acquiring AI tools and technologies. This includes software licenses, hardware, and potential infrastructure upgrades.
- Allocate budget for training your team to use AI tools effectively. This might involve workshops, online courses, or hiring external trainers.
- Factor in the recurring costs of maintaining and updating AI systems. This includes software subscriptions, cloud storage, and technical support.
- Here are some budgeting considerations:
Start small for success
I recommend identifying your needs, answering the key questions, and then setting up a plan.
Remember, less is often more. You don’t need to implement a robust system to see results; you can start with small steps. Use a small campaign as a pilot, and test, test, test!
Begin by clearly defining the objectives of your AI implementation and the specific outcomes you want to achieve. Focus on a single aspect of your marketing strategy where AI can make a significant impact. For instance, you might start with using AI to personalize email marketing or to analyze customer data for better segmentation.
Once you have your pilot campaign, monitor its performance closely. Collect data on its effectiveness, and be prepared to make adjustments. This iterative approach allows you to refine your AI applications gradually, ensuring that each step is based on solid evidence and real-world results.
As you gain confidence and experience with AI, you can gradually expand its use to other areas of your marketing strategy. This phased approach minimizes risk, maximizes learning, and allows for sustainable integration of AI technologies into your business operations.
