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How to Create an AI Marketing Strategy?

Artificial Intelligence (AI) has transformed numerous industries, and marketing stands at the forefront of sectors poised to gain immensely from its capabilities. Unlike other functions within a company, marketing heavily relies on understanding consumer behavior, aligning products or services with their needs, and persuading them to make a purchase. These core activities are ripe for enhancement with the implementation of AI. A comprehensive analysis by McKinsey in 2018 emphasized that among over 400 advanced use cases, marketing was projected to receive the highest value from AI.

The interest and adoption of AI among Chief Marketing Officers (CMOs) have been on a steady rise. Recent surveys, such as the one conducted by the American Marketing Association in 2019, indicated a significant 27% surge in AI integration within a year and a half. Additionally, a 2020 Deloitte survey revealed that the top five AI objectives, three of which were marketing-oriented, included enhancing existing products and services, creating new ones, and strengthening customer relationships.

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Current State of AI in Marketing

In the current landscape, AI has been integrated into various marketing functions. It aids in digital ad placement, improving prediction accuracy, and supporting structured tasks like customer service. It’s utilized in every stage of the customer journey. For example, AI targets potential customers during their product research phase and assists in guiding their search. Companies like Wayfair employ AI to identify potential customers and suggest products based on their browsing history.

Furthermore, AI streamlines sales processes by offering highly personalized product offers using detailed individual data. It also helps in upselling, cross-selling, and reducing cart abandonment rates. Post-sales, AI-enabled service agents handle queries and provide 24/7 support, managing fluctuations in service requests more efficiently than human agents.

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Framework for AI in Marketing

The AI Marketing Framework is a structured model that categorizes various applications of artificial intelligence within the marketing domain based on two fundamental dimensions: intelligence level and integration into platforms. This framework helps marketers understand, classify, and strategize the implementation of AI in their marketing activities.

Dimensions of the AI Marketing Framework

Intelligence Level:

• a. Task Automation: These applications are designed to execute repetitive, structured tasks following predefined rules or a sequence of operations. However, they lack the ability to handle complex or nuanced problems. An example of task automation includes systems that automatically send welcome emails to new customers or basic chatbots that follow decision trees but can’t discern complex customer intent.
• b. Machine Learning: These algorithms are trained using vast amounts of data to make relatively complex predictions and decisions. They can recognize patterns in images, segment customers, and predict responses to various initiatives. Machine learning drives programmatic buying in online advertising, powers e-commerce recommendation engines, and helps in sales propensity models in customer relationship management (CRM) systems.

Integration into Platforms:

• a. Stand-alone Applications: These are separate AI programs or tools that exist independently, outside the primary channels through which customers interact with a company’s offerings or services. Customers or employees have to make a special trip or interaction beyond those channels to use these stand-alone AI tools. For instance, a color-discovery app from a paint company that operates independently but connects users to a platform for making the actual purchase.
• b. Integrated Applications: Integrated AI applications are embedded within existing systems or platforms, often less visible to customers, marketers, and salespeople who use them. These applications operate within the primary channels and are seamlessly woven into the overall user experience. For example, machine learning models integrated into platforms that handle the entire process of ad placements or recommendations on e-commerce sites.

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Categories within the AI Marketing Framework

The combination of these two dimensions results in four categories of AI applications within the marketing context:

1. Less Advanced, Stand-alone Task-Automation Apps: These are basic AI tools or programs that operate independently and perform repetitive, rule-based tasks. They may include simple chatbots or email automation systems.
2. Less Advanced, Integrated Task-Automation Apps: These AI applications are integrated within existing systems and handle structured tasks, such as inbound customer call routing or marketing automation within CRM platforms.
3. More Advanced, Stand-alone Machine-Learning Apps: These AI applications operate independently and utilize machine-learning capabilities. Examples include advanced recommendation engines or personalized AI-driven tools like skin advisors or color recommendation applications.
4. More Advanced, Integrated Machine-Learning Apps: These are highly sophisticated AI applications integrated within existing platforms. They encompass predictive sales-lead scoring in CRM, sales coaching within integrated systems, e-commerce product recommendations, and programmatic digital ad buying embedded into larger marketing platforms.

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A Strategic Approach

Although simple stand-alone apps are easier to set up, their benefits are limited. The ultimate value lies in integrated machine-learning applications. However, basic AI skills and an abundance of data are prerequisites before progressing to more advanced applications. Companies should gradually transition from task automation to machine learning as they acquire the necessary skills and data.

New sources of data are critical, as AI applications heavily rely on vast amounts of high-quality data. Integrating AI into existing systems, particularly for more sophisticated applications, poses challenges that need careful consideration.

Balancing Automation and Human Involvement: Automating decisions wherever feasible provides the greatest returns from marketing AI. While some domains fully automate decisions, others present recommendations to individuals, with human input reserved for critical choices.

Challenges and Considerations: Implementing even simple AI applications can be complex, demanding appropriate skills and careful integration into workflows. The integration of AI into third-party platforms can pose additional challenges. Maintaining transparency and ethics is essential, particularly concerning data privacy, security, and customer trust.

Looking Ahead: AI in marketing, while offering significant benefits, is still limited in its capabilities and cannot entirely replace human decision-making. Yet, its potential is vast and evolving. Developing a strategic approach to leverage AI’s current capabilities while considering future prospects is crucial for CMOs and their teams.

Also Read: 8 Transformative Benefits of AI in Digital Marketing

Conclusion

In conclusion, while AI will transform marketing in the long run, this transformation will take time. Companies need to focus on building AI capabilities and addressing potential risks over the long term to realize the full potential of AI in marketing. It’s a journey that will require attention to detail, continuous improvement, and adaptation to the evolving landscape of AI capabilities.

Implementing AI in marketing is a strategic undertaking that demands a comprehensive understanding of its capabilities and limitations. As AI continues to advance and shape the future of marketing, CMOs and marketing teams will need to stay abreast of these developments, adapt strategies accordingly, and always prioritize ethical use and customer trust.

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Examples of AI Marketing Strategy

AI marketing strategy is the use of artificial intelligence (AI) to improve marketing outcomes. AI can be used to automate tasks, gain insights into customer behavior, and create more personalized and targeted marketing campaigns.

Example 1:

AI marketing strategy framework is a structured approach to using AI to achieve marketing goals. The framework typically includes the following steps:

1. Define your goals: What do you want to achieve with AI marketing? Do you want to save time, generate more leads, or improve your marketing ROI?
2. Identify your target audience: Who are you trying to reach with your AI marketing campaigns?
3. Collect data: What data do you have about your target audience and their behavior?
4. Choose the right AI tools: There are a variety of AI marketing tools available, so it’s important to choose the ones that are right for your business and your budget.
5. Develop your AI marketing strategy: This should include a plan for how you will use AI to achieve your marketing goals, reach your target audience, and personalize your marketing campaigns.
6. Implement your AI marketing strategy: This will involve using the AI tools you have chosen to create and execute your marketing campaigns.
7. Monitor and evaluate your results: It’s important to monitor your AI marketing campaigns to ensure that they are performing as expected and that you are achieving your marketing goals.

Example:

A company that sells e-commerce software could use an AI marketing strategy to achieve the following goals:

• Increase website traffic
• Generate more leads
• Improve conversion rates

The company could start by identifying its target audience, which could be small business owners who are interested in e-commerce software. The company could then collect data about its target audience, such as their demographics, interests, and website browsing behavior.

Next, the company could choose the right AI marketing tools. For example, the company could use a tool to create targeted social media ads or a tool to personalize its email campaigns.

Once the company has chosen its AI marketing tools, it can develop its AI marketing strategy. This could include a plan to create social media ads that target small business owners who are interested in e-commerce software, or a plan to personalize email campaigns based on the interests of the subscribers.

The company would then implement its AI marketing strategy by creating and executing its marketing campaigns using the AI tools it has chosen.

Finally, the company would monitor and evaluate the results of its AI marketing campaigns to ensure that they are performing as expected and that the company is achieving its marketing goals.

Also Read: How Smart Companies Are Using AI in Digital Marketing

Example 2:

AI Marketing Strategy Framework

One way to think about AI marketing strategy is to use a three-stage framework:

1. Data collection and analysis: AI can be used to collect and analyze large amounts of data, such as customer demographics, purchase history, and website behavior. This data can be used to gain insights into customer behavior and preferences.
2. Segmentation and targeting: AI can be used to segment customers into different groups based on their interests and needs. This information can then be used to target customers with more relevant and personalized marketing messages.
3. Campaign optimization: AI can be used to optimize marketing campaigns by tracking performance and making adjustments as needed. For example, AI can be used to identify which ads are most effective and to target those ads to the right people.

Example:

Here is an example of how AI marketing strategy can be used in practice:

A clothing retailer wants to increase sales of its new line of winter coats. The retailer uses AI to collect and analyze data on customer demographics, purchase history, and website behavior. This data reveals that the retailer’s target customers are women aged 25-34 who live in cold climates.

The retailer then uses AI to segment its customers into different groups based on their interests and needs. For example, the retailer creates one segment for women who are interested in fashion-forward coats and another segment for women who are interested in practical coats.

The retailer then uses AI to target each customer segment with more relevant and personalized marketing messages. For example, the retailer sends fashion-forward coats to customers who are interested in fashion and practical coats to customers who are interested in practicality.

The retailer also uses AI to optimize its marketing campaigns. For example, the retailer uses AI to track which ads are most effective and to target those ads to the right people.

As a result of using AI marketing strategy, the clothing retailer is able to increase sales of its new line of winter coats by 20%.

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FAQs on AI Marketing Strategy

What is AI marketing strategy?

AI marketing strategy is the use of artificial intelligence (AI) to improve marketing outcomes. AI can be used to automate tasks, gain insights into customer behavior, and create more personalized and targeted marketing campaigns.

What are the benefits of using AI in marketing?

AI can help marketers to:

• Save time and automate tasks.
• Gain insights into customer behavior and preferences.
• Create more personalized and targeted marketing campaigns.
• Improve marketing ROI.

What are some specific examples of how AI can be used in marketing?

AI can be used in a variety of marketing tasks, including:

• Content marketing: AI can be used to generate content ideas, write blog posts, and create social media posts.
• Email marketing: AI can be used to personalize email campaigns, segment subscribers, and predict which subscribers are most likely to open and click on emails.
• Social media marketing: AI can be used to create targeted social media ads, identify influencers, and monitor social media conversations.
• Search engine optimization (SEO): AI can be used to optimize websites for search engines, identify relevant keywords, and track SEO performance.
• Customer relationship management (CRM): AI can be used to segment customers, predict customer churn, and identify upsell and cross-sell opportunities.

How do I get started with AI marketing?

There are a few things you can do to get started with AI marketing:

1. Define your goals. What do you want to achieve with AI marketing? Do you want to save time, generate more leads, or improve your marketing ROI? Once you know your goals, you can start to identify specific AI tools and strategies that can help you achieve them.
2. Choose the right AI tools. There are a variety of AI marketing tools available, so it’s important to choose the ones that are right for your business and your budget. Some factors to consider when choosing AI marketing tools include:
   • The features and functionality of the tool.
   • The ease of use of the tool.
   • The cost of the tool.
   • The level of support offered by the vendor.
3. Integrate AI into your existing marketing strategy. AI should be used to complement your existing marketing strategy, not replace it. When integrating AI into your marketing strategy, it’s important to consider the following:
   • How will AI be used to support your overall marketing goals?
   • How will AI be used to improve your existing marketing processes?
   • How will AI be used to create more personalized and targeted marketing campaigns?

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What are some of the challenges of using AI in marketing?

Some of the challenges of using AI in marketing include:

• The cost of AI tools. AI marketing tools can be expensive, especially for small businesses.
• The complexity of AI tools. Some AI marketing tools can be complex to use, and may require specialized training.
• The lack of transparency in AI algorithms. It can be difficult to understand how AI algorithms work, which can make it challenging to troubleshoot problems or optimize campaigns.
• The potential for bias in AI algorithms. AI algorithms can be biased, which can lead to unfair and discriminatory marketing practices.

How can I overcome the challenges of using AI in marketing?

There are a few things you can do to overcome the challenges of using AI in marketing:

• Invest in the right AI tools. There are a variety of AI marketing tools available at different price points. It’s important to choose tools that are affordable for your business and that meet your specific needs.
• Get training on AI marketing. There are a number of courses and tutorials available that can teach you how to use AI marketing tools effectively.
• Monitor your AI marketing campaigns closely. It’s important to monitor your AI marketing campaigns closely to ensure that they are performing as expected and that they are not biased.

Overall, AI is a powerful tool that can be used to improve marketing outcomes in a variety of ways. However, it’s important to be aware of the challenges associated with using AI in marketing and to take steps to overcome them.