Top 11 AI Marketing Use Cases: Benefits and Real-World Examples

Top 11 AI Marketing Use Cases: Benefits and Real-World Examples

June 15, 2024
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7 min read
Unveil the power of AI in marketing with our guide to the top 11 AI marketing use cases. Explore how each delivers tangible benefits through real-world examples.

Here are three interesting statistics from Sproutsocial:

  • 81% of marketers feel AI has made a positive impact on their work.
  • 78% feel AI has benefited them in creative areas like content ideation.
  • 73% report a positive impact on productivity.

Did you notice that all of them convey the same point - AI and marketing are a match made in heaven. Over the months, AI marketing has automated most of the repetitive tasks in marketing functions, freeing up marketers to focus on strategy and creative development. This enables them to design highly specific and engaging campaigns that also adjust in real-time based on consumer behavior and feedback. But is this the only thing AI and marketing can do in unison? Absolutely not.

And that’s where this post comes in where we look into 11 unique AI marketing use cases that you must know.

Use Case 1: Enhancing Customer Personalization

If you have to convince potential customers, you have to give them what they need. Remember, today’s customers are spoiled for choices. They are going to purchase from you only if:

  • You understand what they want
  • You offer a personalized experience

To achieve this, you need to collect information, analyze it, and then serve hyper-personalized content to the customers, all of this in the blink of an eye. Such speed is, of course, possible with AI and ML tools. They can look through your customer’s browsing history, purchase history, social media interactions, and even perform sentiment analysis from customer reviews and feedback, all in seconds. The generated insights equips you to offer content that can be tuned towards what each customer wants to consume.

A classic example would be AI-based recommendation engines. Most eCommerce stores today suggest relevant products dynamically to customers. This makes the whole shopping experience customized to the customer’s individual preferences, which leads to increased engagement and higher conversion rates. Here is an example of an eCommerce website suggesting products based on your browsing pattern -

Example of customer personalization

Use Case 2: Create and Optimize Ad Campaigns

Many marketers that we’ve spoken to find the creation and management of ad campaigns quite overwhelming. This is understandable. On one hand, you have creative ideation eating up most of their time. On the other, there is the constant stress of ensuring the ads are timely and appealing enough to encourage audiences to click them.

Thankfully, businesses now have access to dedicated AI-powered ad generators for creating and optimizing ad campaigns without experiencing the pitfalls of generic tools. One such tool is Eacel AI, which helps you create captivating, brand-tailored ad creatives in seconds. It uses advanced AI algorithms to analyze past performance to automatically generate ad creatives tailored to your specific campaign objectives.

Creating and optimising ad campaigns using Eacel

Use Case 3: Automating Customer Interactions

Responsive and consistent customer service is no longer optional for brands looking to convert prospects into customers. If you want to boost conversion rates, you need to ensure such efficient customer service is made available. While large enterprises can afford multi-member CS teams, smaller and medium-sized businesses don’t have that luxury. And that’s where AI-based chatbots and virtual assistants come in handy as they automate customer service activities to a great extent.

Most of you would have interacted with a chatbot at some point in your life. They can handle a wide range of customer queries, from answering FAQs to assisting with orders and providing troubleshooting support. These AI-driven solutions can engage with visitors in real time, provide instant responses to inquiries about products or services, and guide them through the buying process. But that’s not all, some chatbots are even capable of upselling or cross-selling based on your customer behavior and preferences.

Here is an example of a chatbot answering all your queries promptly -

Example of a chatbot

Use Case 4: Predictive Analytics in Marketing

Customer choices are not completely random, they have patterns. As a marketer, if you can identify these patterns, you can accurately predict how your customers will behave in response to a campaign. Now, to identify such patterns, you need to go through tons of data sets, which is possible only with the help of AI. AI tools can easily predict what, why, where, and how a customer will purchase from your brand by analyzing market trends and previous customer data.

These tools use a variety of attributes and perform different types of operations like text analysis and sentiment analysis and assign scores to the leads. Using this prediction, you can use the right channel to offer the right solution, that too at a price they are looking for. This will ensure that a sale will materialize. Popular predictive analysis tools in marketing include Marketo Engage and IBM Watson.

Use Case 5: Textual Content Generation

Content creation using AI has come a long way from generating simple texts using ChatGPT. Today, the market is inundated with AI content tools that can generate high-quality, unique, and engaging marketing content across various formats and channels. Right from onboarding emails to ad copies, AI can handle them all.

A typical AI content tool uses natural language processing algorithms and large language models to analyze patterns and styles of existing content that has worked with your target audience. It then uses this knowledge to come up with relevant content that your audience can consume and get converted into customers.

For instance, tools like Copy.ai,  Jasper, and Mailchimp can continuously churn persuasive email content based on user behavior, preferences, and past interactions.  Similarly, Eacel.ai is capable of generating unlimited copies for your ads, eliminating the need to rely on multiple tools for ad creation.

Textual content creation of Eacel

Use Case 6: Visual Content Creation

AI has made visual content creation more accessible and impactful. AI tools can generate high-quality images, graphics, and videos tailored to specific audiences and purposes. They use advanced algorithms like Recurrent Neural Networks and Generative Adversarial Networks to analyze and replicate various artistic styles and create entirely new visual elements, images, and videos from scratch. This saves time and resources and also allows for rapid iteration and experimentation.

AI video creation tools like Invideo and DeepBrain generate professional-looking videos without needing extensive video editing skills. By leveraging AI, these tools can automatically add video clips, incorporate music, and generate transitions based on the inputted script. For example, you could prompt these tools to generate product demo videos just by sharing basic information about your product.

Use Case 7: Real-Time Decision Making

Imagine launching a critical campaign for your brand. Now, what if you could get an instant picture of how your audience responds? This would allow you to tweak messages, adjust offers, and change strategies on the fly. This is real-time decision-making, a key requirement to swiftly pivot your efforts in accordance with the shifting landscape of consumer behavior. Many AI tools also offer critical insights into your competition, further enhancing your decision-making capabilities.

A good example of this use case would be dynamic pricing models on retail websites. AI tools like Pricefx and Prisync facilitate real-time and automated decision-making related to pricing strategies. Here is a typical working of such a platform:

  1. Continuously gather brand-level data from various sources, including customer behavior, historical sales data, competitor prices, and external factors like market trends.
  2. Evaluate product-specific factors such as how often a product is viewed, how many times it has been added to carts, current inventory levels, and competitor pricing.
  3. Analyze all this data in real time to identify patterns and correlations.
  4. Use the insights generated to dynamically adjust prices. For example, if a competitor lowers the price of a similar product, the system will automatically reduce the price on the retail website to stay competitive.

Use Case 8: Search Engine Optimization

Did you know that Google is the starting point for up to 85% of purchasing choices? So, unless you master the art of SEO, it is hard to survive in the extremely competitive business ecosystem. While traditional SEO strategies like link building may still seem relevant, they are not sufficient because search engines are getting smarter and smarter every day. It can easily identify hacks like keyword stuffing and duplicate content and penalize you severely. To stay ahead of the SEO curve, many marketers are increasingly relying on AI-based SEO tools.

An excellent example of an AI-based SEO tool would be SEMRush. This AI research tool uses machine learning algorithms to identify relevant keywords that have high search volume and low competition. It then provides insights into keyword difficulty, search intent, and related queries, enabling you to target the most effective keywords. It also helps you better comprehend the purpose behind specific term usage as well as the content of searches.

Use Case 9: Social Media Marketing

Social media teams are usually overworked because they juggle multiple priorities. Most of their time is spent on responding to customer comments and scheduling posts. This leaves very little time for them to ideate, strategize, and analyze social campaigns, leading to suboptimal performances.

AI social media marketing tools automate most of these functions, saving your team’s time and effort. These tools can personalize your social media interactions, enhance customer engagement, and improve overall campaign performance with minimal manual intervention.

For example, a tool like HootSuite can be used to automate the whole process of scheduling posts. It even identifies the best times to post for maximum audience engagement and impressions.

Use Case 10: Customer Segmentation

One of the main reasons to perform customer segmentation is to align your campaigns with customers who are most likely to buy your offerings. However, performing customer segmentation manually is time-consuming and bias-prone due to the sheer volume of data and the complexity of identifying meaningful patterns. It often leads to oversimplified segments that do not capture the nuances of customer behavior.

AI completely automates customer segmentation by gathering data from various sources, including purchase history, website interactions, and social media activity, and creating highly granular customer segments. AI tools performing customer segmentation continuously learn and adapt, ensuring that segments remain relevant and reflective of current customer behavior.

Adobe Audience Manager is one such platform that uses machine learning to analyze user interaction data across multiple touchpoints, creating detailed customer profiles and segments in real time.

Use Case 11: Campaign Analysis and Optimization

AI tools can analyze your campaigns, capture various performance metrics, and suggest actionable improvements. It can instantly identify anomalies that might not be immediately apparent to human analysts. Some tools can also measure the effectiveness of different campaign elements, such as ad creatives, targeting parameters, and channel performance, offering a comprehensive view of what works and what doesn’t.

Google Analytics 4 employs AI to track campaign performance, while also suggesting optimizations for your landing pages or ad placements. Similarly, IBM Watson can identify underperforming segments and recommend changes to improve targeting and content relevance. By continuously learning from new data, these platforms enable you to make data-driven decisions that enhance campaign effectiveness.

Also Read: Step by Step Guide to Paid Ads Funnel - Set up, Stages and Examples

Conclusion

The use cases highlighted in this post understate the benefits of AI in marketing. AI’s remarkable ability to automate repetitive tasks and analyze vast amounts of data in real time gives you unlimited time to focus on creative and strategic initiatives. Together, you can drive growth and innovation for your brand. One AI-powered marketing tool that you can adopt straightaway to drive efficiency is Eacel. It can automate your ad creation process while you focus on other aspects of campaign management. Sign up for a free account now.

Frequently Asked Questions

1. Is AI the future of marketing?

Absolutely. The integration of artificial intelligence into various marketing functions is already happening as you read this statement. It has already changed how marketers engage with their customers, analyze their data, and fine-tune their marketing strategies. In the coming days, AI-driven marketing strategies are expected to flourish, driving innovation and creating new opportunities for businesses.

2. What are the benefits of AI in marketing?

Some of the major benefits offered by AI in marketing include efficiency, cost savings, and more accuracy in decision-making.

3. How to use AI for marketing automation?

To effectively use AI for marketing automation, you must first identify repetitive and time-consuming tasks.  It could be related to email campaigns, social media updates, or even customer segmentation. They choose AI-powered marketing tools that can automate these activities and can be easily integrated with your existing MarTech.

4. How is AI changing advertising?

AI is transforming advertising by letting you create highly targeted campaigns through the analysis of customer data. Today, you can find a plethora of advertising  tools using AI for automating different tasks such as real-time bidding, ad placements, and dynamic creative optimization.

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