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How To Use AI In Marketing Functions

5 Mins read

AI tools such as viss.ai help marketers make better decisions, and deliver growth that the C-suite is looking for. Explore how AI can be used in marketing functions to better understand customer needs, increase productivity, and maximize return on investment.

Personalized marketing is essential for retaining customers and increasing brand loyalty. AI can identify patterns in customer data to provide more relevant content and offers.

Personalized Content

Personalization in ai marketing is one of the most popular ways to use artificial intelligence. It involves tailoring specific content to customers based on demographic information, context data, and behavior data. This type of personalization has the goal of improving engagement and conversions.

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AI marketing offers several types of personalization, including displaying relevant services or products to visitors on websites or emails, dynamic content in emails based upon user behavior, and providing customized product recommendations. Content and support that is personalized can be used to improve the customer service experience. For example, AI digital assistants can answer questions, provide guidance, and help users navigate a website or app.

Personalized content is an excellent way to show that you care for your customers and want to give them the best possible experience. Many consumers say that personalized content increases their brand trust. In fact, 78% of US internet users say that seeing personalized content from a brand makes them more likely to purchase from that company.

It’s important to remember that not every business has the resources to implement an AI-powered strategy. Choose a few areas in your business where you will have the greatest impact with the least amount of effort. For example, you could start by personalizing your email campaigns, creating AI-assisted sales scripts, or integrating an AI-powered attribution platform to track the ROI of your advertising budget.

You should also set clear metrics for evaluating the success of your AI-assisted marketing efforts. This could be the number or sales generated from ecommerce channels or the number of leads created by ad campaign or the percentage of website visitors who complete your lead form. Track these metrics over time to compare and analyze your AI-assisted efforts.

Lookalike Modeling

Lookalike modeling plays a major role in a successful AI-marketing strategy. It uses machine learning in order to identify the characteristics and behaviors of your most successful audience segments. Then, it finds new audiences with similar profiles — ones that are ready to apply, connect, or donate. It’s a powerful tool to help you reach more customers and scale your campaigns.

To create a similar audience, marketers begin with an existing group of people known as a “seed” group. This can be sourced from a data provider, or it can be native to a DMP (Data Management Platform). The DMP will then analyze that seed group in order to identify the attributes and behaviors which are most closely associated with your campaign objectives. For example, for a brand awareness campaign, the model might look for attributes such as demographics, purchase history, social media behavior, and product affinity. In contrast, a model for a campaign aimed at conversions might look at attributes such as in app purchases, email signups or in platform conversions.

The DMP then uses various ML techniques and algorithms to match users with attributes in its own data. It might, for example, use support vector machines (SVMs) to determine which attributes in the target group are most relevant, and then search for users who have those attributes across all channels. Or, k-nearest neighbours could be used to identify the small group of users most likely to belong to a target group.

Once the DMP has identified a group of users that match, it can serve your ads to them across all channels. This process can be repeated continuously to ensure your campaigns are always targeting the most relevant audience.

AI systems are capable of much more. They can analyze unstructured information like social media posts, customer reviews, and support tickets to identify valuable attributes. They can also optimize similar models for specific platforms or use image and videos analysis to identify specific images and videos. They can also adjust the lookalike audience in real time, based on campaign results and market conditions.

Cross-Channel Marketing

Marketers are faced with the challenge of developing cross channel marketing strategies as the number and variety of digital marketing devices and channels is rapidly increasing. This approach takes multiple channels and uses them for unified messaging to build trust and enhance customer experience. The result is more effective marketing and growth for the business.

AI is becoming increasingly useful in this area. It can help identify target audiences by using data analysis and ad-targeting, but also improve content creation through automation and more compelling messaging. Generative AI for example uses large language and natural language models to create unique results based on the raw data entered by users. This allows marketers to focus their efforts on other aspects of their marketing strategies and ensures that all channels are telling the same story.

When it comes to delivering a seamless brand experience, there is no better way than using an omnichannel marketing strategy. This approach combines all marketing channels to reach the consumer at every point in their journey, resulting in more engaged customers and increased ROI.

AI-powered analytics tools and personalization can help you create a successful omnichannel marketing strategy. For example, an email AI-powered solution can identify the best time and message for a brand to contact a potential lead, without taking into account their previous interactions with the company. This kind of personalization can greatly increase the likelihood that a prospect will become a customer.

AI can also help create a seamless experience by coordinating messages and campaigns across channels. To drive engagement, for example, a campaign via email may be followed by a social media posting or retargeted ad. A marketer can automate this type of coordination by connecting their customer data via a data management platforms (DMP). This will ensure that a consistent and coordinated message is delivered at all time, and that all marketing activities are working together in order to achieve the desired result.

Data-Driven Decisions

Marketers use data-driven decision making when deciding to introduce a new product, invest in a specific channel or even make a branding change. This allows them to save time and money as they can confidently assess the effect of their decision with verified statistics. The data-driven analysis ensures the final result is in line with business goals as it takes into consideration the customer experience, among other factors.

AI can be used by marketing and sales departments as a tool to automate repetitive tasks that consume valuable time. According to a recent survey, marketing specialists spend on average 16 hours a week performing routine tasks, such as entering leads into CRM systems, checking prices of competing products and services, or answering customer questions in chats. By integrating AI in their processes, companies are able to automate these tasks. This allows them to focus on more creative projects.

AI can improve your digital marketing by improving customer experience and increasing conversions. AI makes recommendations based on past purchases, behavior and interests of your customers. AI tools can also analyze social media conversations, surveys and customer reviews to gauge brand sentiment. This information can then be used to make improvements in products, services and marketing messaging.

Programmatic advertising is another area where AI can significantly improve marketing efforts. AI algorithms are able to optimize ad campaigns in real-time to maximize return on investments. Albert, an AI-powered platform for marketing automation, was used, for example, by Interactive Investor to boost account signing ups and reduce advertising costs.

When selecting an AI marketing agency, look for one that offers customization capabilities to align the technology with your business needs and infrastructure. Evaluate whether the solution is scalable to accommodate growing data volumes and if it integrates with your CRM system to streamline workflows. It should be easy to use, and provide reliable customer support. Consider a tech stack assessment to identify inefficient tools and overlapping functionality. This will help you streamline your tech stack while reducing costs and maintaining data security.

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