Artificial Intelligence in Marketing

How AI Is Transforming Marketing

In a fast-paced and ever-evolving digital marketing landscape, marketers need new ways to find and attract their ideal audience.

Artificial intelligence (AI) leverages customer data and machine learning (ML) to help companies:

Understand Target
Audiences

Build More Effective
Strategies

Improve the
Customer Journey

Attract, Nurture, and
Convert Prospects

Transform Marketing Services with Plat.AI

Personalized customer experiences and streamlined operations are vital to a company’s success.

Plat.AI helps marketing teams:

Find their target audience
Increase customer satisfaction and loyalty to build a profitable business
Provide real-time insights to reach new and existing customers, deliver personalized ads, and maximize optimization and yield management

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We offer one-on-one support to marketing analytics teams. Our data scientists are ready to build, deploy, and maintain a real-time decision-making engine with your data.

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Key Trends in Marketing and Advertising AI

Trends in the marketing and advertising services industry are constantly changing and evolving. Keeping up with new technology may be challenging yet vital to build competitive AI marketing strategies and maintain a sense of relevance with your audience.

Conversational Marketing or Chatbots

AI-based technology is becoming a cost-effective marketing strategy where users interact with brands through chatbots. According to Global Market Insights, the worldwide market for AI-powered chatbots will be worth more than $1.3 billion by 2024. Moreover, chatbots are a powerful tool to:

Drive engagement
Improve customer experience
Boost conversion rates
Increase return on investment (ROI)

Finally, conversation marketing helps collect consumer data to provide a personalized experience.

Personalized Content

Personalized content is another key trend in AI marketing. Marketers utilize data analysis to uncover customer behaviors in real-time and use those data-driven insights to tailor their marketing.

For example, Amazon and Netflix provide personalized and tailored content to each user.

The home page content on Amazon displays products likely to interest the consumer based on their previous purchases and browsing history
Similarly, Netflix makes movies and series recommendations based on the user’s viewing history and preferred genres

Of course, none of this would be possible without artificial intelligence.

Artificial Intelligence

As we know by now, AI is the driving technology behind new digital marketing trends such as chatbots and personalized content. The technology leverages sales and marketing data to predict consumers’ next steps in the sales cycle. Therefore, marketers better understand how to predict a consumer's next move based on past behaviors. With AI-driven marketing, marketers can:

Optimize their customer journey
Improve weak points and fill gaps
Create campaigns with more targeted outreach, increasing conversions and return on investment

Three Data Challenges in Marketing

Embracing the new opportunities that AI brings to marketing is essential to remain competitive. AI-based marketing relies on an in-depth understanding of customer needs and preferences. Additionally, the ability to make real-time, data-driven decisions has brought AI to the foreground for marketing stakeholders. Nonetheless, marketing teams must be aware of the following three data challenges in the marketing industry.

Data Quality

AI tools require time and training to learn organizational goals, customer preferences, historical trends, and establish expertise. Moreover, AI tools require high-quality data that is:

Accurate
Timely
Representative

If the tool is trained with poor quality data, it will make poor decisions that do not reflect consumer desires. Therefore, stakeholders must ensure that the existing data sets are cleaned and high-quality for optimal results.

Insufficient IT Infrastructure

AI technology processes vast quantities of data. Therefore, it needs high-performing hardware and a robust IT infrastructure for a successful AI-driven marketing strategy.

However, these computer systems can be:

Very costly to set up and run
Require frequent updates and maintenance

This can be a disadvantage, particularly for smaller companies with modest IT budgets. Nonetheless, smaller companies can opt for cloud-based solutions to leverage AI in marketing. Cloud software vendors provide the necessary IT infrastructure and resources to run AI software for a modest fee.

Limited Bandwidth

As the total of AI technology companies grows, the market faces an AI skills gap. The existing pool of AI talent is not growing fast enough to fill new AI positions. Therefore, companies using AI marketing software need to ensure they have enough skilled and trained employees. Nevertheless, the AI skills gap can be closed by:

Process your data using a codeless modeling solution that requires no development experience
Use a cloud-based real-time predictive modeling engine built, deployed, and maintained by Plat.AI
Grow your data science team one role at a time as you need them

Want to Step up Your Marketing Game?

Plat’s ad management tools allow you to monitor visits, clicks, and conversions with real-time reporting that shows dozens of metrics. Also, our real-time tracking capabilities help you stay organized with an all-in-one dashboard.

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Why Plat.AI for Advertising and Marketing Technology

Real-Time Data

Make better decisions with real-time data. Manage yield more effectively using real-time advertising engagement metrics.

Data Team Collaboration

Enable data teams to collaborate and combine their data-driven insights to create new value, enhance partnerships, go-to-market efforts, and strategic initiatives.

Scale Up or Down

Easily integrate new ad experiences. Plat offers performance agencies the flexibility to set their own rules and scale campaigns.

Machine Learning Use Cases in Marketing

Customer Segmentation:

Machine learning (ML) helps marketers segment the customer base into different categories based on touchpoint engagement and purchase patterns. AI for marketers allows professionals to target the right audience with the right message and discover the channels that can yield a better return on investment.
Real-time Analytics:

ML can analyze large sets of data in real-time and bring marketing insights into campaigns. Real-time analysis allows marketers to get more details about their customers and identify the best practices.
Predictive Analytics:

Predictive analytics in AI marketing applies machine learning algorithms to predict future outcomes. For example, predictive analytics can anticipate customers’ behavior, including products they may be inclined to purchase in the future.
Recommendation Engines:

Recommendation engines provide a personalized experience and high customer satisfaction rates. The goal of these engines is to match consumers’ preferences with product features they might like based on their search history or last purchase. For example, if a customer purchases a new phone, the recommendation engine would offer them a phone cover or a power bank enabling upselling and cross-selling.
Lead Scoring:

Marketing departments utilize lead scoring to determine the worthiness of leads or potential customers through AI in marketing. They attach values to them based on past behavior relating to their interest in the company’s products. This process helps sales and marketing teams prioritize leads, respond quickly, and increase conversion rates.

Related Resources and Blogs

A Step-By-Step Guide on How to Build an AI What is Data Science and How Can it Improve Your Business? The Future is Machine Learning