WHAT IS AI MARKETING?

What is Artificial Intelligence (AI) Marketing?

AI marketing uses artificial intelligence technologies to make automated decisions based on data collection, data analysis, and additional observations of audience or economic trends that may impact marketing efforts. AI is often used in marketing efforts where speed is essential. AI tools use data and customer profiles to learn how to best communicate with customers, then serve them tailored messages at the right time without intervention from marketing team members, ensuring maximum efficiency. For many of today’s marketers, AI is used to augment marketing teams or to perform more tactical tasks that require less human nuance.

AI marketing use cases include: 

data analysis

natural language processing

media buying

automated decision making

content generation

real-time personalization

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WHAT IS AI MARKETING?

Many companies - and the marketing teams that support them - are rapidly adopting intelligent technology solutions to encourage operational efficiency while improving the customer experience. Through these platforms, marketers are able to gain a more nuanced, comprehensive understanding of their target audiences. The insights gathered through this process can then be used to drive conversions while simultaneously easing the workload for marketing teams.

What is Artificial Intelligence (AI) Marketing?

AI marketing uses artificial intelligence technologies to make automated decisions based on data collection, data analysis, and additional observations of audience or economic trends that may impact marketing efforts. AI is often used in marketing efforts where speed is essential. AI tools use data and customer profiles to learn how to best communicate with customers, then serve them tailored messages at the right time without intervention from marketing team members, ensuring maximum efficiency. For many of today’s marketers, AI is used to augment marketing teams or to perform more tactical tasks that require less human nuance.

AI marketing use cases include: 

data analysis

natural language processing

media buying

automated decision making

content generation

real-time personalization

The Waste In Advertising - Stats and Solutions of MisattributionComponents of AI in Marketing

It’s clear that artificial intelligence holds a vital role in helping marketers connect with consumers. The following components of AI marketing make up today’s leading solutions that are helping to bridge the gap between the expansive amounts of customer data being collected and the actionable next steps that can be applied to future campaigns:

Machine Learning

Machine learning is driven by artificial intelligence, and it involves computer algorithms that can analyze information and improve automatically through experience. Devices that leverage machine learning analyze new information in the context of relevant historical data that can inform decisions based on what has or hasn’t worked in the past.

Big Data and Analytics

The emergence of digital media has brought on an influx of big data, which has provided opportunities for marketers to understand their efforts and accurately attribute value across channels. This has also led to an over saturation of data, as many marketers struggle to determine which data sets are worth collecting.

Privacy

Consumers and regulating bodies alike are cracking down on how organizations use their data. Marketing teams need to ensure they are using consumer data ethically and in compliance with standards such as GDPR, or risk heavy penalties and reputation damage. This is a challenge where AI is concerned. Unless the tools are specifically programmed to observe specific legal guidelines, they may overstep in what is considered acceptable in terms of using consumer data for personalization.

Getting Buy-In

It can be difficult for marketing teams to demonstrate the value of AI investments to business stakeholders. While KPIs such as ROI and efficiency are easily quantifiable, showing how AI has improved customer experience or brand reputation is less obvious. With this in mind, marketing teams need to ensure they have the measurement abilities to attribute these qualitative gains to AI investments.

Deployment Best Practices

Because AI is a newer tool in marketing, definitive best practices have not been established to guide marketing teams’ initial deployments. 

Adapting to a Changing Marketing Landscape

With the emergence of AI comes a disruption in the day-to-day marketing operations. Marketers must evaluate which jobs will be replaced and which jobs will be created. One study suggested that nearly 6 out of every 10 current marketing specialist and analyst jobs will be replaced with marketing technology.

How to Use AI in Marketing

It’s important to begin with a thorough plan when leveraging AI in marketing campaigns and operations. This will ensure marketing teams minimize costly challenges and achieve the most value from their AI investment in the least amount of time. 

Before implementing an AI tool for marketing campaigns, there are a few key factors to consider:

Establish Goals

As with any marketing program, it is important that clear goals and marketing analytics are established from the outset. Start by identifying areas within campaigns or operations that AI could stand to improve, such as segmentation. Then establish clear KPIs that will help illuminate how successful the AI augmented campaign has been – this is especially important for qualitative goals such as “improve customer experience.”

Data Privacy Standards

At the outset of your AI program, be sure that your AI platform will not cross the line of acceptable data use in the name of personalization. Be sure privacy standards are established and programmed into platforms as needed to maintain compliance and consumer trust. 

Data Quantity and Sources

In order to get started with AI marketing, marketers need to have a vast amount of data at their disposal. This is what will train the AI tool in customer preferences, external trends, and other factors that will impact the success of AI-enabled campaigns. This data can be taken from the organization’s own CRM, marketing campaigns, and website data. Additionally, marketers may supplement this with second and third-party data. This can include location data, weather data, and other external factors that may contribute to a purchasing decision.

Acquire Data Science Talent

Many marketing teams lack employees with the necessary data science and AI expertise, making it difficult to work with vast amounts of data and deliver insights. To get programs off the ground, organizations should work with third party organizations that can assist in the collection and analysis of data to train AI programs and facilitate ongoing maintenance.