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Digital Marketing
Published:
July 2, 2023
Updated:
February 2, 2024

What Does It Mean to Democratize AI for Marketing?

Mitha Shameer

What Does It Mean to Democratize AI for Marketing?

Published:
June 30, 2023
Updated:
February 2, 2024
Mitha Shameer

Highlights

As a marketer, you rely on data for multiple things: understanding customer needs, product perception, and social media engagement. But getting your hands on that data can be a fiddly process. 

Data, in its raw form, is as effective to us as a puzzle without the picture. As marketers, the best way we can leverage data is when it comes to us in its simplest consumable form which we can directly use. But not only is it challenging to access all these data, but it can significantly cut into your team’s time and budget.

The good news is that software giants like Adobe and Microsoft have significantly simplified the process of eradicating data silos and effectively democratizing AI. As a result, many firms are quickly adopting democratized AI to boost operational effectiveness and improve the customer experience.

It's simple to guess what business executives mean when they talk about democratizing artificial intelligence (AI). More breakthroughs are definite the more people have access to the expertise, resources, and data needed to create an AI system. Engagement rises as effectiveness grows.

What does it mean to democratize AI in marketing?

Similar to how in a democracy, representation matters, AI democratization means giving everyone access to intelligence so they can reap its benefits. 

It means making AI more transparent and accessible to people who are not tech experts. This can be done through supporting open-source AI software, promoting ai-driven cloud-based platforms, and providing training and instructional resources for a better understanding of AI.

In addition to AI appearing daunting, many businesses find it expensive to employ AI to make smart marketing decisions. AI democratization enables everyone in your marketing team to access intelligence and use it to observe and detect patterns, make forecasts, and utilize this knowledge to take targeted actions. 

Why you should use democratized AI in marketing

There are several use cases for integrating democratized AI marketing into your digital marketing initiatives, and each of these use cases has advantages of its own. 

Minimized entry barriers

One of the most obvious benefits of AI democratization is reduced entry barriers. You can train AI models on the cloud, making it easy to learn AI without the burden of significant financial investment. Whether it is tracking user data using ML algorithms or anticipating the future needs of customers through predictive analytics, AI is paving the way for more tailored and personalized experiences.

Improved customer relationships

Think of an AI model that can process and understand human language. The implications of artificial intelligence in marketing are enormous. A bespoke dataset can be used to train any natural language processing (NLP) model from the transformers' library for a specific application. 

The NPL technology enables you to offer your customers around-the-clock assistance with chatbots and other AI tools. Additionally, it allows digital marketers to see customers who are at risk and reach out to them with the right content for re-engagement.


Faster decision-making

Utilizing AI marketing tools speeds up the process of sifting through reams of data, which is otherwise expensive and strenuous. With AI democratization, your team members now have more time to concentrate on strategic projects that will eventually guide campaigns with AI support. AI marketing empowers digital marketers to use real-time data to make decisions early on in their campaigns, saving time and money.


Boost campaign ROI

Democratizing AI lowers the overall cost necessary to develop AI solutions. Companies create effective and practical AI systems for a plethora of applications using open-source data, algorithms, and models on the cloud. 

Marketers can increase ROI without squandering funds on ineffective attempts by carefully evaluating customer insights and understanding their needs. They can also reduce operational costs by completing more tasks with a smaller staff in less time. 


AI marketing use cases with examples 

Businesses can benefit from the democratization of AI to develop a thorough marketing strategy. Here are some examples of AI in marketing.

Chatbots 

Thanks to natural language processing with the democratization of AI, chatbots are already being used to augment customer service professionals. Customers can use chatbots for more straightforward inquiries, sparing the representatives to handle complex demands that require more human nuance.

Companies such as Sephora can answer the queries of thousands of customers by adopting chatbot technology. The Sephora chatbot helps you look for foundations and narrow down product choices via quizzes, making the experience more fun and less overwhelming for the user. 


Media Buying

You want your target audience to engage with your ads at the right time to boost revenue and engagement. This is made possible through AI with customized adverts. When you democratize AI, you get access to data on preferences, geography, past purchases, buyer intent, and other factors to target the right channels at the right time for a reasonable budget.

Facebook is an outstanding example of this in action. To surpass the competition and increase its market cap, Facebook places a strong emphasis on tailored advertising.


Content moderation and generation

You can use AI to increase the productivity of your content team by automating certain aspects like social network content curation, personalized reports/messages, and email content. 

A five-year contract was reached by Chase Bank and Persado, a business based in New York that uses artificial intelligence in marketing. Chase discovered that integrating machine learning in their copywriting helped them attain more humanity in their marketing after evaluating Persado's suggestions.


Granular Personalization

To generate a more detailed customer profile, AI marketing must consider elements such as users' interests, past purchases, location, and previous brand interactions. The data can then be used to curate tailored content to boost conversion rates and enhance the customer experience.

For instance, Spotify employs AI marketing technologies to generate tailored playlists based on what a user has previously listened to, the hottest songs right now across genres, and what music is trending.


Predictive Marketing Analytics

Predictive analytics, which uses a combination of machine learning, algorithms, and datasets to anticipate future behavior, is made accessible to marketing teams thanks to the democratization of AI. It assists you in deciding which products to promote and to whom in order to increase sales. 

For example, Amazon makes product recommendations to customers based on their past purchases and behavior, which boosts conversions and customer satisfaction.

In order to recognize locations, objects, and activities in photos and videos, image recognition uses deep learning to find patterns in the data. As a result, you can gain more knowledge about your customers and automatically tag and label products as necessary. 

Facebook's DeepFace is one example of an image recognition system. Along with analyzing images for tags and descriptions, it trains its AI models to enable accurate recognition with little room for error.


Dynamic pricing

By providing dynamic pricing, AI marketing aids in increasing brand competitiveness. It's a pricing technique in which the price of a product is determined by demand and/or supply in real time by analyzing vast amounts of data. It enables businesses to raise sales, differentiate themselves from rivals, and modify prices to match the demand for particular products.

For instance, when there is a decline in demand for a product, customers can gain from dynamic pricing. The unsold state of hotel rooms is a prime illustration of this. Dynamic pricing can provide competitive pricing to draw customers, which in turn reduces the likelihood of a vacancy.


Social media marketing

Ai-driven tools can help with social media marketing by creating social posts for various channels and platforms. These tools also help with distribution strategy by automating schedules and publishing timelines across various platforms, suggesting hashtags, monitoring engagement and tracking analytics in real time with helpful insights. Integrate online proofing tools into this process for seamless collaboration, ensuring that the visual content aligns perfectly with your brand message and engages the audience effectively.

Wrapping up

Artificial Intelligence has advanced significantly in the last few years, with many businesses adopting the technology in their digital marketing campaigns. With the marketing landscape turning more cutthroat, AI-powered marketing tools is a must if you want your business to have a competitive edge over others.

Thanks to AI democratization, it’s easier to leverage AI in marketing for increased campaign performance, improved customer experience, or better marketing operations efficiency. 

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