AI has revolutionised digital marketing by utilising automation, personalization, and data analysis. AI is used by marketers to target particular consumers, gather data, and improve campaigns. With a CAGR of 11.1%, the global market for AI in marketing is projected to reach $35.13 billion by 2025. Artificial Intelligence powers digital marketing through automation, ad optimisation, and customised recommendations.
The increasing importance of digital channels is expected to result in a $455 billion global spend on digital advertising by 2023. Artificial Intelligence (AI) will have a significant impact on digital marketing in the future, leading to improved outcomes and innovation.
Impressive features of generative AI include the ability to create virtual characters, discover anomalies, transfer styles, amplify data, personalise recommendations, and generate content. It can construct virtual characters, detect abnormalities, transfer artistic styles, develop fresh content across many mediums, and offer personalised recommendations. The field of generative AI is developing quickly and has the potential to completely transform several industries.
Generative AI has the potential to change the way we work. Could it be the next step toward reshaping marketing, helping you focus more on customers?
Recently, there has been a lot of talk about generative AI, but along with this excitement, there are many myths and misunderstandings about how it may benefit marketers. In the post-cookie era, marketers may leverage generative AI to preserve consumer loyalty and get insights, particularly as personalization becomes more and more expected.
We’ve previously seen how AI can support decision-making for salespeople, commerce teams, marketers, and other stakeholders. This is only a small sampling of the ways in which brands may leverage AI in their marketing to increase productivity and efficiency.
When we questioned marketers how this technology will benefit them, 60% of them responded that it will change their function. More than half (51%) already use generative AI in their work or are experimenting with it.
Marketers that participated in our poll indicated that generative AI might save them five hours a week, or more than one month annually. With that extra time, just think of all the things you could accomplish.
Here are three ways marketers can employ generative AI right now to improve consumer connections, even if the technology is still in its early phases.
What generative AI for marketing could look like
Writing marketing collateral or responding to consumer inquiries quickly are tasks that generative AI may assist with. However, organisations can do much more with this technology than that.
Companies can be empowered to act on real-time insights by combining generative AI with an intuitive consumer data platform. This can assist you in providing personalised content at scale, including product recommendations made to specific clients based on their browsing and purchasing patterns.
Customers anticipate that brands will use their information to provide more customised offerings. Our research revealed that when information moves between departments, more than 60% of consumers anticipate that businesses to respond right away with the most recent data. This customer need can be met by generative AI, which provides agents with instantaneously created suggested solutions based on real time data.
3rd-party cookie replacement
The deprecation of third-party cookies and gaining access to high-quality, valuable, and well-structured data is becoming increasingly difficult for marketing firms. We found that 41% of corporate executives attribute their inability to understand data to its complexity or lack of accessibility.
With data collection, storage, and analysis becoming more and more challenging, marketers may now rely on AI solutions to help them assess the data they do have and make the best choice. AI will give marketers valuable insights by processing their current, possibly sparse, first-party data.
According to 63% of marketers, reliable first-party data is necessary for generative AI to function well. The success of generative AI is also greatly dependent on marketers, with 66% of them believing that human control is required.
The Last Mile of Personalization
Cookieless marketing is the way of the future, with third-party cookies being progressively phased out on platforms including Apple, Firefox, Safari, Google Chrome, and even Safari. Experts firmly believe that less successful targeted advertising will arise from these new restrictions. But do not fret. In this case, generative AI can still be useful.
Code generation using natural language input is simplified by generative AI. Coders and software developers are freed up to work on tasks that require human involvement instead of doing tiresome tasks like error detection, code completion, and optimisation.
Text or Content Generation
Text Generative AI uses natural language processing algorithms and large language models to automate content creation. These models work with large datasets of existing content samples to analyze engaging content patterns and styles.
Besides generating unique ideas, AI-generated text can be used for various purposes in content creation, like creating content through emails, social media, or blog posts, scripting and storytelling for videos and commercials or creating clear, concise, and attractive product descriptions.
Create Visual Content
Visual content is becoming increasingly important. Creative AI can be used to create personalized visual content for each customer. For example, an AI algorithm can analyze a customer’s social media activity and create personalized videos showcasing products they may be interested in.
Generative AI can automate image generation using deep learning algorithms and generative adversarial networks (GANs).
Letting you focus on the Customer
It’s imperative that we refocus on generative AI. By eliminating the uncertainty and latency involved with data processing, generative AI eliminates the labor-intensive processes related to content creation. Product descriptions that are accurate, captivating, and optimised for search engines can be written with this technology.
Generic AI takes care of menial tasks, allowing marketers to focus on more important tasks like concept execution, customer connection building, and strategic campaigns. Because generative AI allows teams to focus more on the customer, where it belongs, it has the potential to significantly change the way that MarkOps operate.
Content Marketing Automation and Search Engine Optimization (SEO)
Generative AI helps organisations find relevant, high-performing, SEO-friendly keywords and phrases for their digital campaigns by analysing large data and identifying trends in customer behaviour.
Marketers can utilise generative AI technologies to generate content ideas, investigate keywords, look for relevant content titles, determine purpose for group searches, and create content structure while developing SEO content.
Brands may use generative AI to quickly create message variations that align with their language and style for customer touchpoints including emails, websites, and mobile messaging.
Through data analysis and pattern recognition, generative AI may assist marketers in optimising their efforts and enhancing campaign performance. An AI system, for instance, is capable of analysing consumer data to determine which channels and messages work best for certain client categories. Campaign optimisation and ROI can be increased with the usage of this data.
Get to know your Customers better through Automation
Customer surveys are automated by generative AI, which enhances the capabilities of conventional data collection and analysis. It examines patterns of consumer engagement to provide insights into what consumers are thinking about the goods and services. By coming up with fresh inquiries in response to feedback and behaviour from customers, it also sheds light on their wants.
Customised Customer Segmentation
Accurately segmenting customers is essential to personalising their experience. Target client segmentation is made easier by artificial intelligence, which gathers and analyses data from various sources. It displays distinct patterns in the behaviour of various client segments as well as new trends in those groups. Marketers can use this data to create segment-specific strategies.
Conversational agents and virtual assistants can be created with generative AI. These AI-powered chatbots can help businesses improve customer assistance and customer engagement by instantly responding to consumer inquiries. Lastly, predictive analytics will probably employ generative AI more and more. Generative AI can assist businesses in identifying patterns and trends in vast amounts of data so they can utilise that information to make better educated decisions. Generative AI, for instance, can identify which channels would work best for a campaign or forecast which products will probably be popular with particular demographic groupings. All things considered, generative AI’s future in marketing appears to be quite bright. As AI technology develops, we may observe more companies utilising this potent tool.