A recent study by Price Waterhouse Cooper (PwC) (link resides outside ibm.com) estimates that by 2030, artificial intelligence (AI) will generate more than USD 15 trillion for the global economy and boost local economies by as much as 26%. (1) But what about AI’s potential specifically in the field of marketing?
From customized content creation to task automation and data analysis, AI has seemingly endless applications when it comes to marketing, but also some potential risks. Here are some key definitions, benefits, use cases and finally a step-by-step guide for integrating AI into your next marketing campaign.
AI marketing is the process of using AI capabilities like data collection, data-driven analysis, natural language processing (NLP) and machine learning (ML) to deliver customer insights and automate critical marketing decisions. Today, AI technologies are being used more widely than ever to generate content, improve customer experiences and deliver more accurate results. Before choosing an AI tool, organizations should fully explore the different types of AI marketing applications available and look at how they’re being used by other businesses.
Examples of AI in marketing abound as more and more organizations look to it to help them improve everything from their social media posts to their email marketing and content marketing efforts. Here are some examples of ways enterprises are increasing their use of AI to help them achieve marketing goals.
As with other new technologies, there are both benefits and challenges to using AI for marketing purposes. From maintaining the quality of the large data sets needed to train AI to complying with the field’s ever-expanding privacy laws, organizations that haven’t used AI before are understandably cautious. But enterprises who have made the investment and identified an AI marketing solution tailored to their needs are enjoying many advantages.
Follow these five steps to effectively incorporate AI into your next marketing campaign.
The first step to integrating AI into a marketing campaign is to set out goals and expectations. Assess what worked and didn’t about past campaigns and outline the ways in which you hope AI can help improve your results in the future. Once stakeholders have aligned on expectations, it will be easier to choose an AI solution and set meaningful key performance metrics (KPIs) to evaluate its success.
Data scientists or engineers with a background in AI, machine learning and deep learning don’t typically sit on marketing teams, but their expertise is necessary for successful AI marketing initiatives. To address this issue, organizations have a choice—they can either make the investment to hire the data scientists and engineers they need, or they can go to a third-party vendor for help training and maintaining their AI marketing tool. Both approaches have their advantages and disadvantages, primarily around the level of investment an organization is willing to make.
One of the biggest challenges facing AI marketing solutions is the use of customer data for training and implementation purposes without violating privacy laws. Throughout the training process, organizations must find ways to maintain their customers’ security and privacy or face heavy fines.
The success of an AI marketing tool depends on the accuracy and relevancy of the data it’s trained on. AI tools that are trained on data that doesn’t accurately reflect customer intentions will fail to provide useful insights into customer behavior or make useful strategic recommendations. By prioritizing the quality of their data, enterprises can ensure that their AI solutions will help them better achieve the outcomes they seek for their marketing programs.
Organizations selecting an AI solution have many different platforms and capabilities to choose from. If they’ve followed the first four steps carefully—laying out their goals, hiring the right talent and ensuring the quality and accuracy of their data—the last step should be the most straightforward: Choosing the tool that’s right for them.
Today’s most effective AI marketing solutions utilize AI and ML technologies to enhance customer experiences and deliver meaningful insights to marketers swiftly and accurately. You can read more about IBM’s approach here. IBM watsonx Assistant is a market-leading, conversational AI platform that enables enterprises to build voice agents and chatbots that can converse naturally with customers and help them resolve their problems.
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