Artificial intelligence (AI) is the field of scientific inquiry that develops machines capable of intelligent behavior. With advances in computing technologies, businesses and industries are increasingly turning to AI as a means to create more efficient systems, identify new business opportunities and automate both simple and complex tasks.
Digital marketing is one such industry that has come under the influence of AI. While early marketing technology focused on automating simple, repetitive tasks such as lead distribution, more recent advancements have seen marketers exploring how to apply AI and machine learning (a branch of AI that gives computers the ability to learn without being explicitly programmed) to augment and simplify their workflows and make deeper connections with customers.
While many vendors tout the value of AI for marketers, it’s important to understand both the capabilities and limitations of AI technology before putting it to work.
AI and Digital Marketing
Studies show that there are still significant challenges preventing scalable AI adoption across marketing, including costs associated with machine learning expertise, lack of skills among personnel and sheer volume of data required to feed algorithms. However, even within these limitations, there are low-hanging opportunities marketers can take advantage of – including chatbots, real-time marketing and content optimization.
Using AI to create customer service chatbots is one example of the emerging digital marketing technology. While these systems aren’t yet capable of providing a fully human experience, they can be used to automate and personalize the purchase and customer service processes.
To leverage AI in their digital marketing services, marketers need to first prioritize which data streams will have the most impact on their online presence. This includes feeds from social media websites, mobile apps and points of sale as well as web-based sales channels such as e-commerce stores or retail outlets.
The data from all these sources can be combined to create a digital profile of each customer, which marketers can then use to personalize customer experiences and build more powerful campaigns.
Marketers still have to decide how much AI they want to employ in their processes. For example, marketers interested in analyzing the success of content marketing may choose to integrate machine learning technology into their content management system (CMS) to find the best performing pieces of content.
Machine learning algorithms can score each piece of content according to a number of metrics and use these numbers as a benchmark for future campaigns.
How to Integrate AI in Digital Marketing
The implications of AI on digital marketing go far beyond these technical capabilities, however – meaning marketers need to take a holistic approach and prepare for a future where AI will be an integrated part of their daily digital marketing services.
There are three main ways marketers need to adjust their approach to digital marketing in order to take full advantage of AI:
- Embrace automation.
While human expertise is still necessary, AI can automate many tasks such as data management and analysis which previously required extensive manpower. This allows marketers to scale their work and reduce the time they spend on routine processes such as preparing reports or managing customer data.
- Focus on understanding customers better, rather than just collecting more data points.
Many marketers see AI as an opportunity to collect even more information about customers for targeted marketing purposes – but this could actually harm the customer experience and make them feel like they’re being spied on.
Instead, marketers should be focusing on how AI can help them understand their customers better and provide more personalized feedback and guidance.
- Prepare for a future where AI is integrated into day-to-day workflows.
No matter what parts of marketing technology they choose to employ, marketers should start thinking about how they’ll put AI to work for their campaigns. Although this will involve additional training and retooling of everyday processes, it will not be a significant hurdle as long as the company is willing to invest in their staff over the long term.
