There’s a lot of hype surrounding Artificial Intelligence (AI) in the Marketing world – and for good reason. As marketers, we know that intelligent technology can transform our industry for the better and eventually lead to more impactful experiences for current customers and prospects alike.
However, there have also been discussions about whether AI applications for Marketing are truly ready for prime time, or even if they should be used on their own at all.
AI is truly just the higher level, a broader category of emerging technology that aims to enable machines to do the business-critical thinking that marketers have traditionally done manually. If marketers think about applying AI to their day-to-day, tactical tasks, they have the potential to not only alleviate the grueling manual work involved but also to execute them perfectly every time – minus the distractions, fatigue, and errors that are inherent to humans.
The following are four specific ways AI has changed data processing and management in the Marketing world:
Stronger Optimization of Data in Assets
AI helps marketers automate the enrichment and tagging of Marketing assets (i.e. content, images, videos) so they can make better use of their assets and Digital Asset Management (DAM) solutions. This technology can also perform critical thinking tasks, such as speech-to-text capture, sentiment analysis, and image use recommendations for assets.
Through automating these essential but time-consuming processes, marketers will have the advantage of a more robust DAM solution in addition to:
- Improved content reuse
- Decreased asset search time
- Decreased content creation costs
- The delivery of richer experiences
- Increased user satisfaction with their DAM, because it’s now making their job easier when they find and select assets
Enhanced Capabilities for Gathering and Using ROI Data
AI assists marketers with becoming more accurate in financial data processing and predictive modeling as it’s able to combine content productivity metrics with creation costs in order to provide accurate and timely ROI analyses. This helps organizations become more agile, providing them with the ability to make stronger data-driven Marketing decisions, like identifying or removing low-performing assets and adjusting activities in-flight to maximize performance – both of which improve top-line revenue and bottom-line performance costs.
New Use of Resource Data
AI helps marketers make greater use of previously stagnant resource data through processing and analyzing it to determine how much time their business took to make it an asset, the current workload, and the capacity of each of its staff members and external agencies. With that said, marketers have taken such analysis to make data-driven decisions as automatically routing or re-routing tasks to more available or better capable resources. This results in:
- Increased percentage of on-time projects
- Improved employee satisfaction
- Increased quality with first-time approvals on assets
- Increased production to maximize existing resources
Improved Use of Customer and Prospect Data
AI solutions help marketers better manage their customer and prospect data by performing an automated analysis of previous content interactions or buyer persona content needs. Then, the technology recommends content that would more accurately resonate with these groups based on this data.
The optimized data management helps marketers deliver stronger customer experiences because it ensures that they create and publish the type of content their customers (and prospects) desire. This often results in:
- Increased return on marketing investment
- Increased overall revenue
- Increased budgets for content/campaign creation
- Improvements in conversation rates and buyer journey progressions
Although AI has numerous potential applications in Marketing, it can never completely replace the various roles of human marketing teams such as human creativity, common sense or the emotional thinking that only people can make.
As some early adopters have experienced, AI has indeed transformed the basic, rote data processing and management tasks in Marketing through automating overhead and expediting the analysis of performance data. As a result, organizations can have the most accurate, timely data at their fingertips to help them make smarter decisions across the enterprise.
Read more: AI and the Future of Content Management