Potential of AI in MarTech
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The rapid increase in generated content volume demands quick responses and flexibility from marketers to attract and retain customers. However, traditional methods are struggling to keep up with these demands, making them ineffective. This acceleration in the marketing cycle requires faster reactions and approaches such as implementation of AI in MarTech.
In today's digital landscape, 84% of publicly available data is composed of image and video content. This emphasizes the significance of analyzing and understanding visual data effectively in various fields, including research, marketing, and data analysis. Visual content, particularly video and images, is undeniably the future of digital marketing.
Traditional research faces challenges in evaluating bias and blind spots, often requiring significant time and resources. Old SaaS tools may lack transparency in data origin and flow, exacerbating the handling of large volumes of visual data.
Over the past decade, SaaS MarTech tools with traditional analytics and AI components have emerged to address the influx of unstructured data from public resources, which is growing exponentially. These tools enable the processing of new data volumes, but their legacy includes large models and outdated data sets, raising concerns about data filtering and bias.
- People are needed to strike a balance between traditional and innovative solutions and adapt to the new realities of a rapidly changing market and regulations that restrict the operations of AI. They are required to provide a data source and comply with API rights. Privacy regulations will gradually limit access to previous channels of information and insights, where data was purchased by B2B and presented as conclusions, whether it be through research or SaaS tools. In the following report, we will provide detailed cases and examples to illustrate our perspective on the future direction of the market.
The significance of marketing technology is on the rise for businesses. Budgets allocated to AI in MarTech are increasing and projected to further expand in the coming 12 months. Moreover, businesses recognize AI in MarTech as a critical factor in meeting customer expectations.
The MarTech market is growing, but it faces significant challenges and changes. First of all, marketers are fighting tough economic conditions; the current state of MarTech maturity; the challenges around people and skills; the tools are adding and upgrading them; and the business challenges they use tech to address the changes which are not directly obvious and related to marketing, for example such as increasing privacy responses, cookie-less future.
AI is a game changer in the coming years because it changes the way we interact with computers, changes the creative industry and creative tasks, changes the way we analyze the data and take key decisions, and AI changes the way an organization operates. AI is a powerful force which would allow the companies to connect the dots between what is happening in the business, why it is happening and using data gleaned to act in the way it helps to make the customer experience as seamless as possible.
In First Bridge we believe that the potential of AI is incredible at any stage of the marketing process: from planning marketing campaigns, scheduling it and media planning to sophisticated customer segmentations, ROI calculation, or selling intelligence process automating and omnichannel approach. On the canvas below, we have depicted a section of the process for organizing a marketing campaign, along with the required tasks (or key jobs-to-be-done). Additionally, you can include potential obstacles at each stage. We highly recommend creating and utilizing similar canvases within the company during internal workshops. This will provide a deeper understanding of your marketing department's needs and help identify the right processes and technologies for their successful operation. Or where are the use cases for AI implementation to succeed.
Figure: Example of Canvas For Internal Marketing Campaign Organization, First Bridge
AI has Numerous Opportunities as well as Challenges and Limitations for AI in MarTech Industry
Imagine how in the past, a marketer had to analyze an enormous dataset of consumer feedback on a new product release. This would have required weeks, possibly even months, of manually sifting through surveys, analyzing focus group discussions, and summarizing the results. However, with the aid of LLMs (Large Language Models), the task is now accomplished in just a few days.
Earlier a marketer or market researcher had to collect data manually through face-to-face interviews, relying solely on self-reported results. Now, thanks to advanced AI analysis tools and vast data, it is possible to track real behaviors, assess self-attitudes expressions, and simultaneously evaluate digital marketing campaigns on a global scale, all in real-time.
A new generation of AI tools solutions have emerged, which are sourced, flexible, and unbiased. These tools steer clear of any negative legacy or reliance on low-quality, outdated data. Secondly, we are examining the active efforts of regulators to enforce stricter data privacy laws.