Empowering CMOs: Generative AI Strategies for Modern Marketing

A report by BCG suggests that CMOs are optimistic about the potential of generative AI (Gen AI) to improve productivity and build competitive advantage. When asked to choose the words that describe the technology, they picked optimism (74%), confidence (71%), and curiosity (63%). Another report by Goldman Sachs finds that Gen AI would boost global GDP by 7% and productivity by 1.5% over a ten-year period.

Here’s how marketing campaigns can be enhanced with Gen AI:

1. Brainstorming and Idea Generation: Enlisting original ideas is the first step to capturing customer attention. Gen AI engines provide novel suggestions and alternative viewpoints to invigorate brainstorming sessions. Marketers can use these ideas to conceptualize and drive targeted content strategies. It also helps them to prevent writer’s block and become more creative in their routine work.

2. Automating Content Creation: Gen AI automates various aspects of content development, helping organizations achieve faster speed-to-market with minimal resources. Whether crafting promotional emails or social media posts and blogs, the technology helps produce a myriad of content that marketers can refine and customize.

3. Developing Multimedia Content: Text-to-image AI applications have been designed to offer captivating sketches, images, and videos. Marketers can use them for visually- rich presentations, infographics, and audio-video content to enhance storytelling and promote engagement on their organization’s social media handles.

4. Hyper-Personalization: Gen AI helps sift through vast datasets and tailor content, adapting it to individual choices and behaviors. With AI-generated content, B2B marketers can design strategic campaigns for the prospects they target, enhance customer experience, and achieve higher conversion rates.

5. Social Listening: Gen AI can also help predict emerging customer interests and market trends by analyzing social media data. Based on data analysis, an organization can make more informed decisions and steer its marketing strategies in the right direction.

With the various tasks that Gen AI handles, there is a fear that it will eventually replace human skills in a creative domain like marketing. However, the purpose of technology is simply to redefine and enrich creativity, not replace it. Organizations cannot undermine the spontaneity and emotional depth of human intelligence.

Marketing is also increasingly becoming data-centric, and AI helps to use that data to drive business outcomes. It empowers users to adjust their marketing campaigns dynamically based on changing market conditions, customer feedback, and the performance metrics of content already published across platforms. This agility enables CMOs and their teams to learn and capitalize upon new developments continuously. Where fresh and real-time data drives a campaign, its marketing collateral can also be free from bias.

With Gen AI, collecting and integrating data from different sources, such as CRM systems, customer interactions, and social media trends, enables marketers to identify customer pain points and areas for improvement.

While organizations are still in the early phase of Gen AI integration, the transformation based on this cognitive technology is on the horizon. To ensure that they are not left behind, here’s how companies can get started:

1. Start with a Road Map: Marketing leaders must define a branding future aligned with their business goals when Gen AI takes over time-, cost-, and resource-intensive tasks. From there, they can plan their investments based on organizational capabilities and customer expectations. By prioritizing use cases and establishing a training pathway for employees, CMOs can ensure synchronized efforts and effective utilization of resources.

2. Build a Team to Implement the Plan: Establishing a multi-tiered team structure is crucial for successfully executing the AI strategy. This includes creating an action office for strategy coordination, cross-functional pods for individual use case development, and a technical team to maintain a secure platform for Gen AI implementation.

3. Focus on Maximizing Value Delivery: Applying Gen AI to less complex use cases first is crucial to identify where it can deliver maximum value and what skills are required to keep such capability consistent. CMOs can then build on high-value use cases, which may be complex and need a fine-tuning of Gen AI’s basic models along with significant refinements to the first draft of the solution. As these models could be challenging to scale, both marketing and technical leadership must be involved. Continuous testing and iterating based on customer response will be necessary to guide deployment and scaling.

To maximize the advantages that Gen AI brings to marketing, CMOs must pay attention to the following best practices:

Data quality: As Gen AI heavily relies on data inputs to develop content and support decisions, ensuring the quality and accuracy of data that trains the AI models is necessary. With unbiased and relevant data for the most recent period, marketing teams will be able to prepare collateral for meaningful outcomes.

Accuracy: Before being applied to real use cases, Gen AI models must be tested for accuracy and reliability and to eliminate any risk of errors.

Transparency: As Gen AI becomes more autonomous in content creation and decision-making, transparency in its usage is imperative to avoid potential ethical problems and other unintended consequences.

Security: Gen AI systems are susceptible to cyber threats, including data theft, manipulation, and unauthorized access. While deploying any model, it is necessary to add robust measures to keep sensitive information safe and ensure the integrity of all systems involving Gen AI.

Maximizing Gen AI’s impact on an organization’s marketing strategy makes it imperative for CMOs to build and establish ethical guardrails to navigate potential pitfalls and build trust in the system. AI guardrails can be classified into three categories—ethical, operational, and legal. Each category serves a distinct purpose in directing AI conduct, ensuring the technology operates within predetermined ethical and operational limits.

Factoring in transparency and accountability in AI-driven decision-making processes is vital, and well-defined guidelines can help govern data usage and uphold privacy and consent. Moreover, auditing algorithms regularly is necessary to detect and mitigate any biases that may have crept in. Imagine a customer segmentation tool unintentionally excluding a specific age group, hindering campaign reach. Or for instance, an algorithm analyzing past customer data might prioritize advertisements for credit cards towards men, unintentionally excluding qualified women. Or say, an AI lead-scoring tool for B2B markets prioritizes contacts based on firm size, overlooking qualified, high-growth startups. Not only do these erode brand reputation, but also impede access to a potentially lucrative market segment.

A robust collaboration between technical and marketing teams is essential to uphold ethical standards and maintain public trust. Regular training programs are also crucial to educating the workforce on ethical AI usage and proactively identifying and addressing ethical, operational, and legal concerns.

Birlasoft has established its Generative AI Centre of Excellence in partnership with Microsoft and launched its Gen AI acceleration platform, Birlasoft Cogito. The platform comes with built-in tools, libraries, and frameworks to streamline and accelerate the development and deployment of Gen AI solutions for businesses. Users get comprehensive training, tutorials, and documentation to make the most of its capabilities. In addition, Birlasoft provides ongoing tech support and regular updates on the application to keep organizations attuned to the newest developments and best practices in the gen AI domain.

With Birlasoft Cogito, organizations can seamlessly integrate innovative processes and ideas into their marketing campaigns. The platform facilitates the creation of roadmaps for enhancing marketing campaigns, adapting to evolving consumer dynamics, and exploring avenues for business growth.