The buzz surrounding Generative AI is no longer confined to tech circles — it's reshaping the landscape for marketers globally.
Deloitte estimates that the Generative AI market is set to double every two years for the next decade, while McKinsey suggests that generative AI could increase marketing productivity with a value between 5% and 15% of total marketing spending annually.
As this technology becomes more prevalent, there are several critical factors that marketing teams must carefully consider before diving headfirst into implementation.
In this guide, we’ll explore the eight key questions marketing teams need to ask before integrating this powerful, cutting-edge technology. From defining clear objectives to ensuring data privacy and security, each insight aims to equip marketers with the knowledge needed to navigate the Generative AI landscape strategically and amplify their campaigns' efficiency.
But first, let’s take a look at what marketers might want to use generative AI for.
How could Gen AI support marketing efforts?
Most marketers have played around with ChatGPT for content creation by now. In fact, according to a recent report, 48% of marketers are now using AI to assist with generating content. But the truth is that this powerful tool has much more to offer marketers beyond copywriting.
Throughout the marketing measurement and reporting process, there are plenty of opportunities for Gen AI to shoulder the burden of tedious, repetitive tasks like building and maintaining the infrastructure for gathering marketing data from multiple sources.
Gen AI tools can help marketers design and implement efficient data pipelines, saving time and reducing errors. At the same time, Gen AI could massively lower the barrier to entry for advanced data transformations, marketing reporting, and campaign analysis by receiving and answering requests in plain language.
This means even non-technical marketers could perform complex queries through simple conversations. Additionally, Gen AI has the capability to optimize data storage architectures, enhance data security and compliance, and improve data quality by automating the cleaning and validation processes. You can find out more about how Gen AI could support marketers here.
8 Questions You Should Ask Before Implementing Generative AI
So, now we've got a clearer idea of how Gen AI could be put to use for marketing teams, let's take a look at the eight key questions that marketers should consider before diving headfirst into implementation.
1. Have you defined clear objectives and KPIs?
To unleash the full potential of Generative AI in your marketing endeavors, meticulous planning is essential. Start by clearly defining your objectives and Key Performance Indicators (KPIs).
Before implementation, articulate the specific goals you intend to achieve, whether it's enhancing content creation, optimizing user engagement, or streamlining data analysis. Delve into critical questions surrounding user roles, industry requirements, cross-departmental use cases, and the quantity, speed, and accuracy of insights you aim to generate. Then decide which metrics you can use to measure the success of your Gen AI implementation.
Establishing a roadmap grounded in well-defined objectives sets the stage for a purposeful integration of Generative AI within your marketing strategy.
2. Who’s going to be using the generative AI tool?
Tailoring the use of Generative AI to your team's composition and industry nuances is pivotal. Determine who within your team will be leveraging the tool — whether it's primarily data analysts or a mix of less technical team members.
Industry-specific requirements should also influence your choice between a generic or specialized Generative AI tool. By aligning the technology with your team's skill set and industry demands, you optimize its impact and ensure a smoother integration process.
3. What frequency and volume of insights do you need?
The frequency and volume of insights required by your marketing team should steer your choice of a Generative AI tool. Whether your team needs real-time updates or periodic in-depth analyses, understanding the pace at which information is required will guide the selection process. Different tools excel in delivering insights at varying speeds and frequencies, allowing you to align your choice with your team's specific needs.
4. How do your teams prefer data presentation and visualization?
Seamless integration of Generative AI into your workflows requires thoughtful consideration of data presentation and visualization. Understand how your team prefers to consume insights — whether through specific dashboards or visualization formats. Adapting the output to match your team's preferences ensures that the generated insights are not just valuable but also easily digestible, leading to better decision-making processes.
5. What level of training is required?
The effectiveness of Generative AI hinges on the accuracy of its results and the preparedness of your team to utilize the technology. Clearly establish the level of accuracy your team aims to achieve with Generative AI-generated insights. Simultaneously, assess the training requirements for your team members to wield the tool effectively. This proactive approach ensures that your team maximizes the benefits of Generative AI without grappling with accuracy issues or training gaps.
6. Is your data of high enough quality for effective Gen AI implementation?
A cardinal rule in the world of Generative AI is that the quality of outcomes is directly proportional to the quality of your data. Before delving into implementation, ensure that your data is reliable, complete, secure, trustworthy, understandable, and actionable. A robust data foundation is the bedrock of optimal results, preventing the infamous 'garbage in, garbage out' scenario that could compromise the efficacy of your Generative AI applications.
7. Have you addressed data privacy and security concerns?
Given the sensitivity of data, prioritizing privacy and security is non-negotiable. Establishing clear policies governing the use of Generative AI within your organization is essential. This includes delineating guidelines on how employees interact with the technology and ensuring responsible and ethical usage. Build a comprehensive privacy and security policy tailored to your company's specific needs, addressing potential risks and safeguarding against unauthorized access or data breaches.
8. Is human-machine collaboration prioritized as a copilot, not autopilot?
Incorporating Generative AI into your marketing strategy requires a nuanced understanding of its role as a collaborator, not a replacement. Communicate within your organization that Generative AI models excel at pattern recognition on a massive scale, dispelling any notion of magical capabilities. Emphasize the symbiotic relationship between humans and machines — Generative AI serves as a copilot, enhancing human capabilities rather than steering the wheel on autopilot. This approach ensures a balanced integration, preventing over-reliance on AI and maintaining vigilant human oversight.
As you embark on your Generative AI journey, remember that it's not about humans versus machines—it's about humans with a machine that can do more. By addressing these key considerations, marketing teams can harness the power of Generative AI to drive efficiency, productivity, and innovation in their campaigns.