AI for marketing

The potential for infusing generative AI into marketing

Introduction

Digital technology has profoundly transformed marketing by enabling real-time, personalized interactions with vast audiences, and by providing a level of measurement that was previously unattainable. The shift has ushered in a new era of accountability, where the effectiveness of campaigns can be precisely measured, optimized, and iteratively improved, bridging the gap between businesses and their customers like never before.

Now, with the maturity of artificial intelligence (AI), and the emergence of generative AI, marketing is being further redefined by the availability of enhanced data analysis, personalization, and automation capabilities. AI can analyze vast sets of customer data to identify patterns, segment audiences, and predict consumer behaviors, allowing businesses to craft more targeted and effective campaigns. With generative AI where tools can take inputs and create original outputs such as fresh copy or new visuals, marketing campaign materials can be produced more efficiently, and new forms of customer interactions are appearing.

This fusion of AI with marketing has many advantages in dealing with the common challenges marketers face: by providing a more personalized, timely, and engaging experience for consumers, enhancing brand loyalty, and boosting sales. It can help with productivity and streamlining operations so teams can concentrate on higher value tasks. As an example, it is particularly useful at creating summaries from in-depth customer interviews. It also opens up new potential for marketing and new strategies that would not have been possible previously. For instance, it can help small organizations think about their brand identity and how this can differentiate them: something previously only available to large organizations with big marketing budgets. How does this work in practice? Let’s look at key areas from strategy, through to execution, operation, and analysis.

Marketing strategy & AI

A good marketing strategy lays out a company’s overall approach to reaching its target audiences and achieving its business objectives. It guides the selection and execution of marketing tactics across different channels. In developing a marketing strategy, you need to consider factors including market research, audience segmentation, competitive analysis, unique selling propositions (USPs), positioning, and key performance indicators (KPIs). AI has a key role to play in many of these aspects of marketing strategy. Let’s look at a few areas.

Summarizing audience interviews

A key part of market research involves talking to customers. Going through reams of customer interview transcripts and looking for patterns and similarities can be a time-intensive task. Here AI can be a great help: once an interview is transcribed, AI can quickly create a summary to pinpoint and present key points from the conversation. It doesn’t stop there; AI can also conduct sentiment analysis, gauging the underlying emotion behind statements. Categorizing the interview content into specific themes helps you swiftly distill and analyze core insights from vast amounts of interview data.

Creating personas

Generative AI can enhance the creation of personas by sifting through vast amounts of data to identify patterns, behaviors, and preferences that might be elusive to human analysis. As generative AI systems are trained on massive amounts of internet data, they are well-suited to building detailed customer personas that are not just based on broad strokes or assumptions but are rooted in actual user behavior and preferences.

You can get a detailed persona that includes areas like detailed demographics (age, location, background, education, etc.), lifestyle habits, shopping choices, values, influences, and more. This can really help with everything from determining marketing channels to key messages.

Keyword research for search engine optimization (SEO)

Generative AI systems are good at identifying the most relevant and effective search terms for a particular topic or niche, as they have been trained on large parts of the public internet. They can identify emerging terms, long-tail keywords, and semantically related phrases. These keywords are particularly useful for SEO, but they also have a role to play in other aspects of marketing such as determining key messages for an event or campaign.

Marketing execution and AI

Generative AI has a big role to play in marketing execution. A major pain point for many marketing teams is how you can scale your efforts and create meaning differentiation so your marketing stands out. Pairing marketing execution teams with generative AI tools can create efficiencies but also open up new marketing opportunities. Note that to achieve true differentiation, the best use of these tools is as a starting point to lay out the broad strokes of creative, and then have marketing professionals add a level of personality and differentiation on top. Here are just a few ways this can be achieved.

Generative AI and content creation

Whether it is writing an ad for Instagram, copy for a website or the script for a video, generative AI tools can help with the creative process. For instance, when considering website content, you can use generative AI tools like OpenAI’s ChatGPT and Anthropic’s Claude for everything, from coming up with a site structure, to creating first draft of web pages, and creating the meta-tags needed for SEO.

When it comes to creating promotional videos, these same tools can help with script generation. Text-to-image generative AI tools like Midjourney and Adobe Firefly can create realistic visual elements, animations, or even entire scenes, reducing the need for costly physical production. When it comes to editing, AI tools can enhance video quality, stabilize shaky footage, upscale resolutions, and even color-correct scenes.

Creating ads with generative AI

Generative AI tools can suggest ad creatives, including visuals, copy, and calls-to-action, tailored to resonate with specific audience segments. Furthermore, it can A/B test variations in real-time, swiftly identifying and amplifying the most effective content. This is one area where it is especially worth noting that these tools are reflective of the whole internet and so do not excel at creating stand-out ads. Especially in terms of ad copy, these tools help copywriters start their process and ideate, but often require further refinement to help make the ad stand out.

One way to achieve this differentiation and move the ad creation process into new territory is to use psychological models like Maslow’s Hierarchy of Needs or the Jungian archetypes to explore different motivators that will attract your audience. Using these techniques and leaning into emotional levers has the added impact of creating a more lasting impression rather than just relying on the more product-driven, transactional aspects of your offering.

Using AI to create new experiences

Whether its creation of chatbots to help answer pre-sales questions, or a website cost-calculator, AI tools are greate for creating tailored interactions that can make you stand out from your competitors and guide users in their purchase journey. Augmented reality (AR) and virtual reality (VR) experiences, powered by AI, can provide immersive product showcases or virtual try-ons at events. AI-driven recommendation systems can simplify a complex website and suggest products, content, or next steps based on a user’s behavior. By integrating AI across the user journey, marketers can craft interactive experiences that are not only captivating but also contextually aligned with user needs.

Account-Based Marketing and generative AI

Targeting specific high-value accounts and users is a rapidly-growing area of marketing. If you have a large customer database, AI tools can help identify which accounts should be targeted. By predicting which accounts are most likely to convert, AI ensures that marketing efforts are directed efficiently.

One of the cornerstones of ABM is delivering personalized content to each target account. AI can automate this personalization by analyzing data from each account to craft tailored messages, recommend specific products or services, or even adjust the timing of outreach.

Marketing operations

Empowering marketing teams to function efficiently and effectively is a key component to marketing success, and this is where marketing operations can play a pivotal role, helping align marketing goals with business objectives.

Technology platforms are increasing in adoption, whether it is for marketing automation and customer relationship management (CRM), data management and analytics, campaign planning and execution, budget management, or performance measurement. All these systems are increasingly using AI to bolster capabilities.

AI can automate a myriad of repetitive marketing tasks performed by marketers, enhancing efficiency and accuracy. For instance, if a product marketer has to share common information around a product feature and benefits, these can be fed into a generative AI system that can then suggest different outputs for each channel, whether that’s collateral, social media, website content, etc. By handling these and other operational tasks, AI allows marketers to focus on more strategic initiatives and the more creative aspects of the job.

Marketing analysis and AI

Marketing analytics provides indispensable data-driven insights that help organizations measure and optimize marketing performance, tailor messaging and experiences, learn from historical trends, improve accountability, and respond quickly to changes.

AI significantly amplifies marketing analysis by processing vast volumes of data at unparalleled speeds to uncover insights, patterns, and predictions that would be challenging for humans to discern. AI can help guide marketing strategy in a data-rich landscape and drive greater efficiency and returns on marketing activities.

Turning data into insights with AI

By analyzing real-time marketing campaign performance, AI can recommend optimizations, detect anomalies, and even predict the success of future campaigns. Thus, AI transforms marketing analysis from a traditionally reactive process to a proactive, predictive approach.

Automating reporting

AI can automate marketing reporting by integrating disparate data sources, conducting real-time analyses, and presenting insights in intuitive formats without manual intervention. Automated dashboards can be generated to visualize performance, and predictive analytics can forecast future trends. This enables marketers to focus on strategy and decision-making rather than data wrangling and manual report creation.

Conclusion

As you can see, AI has a role to play throughout the marketing function, and those marketing teams that can identify the greatest areas of opportunity stand to make the biggest gains from using AI.

Whether it is using AI for building a marketing strategy more directly tailored to the customer, upping the level of marketing execution, or pinpointing the pockets of greatest marketing performance, now is the time to start exploring the possibilities.

How to get started infusing AI into your marketing

Performing an audit across marketing teams to understand where are the greatest challenges and where are most marketing dollars being spent is a good first step. This can help direct initial pilots that have the best chance of showing early value.

One of the main advantages of generative AI tools over previous AI solutions is that they can be applied relatively easy to a wide array of use cases with minimal fine-tuning. Keeping up with how these tools are used by creatives and thinking how that can apply to your organization is one way to find new areas of opportunity that go beyond performance enhancement, and open up new strategic opportunities. For all your AI projects, at the outset define benchmark KPIs and continually monitor progress to set yourself up for the greatest chance of success.

Look for where you have data available and where you might be able to create a sandbox to test a proof-of-concept or validate feasibility and potential value. Continuously seek feedback from end-users and stakeholders, refining the solution based on real-world application. Remember to consider any ethical implications and potential biases in AI models to ensure fairness, transparency, and trustworthiness in your AI-driven solutions.

Man and machine typically leads to better results

As you can see with many of the examples shared here, coupling AI tools with marketing professionals leads to better marketing performance than letting AI tools loose on their own. While generative AI tools often generate useful outputs, creating standout marketing typically involves taking this input and refining it to get to the point of differentiated content that will make you stand out ahead of your competitors. This will be even more important as your competitors start adopting these same tools. You need to act now to build sustained marketing advantage.

Resources

AI-powered marketing and sales reach new heights with generative AI
A detailed post from McKinsey including stats on current adoption rates and a guide to getting started with generative AI for marketing.

How to design an AI marketing strategy
A useful guide from the Harvard Business Review on thinking through strategic development, although note that this predated the emergence of generative AI and so doesn’t take that into account.

The role of artificial intelligence in marketing
A good article from Sprout Social on how AI is currently being used in marketing, and what are the opportunities for this technology.

Generative AI for business leaders
A nice course that talks through the business imperative behind generative AI and how to think about adoption into business. (LinkedIn Learning account required).

An explainer on the technology underpinning Generative AI
A simple page-level tutorial on Large Language Models (LLMs) and the technology that underpins them.

Research on how marketers are using AI
Forbes coverage of research on how marketers are currently using AI: whether that’s across different areas of marketing or the tools that are used.