9 Data-Driven Ways to Use Generative AI for Marketing

The rapid rise of generative AI has become the most captivating trend in the tech industry today. 

Prompted by predictions of massive economic impact and the disruption of multiple industries, professionals in many fields are assessing how this new breed of AI tools will complement and complicate their working lives. 

The ability of generative AI to automate routine tasks, analyze data, and generate content is already freeing up valuable time that entrepreneurs, executives, and individuals can use to instead focus on more strategic decision-making. 

But those changes also bring the possibility of rapidly shifting duties — and some core job responsibilities could be almost entirely consumed by AI.

Marketers are definitely at the forefront of experimenting with GenAI. Early successes we’ve noted include assistance in analyzing campaign performance, creation of email sequences that reflect the company brand, and the summarization of core content into derivative assets, such as video scripts and social media posts. 

Each new example proves tantalizing hints of how much of a productivity game-changer generative AI can be. The results, however, are irrelevant if AI systems are fueled by low-quality data. 

Why Data Quality Matters for Generative AI

While AI tools in the broadest sense have been in development for decades, the explosion of recent interest is fueled by the release of consumer-focused products, like Google’s Bard and Open AI’s ChatGPT. Their rapid growth recalls some of the most durable tech-driven shifts of modern history, with research by Bloomberg suggesting the generative AI market will grow to $1.3 trillion in the next 10 years. 

Data quality stands to play an essential yet often overlooked part in that growth. Without quality data, companies risk creating inconsistent and inaccurate results at a speed and scale that is nearly impossible for humans to control. And first-party go-to-market data at many businesses is notoriously fragmented, with 55% of corporate leaders in an Experian survey saying they distrust their own data assets.

“I’ve yet to meet a company who shows up and says ‘Yes, absolutely the data in my CRM is accurate and complete,’” ZoomInfo CEO Henry Schuck says. “The data underlying customer outreach needs to be incredibly accurate, enriched, and deep. We are in a really unique position as a company and with an offering to fuel that.” 

Think of the problem like a simple recipe. Pouring random ingredients into a cake pan and baking at 350 degrees for 40 minutes won’t give you a birthday worth remembering. Now imagine you’re doing that in an industrial kitchen that can turn out hundreds of cakes in an hour.

Quality data is the essential ingredient for generative AI to work at its highest potential. Because GenAI is based on large language models that are primed to give human users satisfying answers, it’s disturbingly common for models working with the wrong data to “hallucinate” inaccurate results at scale, amplifying run-of-the-mill errors in ways we can’t always understand.

Integrating your own team’s data with comprehensive, constantly updated, privacy-compliant sources like ZoomInfo, on the other hand, can help ensure that GenAI efforts for business are working with the best possible inputs and giving you the most trustworthy results. 

What Does this Mean for Marketers?

A robust data foundation allows businesses to generate not only more results, but better results. Think of all the ways AI is used to streamline internal processes, increase automation, and drive greater efficiency across a company.

“The way you should be going to market is by leveraging signals and then taking action against those signals,” Schuck says.

For marketers, generative AI can analyze complex datasets and extract insights that teams can act on to inform their marketing strategy, engage new customers, and create messaging relevant to each of their key personas. 

At this year’s INBOUND conference, HubSpot CEO Yamini Rangan said the smartest go-to-market professionals will use GenAI with one goal in mind: “To drive customer connection.”

“We are experiencing a transformative shift with generative AI. Customer expectations are changing, and businesses now have the opportunity to leverage AI to drive customer connection at scale,” Rangan says.

How Do Marketers Use Generative AI?

From content creation to market analysis, AI tools can help marketers to work smarter, faster, and more effectively.

1. Revenue Generation 

Lead scoring and personalized messaging are two of the biggest opportunities when it comes to generative AI, which can guide prioritization by analyzing extensive datasets and identifying patterns. Layering AI over a rich dataset enables granular prioritization of target companies based on their attributes and pain points. As a result, teams are more likely to increase conversion rates and revenue.

Personalization is key to capturing potential customers’ attention and building meaningful relationships. Generative AI can be used to analyze user data, purchase history, browsing behavior, and demographic information to craft tailored messages that resonate with individuals at target companies. Such personalization is a great lead-nurture play, as you can gradually build trust and rapport.

Tools like ZoomInfo Copilot drive relevant, resonant personalization at scale, with lightning speed. Now, go-to-market teams can rely on Copilot to surface target accounts that are showing a high likelihood to buy, based on real-time data and insights — and use Copilot’s AI email generator to craft outreach that speaks directly to the account’s goals and priorities.

2. Search Engine Optimization (SEO) 

Generative AI can help SEO teams stay on top of their rankings and make appropriate updates. With the ability to swiftly analyze keyword trends and scan examples, generative AI can create content that is not only well-structured, but optimized for search engines.

Semrush, for example, launched a Compose with AI feature to help users draft SEO-driven content. This feature creates outlines that writers update to meet their brand standards. 

It’s important to note, however, that Google is not giving content teams carte blanche to create tons of AI-based SEO content — quality, helpful content remains king. While not issuing any blanket statements on AI as a tool, the company has said that use of automation tools to create content intended to game search rankings violates its spam policies.

3. Market Intelligence

Understanding competitors and alternative solutions in your industry is time-consuming. With generative AI, this process can become much simpler: AI tools can quickly process and analyze competitor data to identify market trends and opportunities at scale.

With Chorus AI post-meeting summary notes, prospect discovery calls can be transformed into actionable reports for marketers. This feature automatically records and transcribes action items from sales calls, removing the need to manually take notes and identify important action items from a call. 

Marketers can use these insights to quickly synthesize and act on intelligence gathered from sales and customer success teams in a way that was not possible before. As a result, marketers can be immediately looped in to key insights and trends that can help inform their GTM strategy.

4. Social Media

Social media marketers are tasked with publishing content across multiple platforms, covering many topics — and squarely in the public eye. When an urgent request comes in, there often isn’t a lot of time to research everything you need to know and craft an engaging social post that’s relevant for each of your social media channels.

With generative AI, social media managers can generate suggested social copy for each platform. Additionally, generative AI can analyze engagement across these platforms and suggest improvements to meet customer needs. Hootsuite, for example, launched OwlyWriter to help create captions at scale.

5. Product Marketing

Product marketers develop market positioning and communicate new products and features to customers. 

Generative AI can sift through data, such as purchase history or product reviews, to better understand customer preferences. This makes it easier to develop product positioning that resonates with the needs of those customers. Plus, these insights can be shared with the product development team to inspire future product enhancements.

6. Brand Marketing

Brand marketers can assess mentions across the web with AI. This can help illuminate brand perception and identify opportunities for improvement while reducing the time that would otherwise be spent on manual research.

Generative AI can also convert these insights into brand-aligned content ideas that speak to the existing and prospective customers in your target audience. 

7. Content Marketing

Content marketers can automate content creation at scale. Blog post outlines and video script drafts can be created in seconds using generative AI. Some providers, like Jasper, allow businesses to upload brand guidelines, helping ensure that the outputs are on-brand and in the correct tone. 

After you have content created for a campaign, AI can also recommend the optimal channels and timing for content distribution — especially in cases where a team has trained an AI bot on previous performance data. While testing different channels will always be the best way to accurately determine campaign performance, recommended starting points can help drive results quicker.

8. Demand Generation

Generative AI can help demand generation teams save time and money by analyzing datasets to surface potential leads to add to targeted campaigns, like nurture flows. Additionally, tools like HubSpot’s AI Content Writer are an efficient, highly effective way to get suggested copy for landing pages, social media posts, and other key campaign collateral.

If you’re looking to maximize the success of high-intent web pages or marketing assets, AI can suggest different versions of text for the same campaign to A/B test, helping determine which resonates best.

9. Public Relations & Communications

Similar to content managers, communications managers can use generative AI to draft content, like press releases. Using an AI writing tool like Grammarly can be a great way to create quality communications at scale. 

Developing and building your own generative AI use cases internally can also have a major PR benefit in positioning your company as a market leader and innovator. Make sure that PR teams are kept up-to-date with the latest thinking, newest initiatives, and upcoming product releases that incorporate generative AI — they can turn that hard work into valuable public recognition.

Get Started Today

Generative AI has changed the way businesses operate in a very short amount of time. To make sure those changes are having the biggest possible impact on your growth, step one should be ensuring your GenAI is working with a solid data foundation.

Find out more about how ZoomInfo’s data powers the world’s best GTM teams — and how any company, in any industry, can access the same data and tools used by the biggest, most innovative companies on the planet to drive their GenAI initiatives today.