The Gist
-
Smart use cases. Generative AI in marketing thrives with specific, impactful use cases like predictive analytics, personalized outreach and content automation.
-
Tech meets efficiency. From automating lead scoring to creating tailored campaigns, generative AI reshapes marketing operations while cutting costs and improving ROI.
-
Vendor opportunities abound. AI vendors can tap into unmet needs like audience segmentation and UX improvement for growth.
Generative AI in marketing offers a wealth of opportunities, but where do you start? Research shows that four use cases for marketers and six for vendors are particularly valuable. Since ChatGPT 4.0 entered martech 18 months ago, the conversation has shifted from “Should we use generative AI?” to “What use cases can we implement effectively?”
Despite the hype, not all generative AI use cases deliver value equally. Success lies in choosing the right use cases, and there is huge potential for both marketers and software vendors. Some use cases are highly underutilized by marketers, while others are underutilized by software vendors.
But first, let’s take a step back and explore the three major ways generative AI has affected martech.
How Generative AI is Shaping Martech Innovation
There are three primary ways generative AI is being integrated into martech.
-
Individual Tools (n = many): These standalone tools solve specific problems. For example, Jasper.ai automates content writing, while SlidesAI creates presentation decks in seconds. Such tools allow teams to experiment with AI without a significant upfront investment or disruption to existing systems.
-
Tools Embedded Inside Incumbent Solutions (n = many): Leading platforms like Salesforce, Hubspot, and Adobe Firefly are weaving generative AI into their offerings. These embedded capabilities provide AI-driven features (such as personalized customer journeys) within familiar environments and make adoption simple for users.
-
Disruptors (n = handful): New platforms like ChatFactory and ChatSpot (now Breeze Copilot) challenge traditional martech categories and reimagine CMS and marketing automation. These disruptors are particularly appealing to businesses looking for more radical transformation.
Related Article: 5 Actionable Ways to Integrate AI Into Martech Processes
Generative AI’s Impact on Cost Savings and Revenue Growth
Generative AI helps businesses both save and make money. Companies can save costs by improving operational efficiency, a long-driving force for martech investments. Generative AI in marketing amplifies this by automating repetitive and resource-heavy tasks. Here are a couple examples:
-
Automating Lead Scoring: Tools like AlgoOps streamline predictive lead scoring and remove the need for manual data analysis. Sales and marketing teams can reallocate time to higher-value activities, such as strategic planning and sales activities.
-
Content Generation at Scale: SpeakAI automates transcription, analysis and even translation of multimedia files. Jasper.ai goes a step further by generating polished content, which allows marketers to focus on ideation rather than execution.
These tools don’t just save time. They also ensure consistency. For instance, they can automate routine tasks to reduce human error. Also, these scalable solutions allow teams to handle growing workloads without hiring additional staff.
While cost savings are significant, generative AI’s real promise lies in enhancing customer experiences and driving revenue growth. Here are a couple examples:
-
Personalized Outreach: Platforms like Regie.ai analyze intent data and allow marketers to craft personalized outreach campaigns. EgoBooster tailors introductory sales messages for cold email and social outreach.
-
Real-Time Recommendations: Advanced tools like Compelling track buyer behaviors and pipeline data to suggest actionable next steps. These insights let sales teams close deals faster.
By using generative AI for personalization, businesses can improve conversion rates by delivering the right message at the right time. They can also build customer loyalty through tailored experiences and gain actionable insights by analyzing vast amounts of customer data.
Analyzing the Top Use Cases for Generative AI in Marketing
By comparing what generative AI use cases marketers are using and what vendors are offering, we get a clear picture of the opportunities for both marketers and vendors. We combined the data from our own Martech Datawarehouse (2,371 generative AI tools and use cases) with outcomes from MKT1’s “State of AI Survey.” In the latter, marketers indicated if they used certain generative AI cases (daily, weekly or monthly).
By comparing both percentages, it becomes clear if there is more supply than demand or more demand than supply (see the numbers in the bars).
There are stark differences between the supply and demand for individual use cases. By noting where the differences are the largest, one can identify where the opportunities lie for marketers and vendors.
(Note: The tools mentioned are examples only. We neither endorse nor have any affiliation with them. Given the rapidly changing martech landscape, some of these tools may even go out of business in the near future).
4 Ways for Marketers to Use Generative AI
-
Reporting and Analytics: There is a wealth of specialized reporting and analytics tools. What about labnify.com for email analytics? Meanwhile, build your dashboard with canvasapp.com, analyze reviews with mara-solutions.com, explore your CX metrics with augmentcxm.com and look into customer needs with harmonize.ai. Chat with your documents via sharly.ai, and communicate with your data via rawquery.com,
-
Marketing Ops Automation: Immerse yourself in the great number of code assistants like tabnine.com and lead assistant shillbot.xyz. Adopt ad reporting tools magicbrief.com, ETL/data sync with polytomic.com or RPA assistants like runautomat.com.
-
Copywriting: There are many specialized generative AI tools for copywriting. What about writerelease.com for press releases, conversionmaker.ai for eCommerce marketing copy, hoppycopy.co for email copy, notice.studio for your website and docudo.xyz for product copy?
-
Sales Enablement: Optimize your sales efforts by answering RFPs with 1up.ai, source leads with oliverlist.com, and create sales presentations with slidesai.io. Meanwhile, optimize your funnel with salesbox.ai and analyze revenue wins or losses with tribyl.com.
Related Article: Making the Most of Generative AI Tools for Marketing Success
6 Key Opportunities for Generative AI Vendors in Martech
-
Social Copy/Posts: The largest opportunity here lies in assisting marketers with social media. This includes capabilities such as automating social posts (postus.ai and sparksocial.io), automating replies (replyboy.com), writing replies on social media (justcomment.ai) and organizing social posts (publer.io).
-
Content Research: AI also offers promising applications for testing and validating content. While current use cases are still narrow, they cover areas like website analysis with archistar.ai, persona research with qoqo.ai, A/B testing with abtesting.ai and UX improvements with flawless.is.
-
Competitive Research: Improve market research with meaningful.app, customer opinion research with opinio.ai and predictive AI for content with clevr.ai.
-
Audience Research and Segmentation: Detect high-propensity customers with getcorrelated.com, improve churn with headsup.ai, conduct prospect research with lavareach.com, dig into customer data with spatial.ai and explore neuroscience with neuronsinc.com.
-
Design Assets: Some emerging tools are addressing needs such as interface design (usegalileo.ai), videos (d-id.com) and product design (uizard.io).
-
Making Presentations: AI is being used to generate pitch decks with beemerdocs.com, product content with quinv.io, storytelling with storyd.ai and on-brand presentations with deckrobot.com.
Generative AI in marketing is transforming the martech landscape, offering immense opportunities for both marketers and vendors to enhance efficiency, personalization and growth.
Learn how you can join our contributor community.
