When startup funding is tight, marketing can feel like a luxury—even if it isn’t. Fortunately for founders, relevant technologies driven by artificial intelligence (AI) can amplify the efforts of a small marketing team. In fact, according to a Bain & Company survey of nearly 600 companies in 11 industries, almost 40% of respondents said they’re already using or considering using generative AI to speed up the development of marketing collateral. And a majority of global business leaders expect a rapid adoption of AI-powered marketing tools in the next two years, with 90% of those surveyed by McKinsey & Company anticipating frequent use of generative AI.
One reason for this quick adoption is that marketing is characterized by a convergence of creative and data-driven tasks—a combination that makes this area a prime target for disruption by generative AI. As a digital marketing specialist who works with startups, established businesses, and thought leaders to expand reach and grow sales on limited budgets, I have found AI to be crucial to the services I provide. It enables startups in particular to perform essential digital marketing tasks, such as web analytics, search engine optimization, and email outreach, speedily and at significantly lower costs at a time when scarce funding is making many projects otherwise difficult or impossible.
As companies integrate AI tools into their marketing functions, one major challenge is picking the right solution for their specific needs. The dizzying pace and variety of today’s AI offerings have even the most tech-savvy business owners racing to keep up. Take ChatGPT, the popular AI chatbot by OpenAI that can perform data analysis, content generation, and other marketing-related tasks. It’s been in the public domain for over a year and attracted more than 1.7 billion visits within that time. And it’s just one of many new AI tools and platforms being rolled out and regularly updated in a race among the world’s biggest tech companies to stay ahead.
The first thing to know about the new AI-powered marketing platforms is that they don’t change what you need to achieve to market your business. Rather, they change how you can go about accomplishing those tasks. By handling much of the heavy lifting for routine tasks—e.g., analyzing real-time data and autogenerating personalized marketing content—AI can save you time and money. But it’s important to note that human insight and creativity remain crucial. AI-powered tools lack intuition, emotions, and cultural sensitivities—qualities that make humans more effective in creative tasks such as adding unique touches and ensuring alignment with the brand’s data needs, core values, and message.
In this article, I show you how AI can help companies meet five key marketing objectives.
Understanding Customer Preferences
Any good marketing strategy includes tailoring messages to customer interests, behaviors, and preferences. This kind of personal attention makes customers feel understood and valued, thus cementing their connection to the brand. This can result in higher engagement, stronger loyalty, improved conversion rates—and, ultimately, more sales.
Executing such a strategy involves data analysis, segmentation, content creation, and implementation. It can be time-consuming, labor-intensive, and expensive, often requiring additional staff, specialized software, or third-party services—resources not always available to smaller businesses and early-stage startups.
One of my clients, a small fashion shop, wanted to understand the preferences of its customer base. Before AI-powered solutions, the boutique’s owners collected purchase histories and customer feedback forms and conducted surveys, accumulating piles of data over several months. Once they had sufficient information about customers’ buying preferences, the next step was to hire a consultant to sift through it for marketing insights.
However, for a fraction of the cost—potentially $10,000 to $25,000 annually, depending on the scope of work—AI tools like ChatGPT and Adobe Experience Platform can analyze vast amounts of marketing data generated when customers shop online or visit a website. The data collection includes customers’ browsing histories, purchase histories, and what items they’ve clicked on. These tools can even track social media activity related to your products, depending on customer privacy settings. Then the AI uses algorithms to identify patterns, trends, correlations, and preferences in the data.
An AI tool can segment customers based on their behavior and preferences, grouping those who frequently purchase similar items or exhibit similar browsing habits—making it much easier for a company to offer personalized products. These platforms can also track customer journeys through the sales funnel, identifying where customers drop off and revealing problems such as a confusing checkout process or irrelevant content.
Some AI-powered applications can use existing data to extrapolate and predict future customer behavior and purchases, empowering a company to offer customized product suggestions to customers through email campaigns with suggestions based on past purchases, pop-up recommendations, or even invitations to chat with a virtual assistant that can suggest products based on search and browsing history. Companies can implement these tools in alignment with their brand’s strategy, ensuring a coherent experience for the customer.
Improving Customer Targeting
In order to attract, acquire, and retain customers, companies need a good grasp of user behavior. For smaller companies without robust marketing functions, this might require purchasing third-party data and insights and then hiring outside analysts to help develop the personalized content required to keep customers coming back. In my experience, the costs for these services can range from a few thousand to tens of thousands of dollars, depending on the scope and scale.
One tool that can slash those costs is Tableau AI, an analytics platform that charges users less than $100 per month. Tableau can analyze customers’ behavior by comparing them to successful conversion paths in relevant industries and identifying where customers might drop off, potentially saving a small team significant time and money.
Companies can then use this information to tweak their marketing tactics and make data-driven changes to sales processes and customer experiences, ensuring that they are focusing their efforts on customers likely to make a purchase. This is just one way that AI can save money by reducing the need for third-party services or specialized software.
Here are the platforms I recommend to companies looking to improve their customer targeting:
- Adobe Experience Platform provides real-time customer segmentation and targeting. At $50,000 or more a year, this can be an expensive option, but it may be an appropriate investment depending on your company’s needs.
- Salesforce Einstein is an analytics tool that integrates with Salesforce’s customer relationship management platform and helps businesses automate lead scoring and segment customers. Einstein’s pricing varies according to your company’s specific Salesforce package.
- Google Analytics 4 is a free tool that provides substantial user behavior insights and integrates with ad platforms. Google plans to incorporate AI to help companies identify ads that connect most with customers, making it useful for smaller businesses seeking to track and improve their advertising efforts. Google also offers an enterprise-level version called Google Analytics 360, which costs about $150,000 annually.
Automating Customer Support
AI-driven chatbots and email bots improve customer support by enhancing scalability, personalization, and resource optimization. With sufficient guidance, tools such as ChatGPT, Ada, and Google’s Dialogflow are virtually indistinguishable from humans during support conversations.
Another advantage of AI in the customer support space is that these tools are always available when customers need help. One travel startup I recently worked with implemented ChatGPT to handle routine inquiries such as “How do I change the dates for my trip?” or “What’s your cancellation policy?” After the implementation, the need for support staff dropped by 30%, all without sacrificing customer satisfaction. Another startup client reduced response time to customers by 40% and increased customer satisfaction using Zendesk and Dialogflow. These tools offer more advanced ticketing and support automation than ChatGPT by using virtual agents—machine-learning chatbots that operate mostly without the need for real-time human supervision.
Zendesk and Dialogflow are ideal for small to medium-sized enterprises with complex customer queries. Their 24/7 availability and learning capabilities further enable companies to enhance customer experiences and manage complexity effectively, generally at far lower costs than round-the-clock staffing.
To measure the tools’ performance, businesses can prompt customers for feedback after an AI-powered chat or call. This can be done through a simple survey of customers’ satisfaction levels with the responses they received. AI chat systems can automatically run a sentiment analysis of responses such as “Thanks, that’s helpful!” and “That doesn’t help at all” to assess a user’s level of satisfaction.
For nonroutine or complex queries that fall outside the AI’s training, AI systems can suggest transferring the user to a human representative, emailing customer service, or calling a support number. Or the chatbot may offer a general response or send a link to a relevant FAQ section.
Beyond simple customer support, Dialogflow can create dynamic conversational chatbots that assist with more complex inquiries, provide personalized recommendations, and even facilitate sales processes. For example, Dialogflow can be set up (with the appropriate back-end integrations) to search through a product database and provide answers to product-specific questions.
As helpful as these and other AI tools can be for customer service and marketing, they don’t replace the need for human involvement, particularly in training and customer interactions. Rather, AI empowers workers to shift their focus from lead nurturing to lead qualification and activation in later stages.
Establishing and maintaining a social media presence takes considerable time and energy because it requires a constant stream of new, company-specific ideas, monitoring, and creative collateral such as images. Even dedicated social media editors have their hands full managing a company’s presence across a multitude of social platforms. AI can lend a strong assist here too. Tools such as Canva’s free AI image generator, Midjourney, and DALL-E can create images for use on social media and make it easier to create a cohesive visual aesthetic for your business across platforms.
However, I want to note that generating images is one of the most contentious areas in AI-powered marketing tools. Critics of AI-generated images argue that since the AI has been trained on existing images that were created by human artists it is in effect plagiarizing artists’ work. Those who support this latest evolution in image creation counter that each AI-generated image is unique, and that the result largely depends on the prompt given by a human. The debate about what to do—not just the morality—is ongoing in the absence of regulations.
Despite this uncertainty, and amid legal challenges, the market for AI-generated images is growing fast. AI-driven visual content tools—e.g., Midjourney, DALL-E (integrated with Microsoft’s Copilot), Adobe Firefly (which is incorporated into newer versions of Photoshop), and Amazon Rekognition—generate images from text prompts and comparable visual examples. For a company looking to get away from stock pictures and other generic images, these tools can produce one-of-a-kind images to match a company’s brand. The continual learning capabilities of AI mean that these tools can refine and improve visual content generation over time, staying on brand and effective without constant human oversight.
For my clients who want to sidestep copyright and plagiarism concerns, I recommend using the Adobe Firefly image generator, which protects against infringement on intellectual property rights by drawing from Adobe’s own portfolio of stock media and freely licensed images. OpenAI’s DALL-E offers certain protections as well, such as rejecting requests for images made in the style of a living artist.
Crafting Effective Email Marketing Campaigns
Traditionally, effective email marketing has required human effort at every stage, involving coordination between writers, designers, marketing managers, and possibly even IT staff. It’s especially time-consuming and expensive for companies without in-house expertise since they will likely have to outsource these tasks.
AI can automate many email marketing processes, including segmenting audiences based on behavior and engagement, generating personalized content, designing visually appealing layouts, and even testing different versions of a marketing email to see which one performs best. I frequently advise smaller startups on a budget, particularly those in the e-commerce space, to use the free version of ChatGPT to write their newsletter copy.
AI can generate marketing content based on templates, past content, brand guidelines, and audience insights—but that data needs to be thoughtfully curated by a human. Fortunately, training and using AI marketing tools don’t require deep technical expertise. Many technologies offer user-friendly interfaces and customer support to guide nontechnical users through the process. (That said, collaboration with a technical team member or an external expert can also give your company a firm foundation in AI and be helpful for more complex implementations.)
When properly trained and used, AI tools can deliver effective marketing materials for startups and smaller companies at a fraction of the cost of a full marketing staff or outside vendor. Experiment with these tools and find the ones that best align with your company’s business objectives. You’re likely to find, as I have, that AI can handle much of the drudgery of routine marketing tasks, freeing up people to focus their insight and creativity on what matters most.
