The Use of Generative AI in Marketing and eCommerce
Everybody is trying to understand how to use and leverage AI. And with literally hundreds of AI tools, especially the recent popularity of ChatGPT, there is even more white noise. It is safe to say that AI has moved beyond the hands of just the IT Department
There are a lot of AI tools on the market that are used by a wide range of departments and teams, specifically in eCommmerce and Marketing. Historically, they have almost exclusively been used for analytics, but this has changed with the rise of Generative AI (GenAI). This blog post highlights key steps to building a modern GenAI tech stack in Marketing.
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Hear ELASTECH’s CEO, Armen Tatevosian, and EVP of Global Operations, Jim Zordani, in a conversation about the use of Generative AI in Marketing and eCommerce.
Confirm Benefits and Opportunities
The first step is to establish a mutual understanding of Generative AI, its benefits, and potential drawbacks.
GenAI refers to a subset of Artificial Intelligence that goes beyond analyzing or acting on existing or specific data sets. It actually creates new and original content, including copy, images, videos, music, and even software code.
Whether they recognize it or not, marketers are likely already taking advantage of AI, as this technology has been used for years in these areas to perform product and pricing reviews, testing, or sentiment analysis.
Now, with Generative AI, marketing teams have begun to enhance content creation or augmentation. A proven approach is to combine analytical tools with Generative AI, in order to benefit from both disciplines. This way, eComm and marketing teams not only create content for content’s sake, but they can also perform effective consumer and market analysis to optimize content production and targeting. This delivers better customer experiences and digital marketing results.
Determine The AI Tech Stack
The second step refers to the process of manifesting a company- or department-wide vision about where and how AI should be deployed, rather than the actual implementation.
Marketing and creative teams will require a big-picture consideration of what their AI tech stack is or should look like, what tools are in that stack, and how it will integrate into their already existing marketing technologies. When it comes to AI, there are layers of considerations, such as data privacy, customer protections, inclusivity, and authenticity to the brand content outputs.
Fundamental components of a Generative AI tech stack include a publicly trained AI. These tools leverage Large Language Models (LLMs) that are trained on public data. Examples are Open AI’s GPT, Anthropic’s Claude, Google’s Bard, or the dozens of lesser-known tools that have their own foundational models.
Secondly, there is privately trained AI. Privately trained AI involves training language models and other AI tools on a company’s own data to align them with their branding. This involves tone of voice, certain phrases, corporate design, etc. Basically, businesses want to assure that the AI performs through their brand’s lens.
Implementing The AI Tech Stack
There are three different options for adopting AI and integrating a privately-trained AI with a publicly-availale LLM.
The first one is an approach called “Prompt Engineering,” which is the easiest way, requiring only minimal lift effort. Companies simply give guidance to the AI tools, possibly with some uploaded data.
The second option is “fine-tuning,” which is much more involved, but also more controllable. During the fine-tuning, the public AI model adapts to the specific language patterns, terminology, and style of a brand’s dataset, with new specific performance goals trained.
And lastly, there are also Vector Data Embeddings. Leveraging those allows data to be captured via a more simple database and then reformatted by the large language models.
Moreover, companies need to prioritize that public AI and private AI work together seamlessly. This way, marketers can literally type in a question or a topic in an interface that then pulls public data and, based on that data, creates on-brand content.
Minimizing friction requires “tech bridges” between different AI tools (some of them might be personalized, others off-the-shelf), and existing technology ecosystem, including CRM, CMS, etc. Tech bridges enable connections and data flow. In some cases, this can be done fairly easily through direct integrations or APIs. In other cases, teams or development partners will need to build middleware to connect the tools.
Fine-Tune The AI Tech Stack
After technologies are confirmed and implemented, gaps between different systems are bridged, and the AI model starts learning, many consider the process complete. However, this is where companies are missing out.
Once an AI model starts learning, confirmation training needs to be prioritized. This is the process of training an AI to make sure it stays on brand, does not provide irrelevant content, and understands and aligns with a brand’s values and language.
In addition, when organizations use generative AI models, they need to ensure that the results are formatted, templated, and delivered according to their needs.
Generative AI provides tremendous growth opportunities for business success and the customer experience. To make the best use of Generative AI, marketing and eCommerce departments should start by:
- Establishing a common understanding of GenAI
- Evaluating technologies, particularly the publicly-trained AI, to identify how to leverage them
- Selecting the right implementation approach based on budget as well as available skills and bandwidth
- Model training to ensure the AI model is an “expert” on a company’s brand and data
Many executives have recognized the value of outside expertise to execute GenAI projects with confidence and as little rework as possible.
ELASTECH is a company recognized for delivering modern GenAI solutions and for its commitment to fostering a deeper understanding of AI. We welcome your questions about how GenAI and its use cases can best serve you and invite you to take a deeper dive into the practical applications. Our experts will help you evaluate and confirm specific opportunities with GenAI in Marketing and eCommerce, and/or determine how to integrate the technology into your existing stack. Click below to schedule your free consultation.
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