Let me tell you how you can use AI (artificial intelligence) in your company, specifically for a marketing company.
We are replacing a customer's marketing processes with artificial intelligence.
So why do we do this and how do we do it?
Why do we do it?
Our customer currently manages all the steps with human power.
For example, it compares the data it obtains by connecting to various services with similar sectors.
To give a more specific example, in order to measure and improve the performance of its customer's Facebook ads, it exports Facebook data, then examines its campaigns one by one and compares it with similar sector data it has and the user's successful ads. It determines decision points and action plans by evaluating it with its own know-how. Doing this means consuming manpower and time for our customer. In this way, the number of customers it can look after decreases, while on the other hand, it needs to increase the number of employees.
If we look at it, the process can be automated with software. However, there is a very critical point here, which is that the knowledge and datasets our customer has gained in the sector for years, which cannot be included in the software, cannot be imitated with a software.
Or rather, it could not be. We can now solve this problem by using artificial intelligence technologies at a high level. This brings us to the question of how we do it.
How do we do it?
Without getting bogged down in technical details, the following visual will give you a rough idea of how the technology works. To give a little technical detail, thanks to LLMs (large language models), it is now possible to talk to software as comfortably as you talk to a human being, we all know that. But the handicap of these language models is that while they have knowledge on almost every subject in the world, they do not have detailed knowledge and expertise. In particular, they do not have the wealth of professional knowledge that you have. For this reason, directly including them in business processes does not give a sufficient and useful result. However, thanks to fine-tuning or RAG (retrieval augmented generation) and vector databases, it is now possible to customize these language models. How? You can train these language models in a way that is specific to you, using your own information that you have documented so far, the data you have obtained so far, company policies and processes. This roughly means that you can produce a human-like version of your own company. You can talk to your customers directly with this agent (customized AI chatbot) and automate customer relations processes, significantly reducing costs while increasing customer satisfaction. On the other hand, as in this example, you can include your valuable company know-how in your service processes by training artificial intelligence with RAG or fine-tuning, and at this point, you can instantly turn your valuable knowledgeable people into a large team that you can allocate to each of your customers.
Would you like to hear more detailed information and examples? 👍
