Kirill Markin | Source | Head of AI Lab at SOAX

We're already utilizing ChatGPT in our sales, marketing, customer service, and even programming operations.

Most companies don't need to dive straight into Data Science at the onset. It's often better to start with simple solutions. For instance, you could implement straightforward rules for certain scenarios. Once you've got that down, you can begin experimenting with basic machine learning models. Only after mastering these should you consider delving into more complex, harder-to-interpret algorithms.

Let's note down the features that are nearly omnipresent in any entry-level CRM product:
- Dashboards: A sales funnel and metrics to analyze salespeople activity and KPIs.
- Deals: Display records as a board with cards and as a table. For now, we won’t add any automation. (It can be added in an hour or two. We will talk about this later.) Managers can leave comments for each deal. Records also contain a history of actions.
- Customers: Customer details with vital information like contact names, phone numbers, and emails. Both individuals and organizations can be listed with specific fields for each.
- Products: A list of products sold as part of the deal to keep notes on sales.