Company Settings
In the company settings you can customize the company details:
Company Logo
Currency
Products
Company name
Assistant
KPI
Objectives
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Once your company is set up on the [AI] platform, the next step is to configure the Data Language Model (DLM) to ensure that your AI Assistants respond to queries accurately and efficiently. This involves fine-tuning how the AI understands and prioritizes your data. Here's how to proceed:
Adding Keywords: Start by adding business-specific keywords to the DLM. These keywords help the AI understand the context of queries, making it easier to interpret questions related to your products, services, or operations.
Ranking Metrics and Dimensions: One of the key steps is ranking the metrics and dimensions derived from data sources such as Google Analytics, Adobe Analytics, or other integrated platforms. Metrics like website visits, bounce rates, and conversion rates, along with dimensions like traffic sources, regions, or device types, can be prioritized. By ranking these elements, the DLM knows which data points are most critical when responding to queries, particularly when comparing two or more metrics.
Linking Data Sources: Once a data source is connected to the platform, the system will automatically display the available metrics and dimensions from that source. For example, if you link Google Analytics, you'll see metrics like page views, session duration, and goal completions, while Adobe Analytics might provide insights into user interactions, pathing, or segment analysis.
By configuring the DLM with relevant keywords and prioritizing metrics from these analytics tools, your AI Assistants will be better equipped to understand and respond to queries, offering more targeted insights and improving decision-making across teams.
How to configure the DLM for a MetricsLast updated