Our latest product updates make it easier for marketers to integrate all their data sources with Lifesight, declutter their view in the attribution dashboard, and improve the cause and effect relationships between factors of influence for our Causal Inference models.

Let’s deep-dive into it:

Custom API: Enhancing data integration and insights

Want to integrate a data source with Lifesight but don’t see it in our list of native integrations? Introducing Custom API. Here’s what it brings to your marketing efforts:

  • Effortless integration: With Custom API, you can bring in data from any of your sources into Lifesight without writing a single line of code.
  • Enhanced customer journeys: Once you bring all your marketing data in and our platform stitches all the data together and provides you with a comprehensive view of your customers’ journey.
  • Superior attribution data: Get accurate data insights for attribution, ensuring you know precisely how your marketing efforts contribute to your goals.

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Decluttering data into actionable insights with Rules and Labels

When dealing with a lot of marketing channels, the flood of UTM parameters can lead to a confusing mess of data, making it tough to figure out what’s actually working. The Rules and Labeling feature enables users to locate, categorize, and tag various UTM source, medium, and campaign identifiers.

Instead of dealing with data chaos on your attribution dashboard, you get insights that are easier to manage and ready to use. Here’s how it elevates your data strategy:

  • Automated Tagging and Categorization: By setting predefined rules, marketers can automate the process of tagging and categorizing UTM parameters. This ensures that data from similar sources, mediums, or campaigns is grouped together, making it easier to analyze.
  • Smart Conditional Logic: Implement rules based on “if/then” scenarios to streamline your data further. This means you can automatically filter out irrelevant data or highlight the traffic sources that matter most to your strategy.
  • Precision with custom rules: Set traffic attribution to your needs, filter out unwanted sources for clearer insights, and use custom labels. This streamlined approach ensures your data is both clean and detailed, enhancing your understanding of audience engagement.

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Enhancement: New additions in Causal Inference

  • Relationships: Users can now easily set up relationships between variables when creating a model. These represent possible causal connections that could exist between two variables. You can choose which relationships to include or exclude, focusing your analysis on the causal connections that matter most to your goals. This allows you to refine the model and focus on the causal connections that are most relevant to your inquiry.
  • Rediscovery: Post-model insight generation, you have the option to revisit and adjust these relationships, fine-tuning your model’s accuracy and relevance continuously.

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With these enhancements, your marketing models are not only more reflective of your specific hypotheses but also provide deeper, actionable insights.

And there you have it, that was all from our side this month! Expect these enhancements to eliminate tedious data tasks and enhance the clarity of your choices. We’ll return with more innovations and enhancements next month.

Stay connected!