Embedding the platform

How to Pair Subconscious.ai with your existing research stack/ tech stack?

Pairing the quantitative causal insights from Subconscious.ai with your existing research methods and tech stack can create a powerful synergy, enhancing both the breadth and depth of your insights. Here’s a warm, practical guide to making that connection seamless:

1. Understand the Unique Strengths of Subconscious.ai

  • Causal insights at scale: Subconscious.ai excels at determining why certain behaviors or outcomes occur, using its AI-driven causal modeling and synthetic respondents. This adds depth to traditional research methods by providing robust, quantitative, and ethically-gathered data on human behavior.
  • Speed and flexibility: The platform allows for rapid testing and iteration, so you can quickly validate hypotheses or explore new ideas before committing to large-scale studies.

2. Integrate with Your Existing Research Framework

  • Pair causal insights with qualitative research: Use the rich causal data from Subconscious.ai to inform and enhance your qualitative methods (e.g., interviews, focus groups). For example, if Subconscious.ai reveals that customers respond better to a certain messaging tone, you can follow up with focus groups to explore the emotional reasons behind that response.
  • Complement survey methods: Traditional surveys gather surface-level preferences and opinions. You can enrich this by running causal experiments in Subconscious.ai to dig deeper into why people make certain choices. Once the causal insights are known, you can tailor your surveys to be more focused, validating those causal relationships in real-world populations.

3. Integrate Subconscious.ai with Analytical Tools

  • Leverage existing data analytics platforms: If you’re already using platforms like Google Analytics, Salesforce, or Tableau, Subconscious.ai’s insights can be fed directly into these tools. This helps you analyze user behavior at a granular level and then run controlled experiments to test hypotheses generated from real-world data.

How to pair them:

  • Google Analytics: Use Subconscious.ai to run experiments on why specific user segments convert or drop off, based on what Google Analytics tells you.
  • Salesforce or CRM platforms: Subconscious.ai can simulate the responses of different customer segments to various sales strategies, offering you insight into the best engagement practices before you apply them to real clients.

4. Incorporate Subconscious.ai into Behavioral Economics Models

  • Boost conjoint analysis: If you’re already using conjoint analysis to understand how different attributes of a product affect consumer preferences, Subconscious.ai can be an ideal complement. After conducting conjoint surveys, use Subconscious.ai to explore the causal mechanisms behind those preferences. This can help you refine your attribute set or hypothesize about additional product features.
  • Discrete choice modeling: Subconscious.ai is excellent for testing decision-making frameworks through its synthetic respondents. After using traditional DCE (Discrete Choice Experiments), apply causal models to test which attributes or choices are truly driving the decision process.

5. Integrate with Data Visualization Tools

Feed results into data visualization platforms like Power BI or Tableau to visualize causal relationships discovered through Subconscious.ai. You’ll be able to:

  • Track how different variables influence each other.
  • Compare outcomes from different experiments side-by-side.
  • Present findings in an intuitive way to stakeholders, helping them understand not just the what, but the why behind customer behaviors.

6. Pair with A/B Testing and Optimization Tools

  • Use causal insights to power A/B testing: Tools like Optimizely or Google Optimize are great for A/B testing, but they only show you which version performs better, not why. Subconscious.ai can help identify the underlying reasons for success, so you can refine your A/B testing strategy and focus on the most impactful elements.
  • Optimize your web or app experience: Once Subconscious.ai identifies what messaging or feature sets are likely to drive engagement, you can set up targeted A/B tests or multivariate tests on your platforms to validate those findings with real user data.

7. Integrate with Machine Learning and AI Pipelines

  • Enhance predictive models: If you’re already using machine learning algorithms to predict customer behavior, feed Subconscious.ai’s causal insights into your models to improve prediction accuracy. For example, you can use its results to refine the features you’re feeding into your models, focusing on those that have been proven to drive behavior causally.
  • Train models with richer data: Subconscious.ai’s synthetic respondents can provide you with large-scale, high-quality data to augment your machine learning pipelines. This enriched dataset can be used to train your algorithms, ensuring they capture nuanced consumer behaviors.

8. Support Longitudinal Research with Real-Time Experimentation

  • Pair long-term studies with rapid experimentation: If you’re running longitudinal studies to track changes over time, Subconscious.ai can provide real-time experiments to test interventions as you go. This lets you adjust your research program dynamically, experimenting with potential solutions in the short term while your long-term study runs in the background.

9. Ensure Ethical and Privacy-Conscious Research

  • Bolster privacy with synthetic respondents: If your research involves sensitive topics or populations, use Subconscious.ai’s synthetic respondents to gather ethical, privacy-friendly data without sacrificing quality. This is especially useful when combined with traditional methods like medical research, policy testing, or consumer studies that require confidentiality.

10. Sync with Marketing Automation Tools

  • Test before rolling out campaigns: Before launching a marketing campaign via platforms like HubSpot or Marketo, run causal experiments in Subconscious.ai to test how your target audience might react to different messages, incentives, or calls-to-action. This can significantly boost campaign effectiveness by identifying the strategies most likely to succeed before committing budget.

Example: How to Pair Subconscious.ai with Your Research Stack

  1. Google Analytics for Behavior Insights: Identify the key points where users drop off in your customer journey.
  2. Subconscious.ai for Causal Testing: Run experiments to test why users drop off at specific stages (e.g., pricing page or checkout) by simulating different scenarios.
  3. CRM (Salesforce) for Personalization: Use the causal insights to adjust messaging and strategies for different customer segments in your CRM.
  4. A/B Testing for Validation: Implement the insights from Subconscious.ai in real-world A/B tests, using tools like Optimizely, to validate and fine-tune your approach.