Pierre DeBois's profile photo

Pierre DeBois

Norwich

Founder and CEO, Zimana and Contributor at CMSWire

#analytics #marketing #datascience #rstats services #smallbiz contributor @InformationWeek @ITProToday @CMSWire @smallbiztrends #BlackLivesMatter #BlackInData

Articles

  • 2 days ago | zimanaanalytics.medium.com | Pierre DeBois

    When I last explained about LMStudio, the hosting platform for local AI development, I noted how developers can create AI models using smaller LLMs, called small language models. Many of the LMStudio display model size parameters, which you use to select a model.

  • 2 days ago | cmswire.com | Pierre DeBois

    Explore the new rules of AI search and how marketers can stay visible in an evolving SERP landscape. AI has changed the rules of SEO. Traditional keyword-based approaches must evolve to match AI’s prioritization of context, quality, and user intent. Enter AISO: AI Search Optimization. Marketers must optimize for how AI summarizes and ranks content across evolving SERPs and conversational experiences. New playbook required.

  • 1 week ago | cmswire.com | Pierre DeBois

    Unify touchpoints, deploy predictive models and create insight-to-action loops that actually scale. Personalization through AI. Artificial intelligence helps marketers connect fragmented touchpoints into coherent journeys. Faster insight-to-action. AI reduces the time it takes to go from raw data to real-time decision-making. New visibility into journeys. AI-driven pattern recognition and prediction replace outdated dashboards.

  • 2 weeks ago | cmswire.com | Pierre DeBois

    It’s time to move beyond vanity metrics. Discover how AI turns customer data into performance-ready action. AI-powered insights. AI-driven predictive analytics allows marketers to forecast future customer behaviors and trends with greater accuracy. Real-time adaptability. By using real-time data and AI, businesses can make faster, more informed decisions that directly improve CX and drive KPIs. AI for data storytelling.

  • 3 weeks ago | zimanaanalytics.medium.com | Pierre DeBois

    Data — be it in R, SQL, or Python — are always categorized. Understanding binning and slicing can lead to better choices for planning data models. Here’s how. Pierre DeBois·Follow5 min read·--The world is awash in data, and many times we have to categorize that data before it is applied to a data model to perform an advanced calculation. The starting point for a good categorization strategy is to identify what data should be binned and what data should be sliced.

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Zimana Analytics | Pierre DeBois, Founder (He/Him)
Zimana Analytics | Pierre DeBois, Founder (He/Him) @ZimanaAnalytics
14 Jan 25

RT @DMBeat: What Makes NotebookLM Appealing for Marketers? by @zimanaanalytics https://t.co/WtkVoU5t4v

Zimana Analytics | Pierre DeBois, Founder (He/Him)
Zimana Analytics | Pierre DeBois, Founder (He/Him) @ZimanaAnalytics
14 Jan 25

RT @CXMWorld: What Makes NotebookLM Appealing for Marketers? by @zimanaanalytics https://t.co/7495LaV5hn

Zimana Analytics | Pierre DeBois, Founder (He/Him)
Zimana Analytics | Pierre DeBois, Founder (He/Him) @ZimanaAnalytics
7 Jan 25

RT @CXMWorld: Will ChatGPT Search Change Everything in SEO? by @zimanaanalytics https://t.co/zC7oOr7FxK