Using the XPOZ MCP to Build a Complete Online Campaign Analysis: A Practical Walkthrough for Analysts

Marketing analysis is evolving fast, and analysts are increasingly expected to deliver insights that are richer, faster, and more tailored than ever. Using the XPOZ MCP, a multi-component prompting system built precisely for structured, repeatable, high-quality research.

In a recent project, I used the XPOZ MCP to create a full online campaign analysis. Below, I break down exactly how I approached it: from preparing the materials, to phrasing the MCP prompt, to refining the model outputs into a polished report.

The first phase of every analysis starts with understanding the scope and the data.

XPOZ MCP makes this smoother because it is designed to handle multiple data sets and contextual materials at once, allowing the analyst to anchor the model in real evidence.

Here’s what I used in the initial stage with the MCP:

Why XPOZ MCP matters here:

Its multi-source context ability ensures the model knows exactly what the research is about before it generates a single insight.

The next step was taking a report outline and translating it into a structured XPOZ MCP prompt.

I could define:

(e.g., volume trends, sentiment, competitor benchmarks, influencer contribution, narratives, demographics)

(engagement rules, sentiment rules, time periods, comparison logic)

(tables, charts, summaries, insights, recommendations)

(pre-campaign → during → post-campaign timeline segmentation)

The outline became the backbone of the prompt. With XPOZ MCP, prompts can also be stacked or extended:

The real value of the MCP shows up during the refinement cycle.

With each refinement I checked:

Are engagement, impression, and sentiment values aligned across sections?

Does the pre/during/post structure make sense?

Are insights meaningful? Are patterns explained and not just listed?

Can the final findings apply to any campaign, not just the one I analyzed?

I refined:

Why XPOZ MCP matters here:

MCP makes it easy to refine section by section instead of regenerating the entire report each time. This modularity speeds up the analytical refinement cycle.

By leveraging the XPOZ MCP across these three steps, I produced a generalizable, professional report that can be applied to:

This workflow can serve as a template for future projects:

XPOZ MCP is especially powerful for analytical workflows because it:

The system handles structure so the analyst can focus on insight.

Reports follow the same logic and methodology every time.

Prompts can be reused, extended, or segmented based on project needs.

Strong contextual input minimizes errors and keeps all metrics coherent.

What once took days can now be produced and refined much faster.

Final Thoughts

Using the XPOZ MCP to analyze an online campaign fundamentally changed my workflow. Instead of using multiple data sources manually, the MCP allowed me to conduct the entire analysis through structured prompts, continuous refinement, and contextual grounding.

If you’re an analyst dealing with:

Then building your workflow using the XPOZ MCP can transform both your speed and the quality of your insights.

Prompt Example:

Generate a comprehensive social intelligence report analyzing public discourse surrounding {Keywords or brand name). The analysis must:

1.⁠ ⁠Describe the general image and positioning of {brand name} in the broader industry.

2.⁠ ⁠Include specific examples of posts, platforms, and key users shaping the conversation.

3.⁠ ⁠Provide a deep analysis of the most recent campaign {dates}, comparing sentiment, engagement, and narrative shifts before and after its launch.

Sections & Instructions

1.⁠ ⁠Introduction & Context

•⁠ ⁠Define the purpose, scope, and relevance of this research.

•⁠ ⁠Introduce {brand name} role and positioning within that context.

2.⁠ ⁠Methodology

•⁠ ⁠Outline data sources

•⁠ ⁠Describe the analytical framework:

* Sentiment analysis (positive, neutral, negative)

* Influencer mapping (reach, engagement, relevance)

* Narrative clustering (recurring themes and tone)

3.⁠ ⁠General Brand Image

•⁠ ⁠Summarize digital reputation and comparative standing vs. competitors.

•⁠ ⁠Present data-driven sentiment trends and representative posts from users.

•⁠ ⁠Include examples of influential posts (top likes, shares, or mentions).

•⁠ ⁠Identify key user segments engaging with the brand.

4.⁠ ⁠Influencers & Opinion Leaders

•⁠ ⁠Identify and categorize top influencers discussing {brand name}.

•⁠ ⁠Include details such as:

* Platform and reach

* Tone and sentiment

* Impact on conversation (e.g., started debates, went viral, etc.)

•⁠ ⁠Highlight authentic consumer voices vs. professional or sponsored influencers.

5.⁠ ⁠Sentiment Analysis

•⁠ ⁠Provide quantitative breakdown of sentiment (positive/negative/neutral).

•⁠ ⁠Visualize through charts or tables if possible.

•⁠ ⁠Highlight representative quotes or posts illustrating each tone.

•⁠ ⁠Compare {brand name} sentiment to industry averages or main competitors.

6.⁠ ⁠Impactful & Viral Content

•⁠ ⁠List high-impact or viral posts with metrics: impressions, engagements, shares.

•⁠ ⁠Analyze visual tone, hashtags, and timing (e.g., peak hours or events).

•⁠ ⁠Explain why these posts resonated with the audience.

Use coding tools and the XPOZ MCP (both instagram and twitter)

When looking for posts and leading users try looking in Hebrew and using these keywords:

{keywords}