Discover the Game-Changer in Connecting Security & Resilience Capabilities with Stakeholder Needs

There is a growing number of Security Risk Advisories and related services jostling for position the market. To get and stay ahead, all companies must promote their differentiated capability. The challenge is to get your solution in front of buyers quickly, consistently, and in the most cost-effective manner.

• Competing for attention through social media is getting harder and more expensive.
• The market is drowning in irrelevant, ephemeral, and disjointed content.
• Knowing what’s available or sourcing capability/expertise at the right time and place is challenging.

Trade Shows are no longer the answer!

Marshal is building Machine Learning Artificial Intelligence (ML/AI) to channel recommendations* about  suppliers to our stakeholder community, according the specific and evolving interests of each individual.

We’ve created a network to help users discover Security & Risk Management content that they wish, and need, to know about. The industry-exclusive platform will enable the promotion, sourcing, filtering, following, continuous reference and update notifications of niche and diverse capability – be it Intelligence Reports or Training Courses; C-UAV solutions or Civilian Armoured Vehicles; Podcasts or Events, to name a few – either to enable followers to remain current with the market, or to conduct research into supplier availability and evaluation with a view to and potential procurement of services.

Here’s how it works in broad terms:

Conceptually, an industry-exclusive demand generation platform will cut out the noise to distribute services, updates and innovations automatically, at speed and scale, to stakeholders, in a customisable feed.

1. Data Collection: We collect  data on user interactions, such as search history, click through, likes/follows, dislikes/unfollows, comments, and even the amount of time spent on each exhibit page.
2. User Profiles: Based on this data, we build user profiles to understand each user’s preferences and interests.
3. Content Analysis: We analyze the content of Exhibits using various machine learning techniques. This includes extracting metadata, understanding Exhibit topics, and evaluating engagement metrics.
4. Collaborative Filtering: We use  collaborative filtering techniques to recommend Exhibits. This involves identifying patterns and correlations between the viewing habits of different users who have similar tastes.
5. Ranking Algorithms: Machine learning algorithms rank Exhibits by predicting how likely a user is to engage with a specific Exhibit. Factors like relevance, freshness, and user engagement are considered.
6. Personalization: The system personalizes the recommendations shown in the User’s Library based on the user’s profile and behavior.

The goal of these machine learning models is to optimize user engagement by recommending content that matches user preferences, thereby increasing the likelihood that users will browse content and access / follow more exhibits to help them find the resources they need, and to generate more demand for the supplier.

Users create and dynamically manage Exhibit Libraries** by browsing the various Channels and Markets within the platform to follow showcased services, then gain access and refer quickly to those services that they want to keep updated on. AI tools within the Library will facilitate the sourcing of similar and adjacent products and services for more efficient overview and comparison of the diverse and niche capability on offer.

*Disclaimer: AI generated recommendations are not endorsements. Users should conduct due diligence before acting on information, or agreeing to a formal commercial engagement with any services promoted via the platform.

**Coming soon. Full service access will be available with a monthly or annual subscription.

Marshal is a powerful and exclusive Digital Marketing & Recruitment platform for the global Security, Risk Management & Resilience industry. 

Visit our curated Jobs Map for latest vacancies across the industry.