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Case Study

Case Study: How AI can be used to understand demand and identify customers for Embedded Cyber?

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Your team provided our customers with an organized understanding and comprehensive visibility into the Federal embedded cybersecurity system market. For supplier members, you answered one of the most difficult questions to answer when engaging with the public sector, ‘Who buys what I sell?’. For our current Government customers, you helped answer ‘Who buys what I buy?’.
Federal Intermediary Organization
Executive Director

Summary and Results

300%
additional
potential customers

This case study illustrates how PSF’s AI-MI (Artificial Intelligence for Market Intelligence) enabled Market Planning and Customer Matching workflow:

1. As part of its goal to better serve its membership of emerging companies as well as its government customers, this federal intermediary organization wanted to get full visibility into federal government demand for embedded cyber. Their management team knew that existing market research methods wouldn’t work and there were potentially many other programs with needs that they weren’t able to identify.

2. Provides government agencies with a way to create transparency around their procurement spending while identifying other programs across the government they can collaborate with.

Results: For an intermediary organization, AI-MI matched over 300% of additional potential customers across federal defense and civilian agencies, utilizing PSF’s artificial intelligence market planning technology and GovShop platform.

The Need

To support sales and market planning, identify all potential customers of embedded cyber solutions in the federal market

As part of its goal to better serve its membership of emerging companies as well as its government customers, this federal intermediary organization wanted to get full visibility into federal government demand for embedded cyber. Their management team knew that existing market research methods wouldn’t work and there were potentially many other programs with needs that they weren’t able to identify.

Approach

Used Public Spend Forum’s AI-enabled Market Planning and Customer Matching workflow, which leverages our comprehensive demand database and AI-MI™ algorithms, to identify potential customers for embedded cyber

To rapidly identify the full potential market and customers for embedded cyber, we used Public Spend Forum’s AI-MI™ Market Planning and Customer Matching (MPCM) workflow. The MPCM workflow integrates and leverages several of PSF’s demand datasets along with various AI-MI tools specifically designed to support market planning.

First, we identified the “ontology” and market segments (“capability clusters”) for embedded cyber

Basic market research is flawed in many ways, especially when it comes to defining a market. Without the right keywords and understanding of how a market may be evolving over time, the research that follows results
in missed opportunities. A specific example: a mobility solutions company used the term “urban transportation” to search for potential customers. Using our ontology tools, we also identified “city transportation” as a term used by cities. Jackpot – the new term resulted in an additional opportunity that would’ve been missed otherwise.

For this specific market planning exercise:

1. To start, we identified the scope and definition of “embedded cyber”, utilizing a tool we call OntologyMatch™. The goal of this tool is to ensure we have a holistic definition of a market based on keywords, so we don’t miss any potential customers which generally occurs with typical search methods. The key to conducting the ontological analysis is having comprehensive datasets, which we have developed over the past 4 years.

Intensity map
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2. We then developed an overall market segmentation, grouping into 15 capability clusters based on the nature of needs and requirements. This approach is especially useful in understanding the way government agencies or any buyers for that matter organize requirements versus how suppliers organize their capabilities.

The illustrations below show some of the AI-MI outputs that ultimately result in the “Embedded Cyber Capability Clusters.”

Embedded Cyber Capability Clusters

Second, we ran our CustomerMatch™ algorithms against our GovShop Demand datasets

Even if you have the market taxonomy and keywords identified, the next problem most sales teams run into is a lack of data related to potential customers. The fact is data on government programs and demand is buried deep inside websites and documents. The typical approach, which most small businesses can’t afford,
is to dig through tons and tons of information. That is typically an endless exercise.

That is why we have built out GovShop Demand datasets to be as comprehensive as possible while we append additional demand data for every client and market planning exercise.

Utilizing our demand datasets:

  • Our AI-MI™ algorithms analyzed 2000+ federal programs, quickly narrowing matches down to 250+ potential programs with the need for embedded cyber
  • Additional validation resulted in matches with 120+ program offices, with detailed customer profiles of each office used for prioritization
AI-MI Program Office Analysis

Results

Rapid market visibility and expansion of targets by over 300%

  • Comprehensive market visibility – expanded visibility beyond the current Army market into the entire defense and civilian market to include 120+ programs
Sources

Sample of Identified Program Offices

Sample of Identified Program Offices

In addition to identifying direct customers, PSF’s market planning approach includes identifying potential contracting and partnership channels including prime contractors already doing business with the government. In this case, the customer preferred not to identify partnerships but specifically focus on contracting channels. The result:

  • Identified 100+ channel and contracting pathways to create a faster path to market

Sample of Identified Contract Channels

Sample of Identified Contact Channels

Customers and channels are great but ultimately you need people to call! The final result also included specific points of contact for each target, a part of our growing community.

Innovation Awards for SBIR/STTR – Supplemental Analysis

The customer also requested an additional analysis to identify emerging and diverse companies that had already won innovation grants or awards from the federal government. Using our enhanced SBIR/STTR database that includes AI-enriched definitions for each award, we:

  • Identified 335 SBIR/STTR award winners related to the embedded cyber, for FY2019-FY2021
SBIR/STTR Award
SBIR/STTR Award Breakdown by Agency

Sample of Identified SBIR/STTR Awarded Suppliers

Sample of Identified SBIR/STTR Awarded Suppliers
How Can We Use AI-MI to Help You?
Please fill the form or contact us directly at sales@publicspendforum.net to learn more about Public Spend Forum’s Market Planning and Customer Matching service