Whether you call it fresh powder, clean air, greenfield, a jump start or simply a unique competitive advantage, being first is scary, but it's critical.
You may look back wistfully now on the early mover advantage of companies that took SEO seriously in the early 2000s. If only you had...
Well, here's your chance to establish an early mover position in knowledge graphs. Establishing your company's leadership by creating your industry's knowledge graph will be an enormous competitive advantage. A business strategy opportunity that you can't afford to miss, particularly in conservative areas like capital equipment sales and manufacturing marketing.
Everything besides the industry knowledge and connections.
Seriously.
My goal is to simplify this so it gets done. Of course creating knowledge graphs won't be easy. And it's not a 90-day program. You need to commit to long-term work on knowledge graphs.
But here's how we get started and what happens over 90-120 days:
Basically an industry knowledge graph in a box, with quick start resources, consulting and coaching, lessons learned and best practices.
All you need to bring is the industry knowledge and connections - plus desire and some time.
I'd plan on roughly $150K/year in direct cost.
The first year you'll pay me to help you launch, and your editor/moderator for part of the year.
There will be some small technology and legal costs, and you might plan on some ads to promote it once it's up and running.
Subsequently, you'll have your editor/moderator and incidental costs. Probably $100K/year.
And of course you'll have some management time along with SME contributions from within your company.
We're on the cutting edge and we're both going to be learning as we go. Roam Research is evolving quickly, and we'll have to educate people on the value of this project.
Therefore I'm planning on only working directly with three companies on this project to create a packaged, scalable model based on that experience.
I'll only work with one company in an industry.
Early movers get the best deal. If your company engages:
First - $65,000
Second - $85,000
Third - $95,000
As manufacturing marketing rapidly evolves, leveraging knowledge graphs is not just a novel idea; it's a strategic imperative. Integrating knowledge graph technology into your marketing practices can transform complex data into actionable insights, providing a significant edge in a competitive market and extensive reach and authority.
The manufacturing sector is awash with data and expertise, stemming from various industries and different systems. Here, knowledge graphs emerge as a powerful tool. They aren't just about accumulating data; they're about making sense of it. A knowledge graph can turn unstructured data into a structured, understandable context to help users discover new ideas. This clarity is crucial, especially when dealing with the complex networks of expertise typical in manufacturing systems.
The true potential of knowledge graphs in manufacturing marketing lies in their ability to learn and evolve. This is where data scientists and machine learning come into play. Data scientists are the architects who build and refine the data model at the heart of a knowledge graph. Their expertise ensures that the graph not only stores data but also understands and interprets it.
Machine learning adds another layer of sophistication. It allows the knowledge graph to evolve, adapting to new data sources and changing market dynamics. This adaptive capability ensures that your marketing strategy remains relevant and effective, even as the market shifts.
What's important to keep in mind is that a knowledge graph isn't a purely data model. It incorporates insights, thought leadership, expertise, and other raw data in a format that helps all industry stakeholders use knowledge graphs.
In a manufacturing system, different elements - often from different suppliers and industries - must work in harmony. Knowledge graphs act as crucial components, connecting disparate parts of the system and concepts. By integrating data from various sources, they provide a comprehensive view of the market. This integration is vital for informed decision-making, allowing manufacturers to identify new opportunities, understand customer needs, and tailor their marketing strategies accordingly.
A knowledge graph in the food industry, for instance, could include nutrition, raw material, recipes, food processing, packaging, shelf-life, marketing, merchandising and maintenance perspectives.
The ultimate goal of using knowledge graphs in manufacturing marketing is to enable learning and informed decision-making. With a clear understanding of complex data, companies can make strategic decisions that are grounded in reality, not just assumptions. This clarity leads to more effective marketing campaigns, better customer engagement, and, ultimately, a stronger market presence.
As we look to the future of manufacturing marketing, knowledge graphs illustrate the creative opportunities companies have. By harnessing the power of extensive industry data, employing the expertise of new technology, and leveraging machine learning, knowledge graphs can transform the way manufacturers approach their marketing strategies. They are not just tools for storing data but powerful instruments for making sense of it and turning it into actionable strategies. In this ever-evolving market, knowledge graphs are not just useful; they are essential.
