Key Types of Market Intelligence

Modern businesses need in-depth knowledge across various aspects of their operations to succeed in a changing world. Key areas include competitive intelligence, product intelligence, market understanding, and customer understanding. Each of these areas is crucial for making informed decisions and gaining a competitive advantage.

Competitive Intelligence

What is Competitive Intelligence?

Competitive intelligence can be defined as the systematic gathering of information about competitors and/or market conditions to assist in the process of making strategic decisions. Competitive intelligence must be conducted in a manner that is lawful and from open-source information with credible reports arising from markets.

Why Is Competitive Intelligence Needed?

Competitive intelligence helps a business in strategizing for effectively dealing with the actions of competitors by mitigating risks and maximizing opportunities.

One of our customers, a logistics company, was struggling to compete in a new market. They were getting undercut on price, and their delivery times were lagging behind the competition. They started by gathering competitive intelligence on their main rivals—looking at everything from shipping routes to pricing strategies. What they found was that their competitors were using a more efficient network of regional hubs, which allowed them to cut costs and reduce delivery times.

rmed with this insight, the company restructured its logistics network, invested in new regional hubs, and negotiated better rates with local suppliers. Within a year, they not only matched their competitors on price and delivery times but actually gained a market share by offering more reliable service. This is the kind of impact competitive intelligence can have when it’s done right.

Elements of Competitive Intelligence

1. Data In Competitive Intelligence

Let’s talk about competitive intelligence in the global supply chain space. First up, when we’re talking about the data you need, it’s all about getting the right mix. You’re looking at trade data, which tells you who’s moving what, where, and how much of it. This includes import/export data, shipping manifests, and even port records.

Then, there’s market data—things like pricing trends, demand forecasts, and competitor activity. You want to know not just what your competitors are doing, but also what the market is hungry for. And let’s not forget financial data—balance sheets, profit margins, and investment patterns give you a peek into how strong your competitors really are. All this data gives you a 360-degree view of the competitive landscape.

Now, you can’t stop there. The next level is diving into operational data. This is where you look at supply chain specifics, like lead times, inventory levels, and supplier performance. Understanding these details can help you identify where competitors might be facing bottlenecks or delays. And then there’s compliance data—regulatory filings, sanctions lists, and tariff changes.

This is crucial because in global supply chains, one regulatory hiccup can throw everything off course. And finally, don’t overlook customer sentiment. What are customers saying about your competitors? Social media, reviews, and customer feedback surveys can give you insights into how well your competitors are serving the market and where they might be vulnerable.

2. Competitive Intelligence Analysis

Once you’ve got all this data, the next step is analysis. You’re not just collecting numbers—you’re turning them into actionable insights. Start with benchmarking, where you compare your performance to industry standards or specific competitors. Then there’s trend analysis, which helps you spot patterns over time—are your competitors gaining or losing market share? SWOT analysis is another big one; this lets you map out strengths, weaknesses, opportunities, and threats both for your company and your competitors.

Scenario planning is another powerful tool—what if your competitor launches a new product or enters a new market? How will that affect your supply chain? And then there’s benchmarking, where you compare your performance metrics against those of your competitors. This gives you a clear picture of where you’re leading and where you need to catch up.

You’ll also want to do gap analysis to identify areas where your supply chain could outperform others, like faster delivery times or lower costs. And of course, predictive analytics comes into play. By forecasting trends based on historical data, you can anticipate moves your competitors might make before they happen.

3. Competitive Intelligence Tools

To do competitive analysis effectively, you’ll need some solid tools. For starters, business intelligence platforms are a must—they can aggregate and analyze data from multiple sources in real time. Tools like Trademo Intel, a supply chain intelligence, for instance, are great for digging into global trade data, helping you track competitors’ shipments and identify market opportunities.

Then there’s supply chain management software that integrates competitive intelligence, giving you a comprehensive view of your supply chain alongside your competitors’. Advanced analytics tools can help with predictive modeling and scenario planning, while market intelligence platforms can keep you updated on economic indicators and market trends. The right mix of these tools not only makes the process more efficient but also ensures you’re getting the most accurate and actionable insights.

Product Intelligence

What is Product Intelligence?

Product intelligence is the process of gathering data about company products to improve their functionality and promote innovation. This would entail assessing product usage, customer feedback, and competitor products to make enlightened product development and market positioning decisions.

Why Is Product Intelligence Needed?

Product intelligence enhances features and increases consumer satisfaction. It promotes innovation by allowing firms to make data-driven decisions to improve product satisfaction based on market demand.

One of our cutomers, a global electronics manufacturer were struggling with fluctuating demand and high inventory costs. By leveraging product intelligence, they integrated data from their suppliers, market trends, and even weather forecasts. They used predictive analytics to forecast demand more accurately and optimized their inventory levels across multiple regions.

The result? They reduced their inventory holding costs by 20% and improved their on-time delivery rate by 15%. It wasn’t just about collecting data; it was about using that data intelligently to drive real business outcomes.

Elements of Product Intelligence

1. Data In Product Intelligence

When we talk about product intelligence in the context of a global supply chain, the data you’re working with is everything. You’re pulling in information from all corners—starting with your internal data like production costs, lead times, and inventory levels. Then, you’re looking at external data: market trends, competitor products, and customer demand signals.

But that’s just scratching the surface. You also need to consider regulatory data, especially if you’re dealing with multiple countries, as well as environmental data, like the impact of weather on your supply chain. This data gives you a comprehensive view of how your product is performing, not just in isolation but within the broader market and operational context.

Now, let’s go a bit deeper into the types of data you need. You’re going to need SKU-level data—right down to individual product codes. This lets you track specific products across different regions and markets. Add to that your historical sales data, which helps you understand trends over time. And don’t forget about supplier data, which is crucial for understanding your upstream risks.

You want to know not just who your suppliers are, but how reliable they are, how quickly they can respond to changes, and whether they’re facing any disruptions of their own. All of this data, when combined, gives you a 360-degree view of your products’ journey through the supply chain, from raw material to end customer.

2. Product Intelligence Analysis

So, what do you do with all this data? This is where the analysis comes in. You’re running demand forecasting models to predict how much of a product you’ll need and when. You’re also doing cost-benefit analyses to figure out the most efficient way to produce and deliver your products.

Margin analysis is key too—understanding which products are driving profits and which are dragging you down. And let’s not forget about risk analysis. You’re assessing geopolitical risks, supply chain vulnerabilities, and even potential reputational risks if you’re sourcing from sensitive regions. The goal here is to make data-driven decisions that optimize your supply chain while minimizing risks.

3. Product Intelligence Tools

Now, let’s talk about the tools that make all this possible. You’ve got your traditional ERP systems, which are great for managing internal data. But on top of that, you’re likely using advanced analytics platforms like Tableau or Power BI for visualizing complex datasets. Machine learning tools are increasingly becoming essential, especially for predictive analytics and anomaly detection.

Then there are specialized supply chain management tools like SAP Integrated Business Planning or Oracle SCM Cloud, which help you manage everything from demand planning to supplier collaboration. These tools don’t just crunch numbers—they help you visualize data, identify patterns, and make informed decisions in real time.

Market Understanding

What is Market Understanding?:

Market understanding incorporates vast and deep knowledge of industry trends, competitive dynamics, and economic factors. It uncovers opportunities and risks by analyzing strategies against current market conditions. As, Demonstrated through the applications of market intelligence (MI), understanding global industry trends helps businesses navigate these dynamics and adapt their strategies effectively.

Why is Market Understanding Important?

Understanding the market is important in creating diverse strategies to optimize opportunities while trying to minimize risks. It enables the business to adapt to changes and position itself competitively.

We worked with a logistics company that was struggling to keep up with demand fluctuations in the global market. They started using a combination of market data and predictive analytics to better understand demand patterns across different regions. By integrating this data into their supply chain management system, they were able to optimize their order levels and reduce transit times.

The result? They saw a 20% improvement in order fulfillment rates and a significant reduction in operational costs. This wasn’t just about having the right data; it was about using that data effectively to make smarter, faster decisions that directly impacted their bottom line.

Elements of Market Understanding

1. Data In Market Understanding

First, let’s talk about the kind of data you need to really understand your market. You’ve got to start with a broad range of information—think economic indicators, trade data, and industry reports. This gives you the big picture of the global landscape. You’ll also need data on supply and demand trends, both globally and in specific regions.

For example, knowing the demand for certain raw materials in Asia versus Europe can help you make smarter sourcing decisions. Then, there’s competitive data. You want to know who your competitors are, what they’re doing, and how they’re performing. This can come from market research reports, public filings, or even customer feedback. And don’t forget about regulatory data—import/export regulations, tariffs, and trade agreements can all impact your supply chain strategy.

Next, you want to dive into more specific, company-level data. This includes your sales data, inventory levels, lead times, and cost structures. You need to understand how your company is performing in the context of the broader market. For instance, are your lead times competitive? Are your costs in line with industry averages? Customer data is also crucial—what are their buying patterns, and how satisfied are they with your products or services? This kind of detailed, granular data allows you to see how well your supply chain is aligned with market demands and where you might need to make adjustments. And with globalization, you’ll also want to track geopolitical events that could disrupt your supply chain—like trade wars, natural disasters, or political instability in key regions.

2. Market Understanding Analysis

For analyzing market data, start by conducting a series of analyses to get insights into market trends and your company’s performance. A market segmentation analysis can help you understand different customer groups and how they might be affected by changes in the market. SWOT analysis (Strengths, Weaknesses, Opportunities, Threats) is another tool you can use to evaluate your position in the market. This helps you identify where you’re strong and where you need to improve, as well as spotting new opportunities or potential threats.

You might also run a supply chain risk analysis to identify vulnerabilities in your operations—whether that’s reliance on a single supplier or exposure to volatile markets. The key here is to use the data to inform your strategy and make data-driven decisions.

3. Market Understanding Tools

Business intelligence platforms are a must—they can aggregate data from multiple sources and provide real-time insights. Tools like SAP, Oracle, or even more specialized platforms like Trademo Intel for global trade data can help you track everything from market trends to supplier performance. Predictive analytics tools are also essential—they use historical data to predict future trends, helping you anticipate market shifts and adjust your strategy accordingly.

And let’s not forget about AI and machine learning—they’re becoming increasingly important for analyzing large datasets and uncovering patterns that might not be immediately obvious. These tools can give you a competitive edge by enabling you to make faster, more informed decisions.

Customer Understanding

What is Customer Understanding?

Customer knowledge involves analyzing demands, preferences, dissatisfaction, and behaviors, which is essential for product differentiation, satisfaction, and loyalty. Effective marketing techniques enhance customer understanding, while market intelligence technologies are crucial for compiling and analyzing customer data.

Why Is Customer Understanding Important?

Customer understanding is essential for the personalization of marketing, the improvement of products and services, and the enhancement of satisfaction of the customer. Businesses are capable of designing only some of the targeted strategies and offering relevant value to build long-term loyalty from existing ones.

Trademo worked with a global logistics company that wanted to improve their customer service. They started by analyzing their customer data and realized that a significant portion of their high-value clients were experiencing delays in delivery due to regulatory hold-ups at customs. By digging deeper, they identified the specific routes and products that were causing the most issues.

With this insight, they were able to proactively adjust their logistics strategy, rerouting shipments and improving documentation processes. Within six months, they saw a 20% increase in customer satisfaction and a 15% boost in repeat business. It wasn’t just about understanding their customers—it was about using that understanding to deliver better, faster, and more efficiently.

Elements of Customer Understanding

1. Data In Customer Understanding

when we talk about customer understanding in the global supply chain, the data you need is the starting point. You’re going to be looking at everything from customer purchasing behavior to market trends and demand forecasts. This might include historical sales data, order frequency, and even feedback from customers about your products or services.

Then there's the more granular stuff—like delivery times, returns data, and how often customers are reordering specific items. All this data paints a picture of what your customers want, how they want it, and when they want it. It’s like having a window into their decision-making process, which is crucial for staying ahead in a global market.

Next, you’ve got to think about the external data that influences customer behavior—things like economic indicators, trade regulations, and geopolitical risks. For example, shifts in trade policies or tariffs can drastically change purchasing patterns, especially if you’re dealing with cross-border transactions. You’ll also want to pay attention to trends in your specific industry.

If there’s a surge in demand for sustainable products, for instance, and you’re not tracking that, you could miss out on a big opportunity. By combining internal and external data, you’re not just reacting to what your customers did last quarter—you’re anticipating what they’ll need next quarter.

2. Analysis of Customer Understanding

Once you’ve got all this data, what do you do with it? You start by segmenting your customers—grouping them based on similar characteristics like buying behavior, location, or industry. Then, you analyze each segment to understand their specific needs and pain points.

Predictive analytics comes into play here, where you can forecast future demand based on past behavior and external factors. You might also run scenario analyses to see how changes in the market—like a new competitor entering or a shift in raw material costs—could impact your customers. The goal is to not just know who your customers are today but to predict what they’ll need tomorrow.

3. Tools For Customer Understanding

For the tools, you’re looking at a mix of traditional and advanced technologies. Customer relationship management (CRM) systems are a must—they help track interactions and preferences. But you’ll also want to leverage big data analytics platforms that can handle large datasets and offer insights in real-time. Machine learning algorithms can help with predictive analytics, identifying patterns you might miss with manual analysis. Trademo leverages machine learning to provide valuable insights into such trends.

And then there’s the use of AI-driven tools that can automate much of the data processing, freeing you up to focus on strategic decisions. The right tools don’t just make the process faster—they make it smarter.

In Summary

Four critical types of market intelligence—competitive, product, and market and customer understanding—are important for any business in the fiercely competing market today. These kinds of intelligence enable a business to adapt to new situations, become opportunistic, and maintain an edge over competitors. Global trade data enables businesses with analysis on all these types of market intelligence.

• Competitive Intelligence: Trade data of competitors helps analyze and monitor their business closely.
• Product Intelligence: Product descriptions and trade volumes go a long way in product intelligence.
• Market Understanding: Global trade trends help identify shifts in different markets and plan better.
• Customer Understanding: Analyzing a customer's trade data helps know a lot about their business health, suppliers, and buyers.