Competitive Intelligence and Competitor Analysis

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(pleasant music) (cymbals ringing) In these lessons, we'll discuss utilizing market and competitor data analysis to develop a business strategy that relies on evidence of performance. And advantages of market and customer outcomes for effective strategizing. Altogether, you'll learn to design your business strategy around a thorough examination of your key competitors. The combination of competitive intelligence and the analysis of the competition can help a company achieve a greater competitive advantage, and a sustainable competition strategy. So what exactly is data? Data is defined as facts or information used to calculate, analyze, or plan something. When we want to understand our competition and our own offerings, we need to gather data that pertains specifically to those critical criteria. To do this effectively, we can focus data collection for analysis on a few important issues. Proactive targeting, competitive intelligence, real-time performance, and predictive analysis. Traditional strategies rely on advertising and promotions to pull customers into a store to make a purchase decision. Proactive targeting uses additional push strategies to motivate customers during the shopping experience, to increase purchase decisions. A pull strategy offers a discount to shop at a particular time. And then the push strategy gives an additional incentive once they're in the store, physically or online, to encourage an immediate purchase and avoid second thoughts or comparative shopping. It's difficult to get competitive intelligence, since they're not likely to provide you with their data. But it's not impossible to get close. Once you gather as much information as possible about the market, key competitors, and the customer's perspective, it can lead to an efficient and effective competition strategy. It's best practice to consider the internal controllable elements for your core competencies, versus external uncontrollable elements of the competition's competencies. It can be inefficient to analyze internal and external elements only before and after specific periods of time. Instead, it might be more efficient and effective when it's inclusive of current real-time performance analyses. While a bit of a challenge to measure during actual performance, real-time analysis helps identify costly processes and increase experience curve effects by streamlining production. It requires understanding the market, the customers, and the competitors. Through that, you can compare projections of performance expectations against the actual performance results, with the real-time performance to judge where improvements can be made during the entire cycle of production. And eventually, increase the level of control. There are a wide variety of marketing tools that can be used for predictive analytics and estimating future performance. It comes down to knowing what data is useful, and collecting enough to show accurate predictions. Which analysis method or tool you decide to use will rely on the market and offering type. But that won't be as important as collecting appropriate and accurate data that's both reliable and as complete as possible. Collecting and analyzing competition data and information is important, but how can we use that information for creating business strategies? In the past, business plans focused on developing competition strategies based on the idea that more data gives you a competitive advantage. While more data means greater reliability in business strategizing, it's no longer accurate to say, it gives you an advantage. The digitalization and advancements in technology have put more information in the hands of the consumer. The nature of the competition has always changed with technological and digital developments. Multinational, transnational, and global corporations that historically maintains superior market positioning and control are now facing new competition from the rise of mini multinationals. These are small to medium enterprises, developing global strategies made possible with modern, low cost, technological, and digital resources. Because of this, it's best practice for a company to continually collect and analyze well maintained, real-time data to remain competitive. And there lies the real challenge and usefulness of data analysis as competitive intelligence. Does the firm have the capability and budget to go global and remain competitive?