Marketing has always been about innovation. Today, many marketers are using data analysis to generate innovative marketing strategies and using visualization tools to depict the flow of campaign performance as well as customer experience.This article will show you how marketers are trending towards data analysis, which can provide useful insights regarding your target market’s behavior and preferences, enabling you to redesign your marketing strategy.Data analysis has played an important part in marketing since the 1980s when the first million-dollar advertising campaign started.
This is when bigger companies like McDonald’s or Coca-Cola started to gain power and dominance over the smaller companies who did not pay much attention to using data in their marketing strategies.As more new technologies, like computers, B2B Email List were introduced to businesses, marketers and advertisers began to use their amazing potential for data analysis and promotional techniques that would optimize their marketing.What is Data Analysis?The better you know your customers, the more you can tailor your marketing to them. Data analysis is the data-driven process of discovering new information. First, you collect data, whether through surveys, focus groups, or analyzing customer transactions. Next, you analyze the data, looking for patterns and relationships.Finally, you decide what action to take. Data analysis can be used for discovering trends, predicting probabilities, and measuring outcomes.
Marketing companies use data analysis to help customers choose what to buy when to buy it, and where to buy it.Today, data analysis is less expensive than ever. (In 2007, Home Depot launched a program that allows regular customers to download information about their purchases in a format they can analyze with a spreadsheet.) With data analysis, companies can capture and tailor marketing not only to their individual customers but also to their potential customers as a business growth strategy.The 5 Big Changes Data Analysis Brought to MarketingWe all know that data is important. But data is only valuable to the extent that it enables better decisions.Too often, data is treated as a number. For example, suppose you study how people use a product. You ask people whether they did X, Y, or Z with it, and then look for correlations.