What’s the difference between goal setting and strategy? As a marketer we need understand that difference to effectively create a marketing campaign. Goal setting is developing a goal that needs to be accomplished. These goals can be a mix of personal goals or marketing campaign goals. Goals are usually created by aligning them to the organizational goals of a company. These goals are usually what a company wants to accomplish during a marketing campaign. The steps we take to accomplish a goal is the strategy. The strategy is usually crated by having a step by step plan on how to accomplish a certain goal. For instance, if my personal goal was to lose weight in three months. The strategy would be to work out 4 to 5 times a week, eat healthier, weight training and cardio. By completing this strategy, I will be able to complete my goal of losing weight. Goal setting and strategy are both interconnected, you can’t complete one without the other.
Thinking about Big Data sends me into a spiral of looking at so much information on consumers, to which I have no idea where to start. Big data is a list of information usually extracted from a company’s CRM system. Utilizing big data can give a company the information needed to properly analyze and even retarget consumers in order to build profit. The hardest part is trying to analyze the data. There are two ways to make sure your big data is analyzed correctly. One, understand your marketing objective, what question do you need answered? Knowing what questions need be answered will help you organized your data to find the answers. Two, eliminate incomplete information within your big data. For instance, if a consumer didn’t complete the company’s sign-up sheet in its entirety, missing fields such as the age, sex, or income, then you eliminate that data based on the marketing objective your trying to accomplish. If your objective was finding an average age of your consumers, then eliminating that consumers information, can provide more accurate results. Understanding big data can become overwhelming, but if you use these two techniques you too can become a big data expert.