HOW MARKETING ANALYTICS IS IMPACTING MARKETING ACTIVITY
June 21, 2018
Measuring and forecasting consumer behavior has made giant strides forward in just the past few years. Previously, companies often struggled to comprehend the specific role that each marketing activity played in the purchase decision. What are some of the latest strategies emerging from data analytics?
Personalization – 4 out of 5 consumers value personalization, are willing to share personal data with trusted companies and are more likely to engage in business with a company if their experience is personalized. Research indicates as much as 50% of customers are likely to switch if interactions are not personalized. Examples of personalization – AMAZON provides personalized recommendations to enhance the browsing/shopping experience; STARBUCKS – gamified mobile app; and NETFLIX – personalized viewing recommendations;
Forecasting – Predictive analytics is on the rise. Consumer data isn't just used to explain past behavior but it also can be utilized to predict future behavior and provide insights regarding customers. Customer insight examples include ideal time(s) for interaction, channels and mediums for message receptivity, interests and perceptions and/or social data;
Consumer Understanding – It is now possible to identify specific consumers/households, outline their priorities, interests and behaviors, ascertain where they like to "hang out" (social platforms, etc.) and understand their key perceptions. A determination can now be made precisely how and where a brand might best engage the customer;
Full Funnel Strategies – Customers no longer go from awareness to purchase in a strict linear fashion. Instead, consumers often utilize search tools, social media and product review sites to enhance their research of products. Marketing now needs to be tailored to meet the specific demands of consumers when and where the consumer desires.
What is imminently important today is to: (1) comprehend your customer as thoroughly as possible through analytics; (2) not be afraid to measure exactly what works in converting prospects to customers; and (3) understand why what works actually works.
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