You’ve selected your target market, developed a strategy, and put your marketing tactics into play. Yet, digital marketing isn’t a “set it on cruise control” kind of practice. There have been much marketing fails when the wrong target market is focused on.
Last week, we looked at three questions you can ask yourself when determining your target market. This week we will turn the tables and look at 3 topics to ask your customer. Accessing this information in conjunction with performing a cluster analysis can open the door to your understanding of the needs and wants of your validated target market.
One of the quickest ways to capture insights is through a survey. There are lots of free or minimal cost tools out there like Survey Monkey, Typeform, SurveyGizmo, and Qualtrics but a quick Google Search will likely result in many more. When you create a survey to capture the insights of your customers, make sure to ask the right questions and design with the end in mind. A few topics to consider include:
What is your age, race, gender, or income? Think about which of these demographic tidbits is helpful for your product or service. Only ask about the ones that matter.
How often do you shop with us? Or How often do you purchase (product or service) This will help you to understand your consumer's behavior.
How do you feel about receiving a phone call versus an email from our company? How do you feel about text messages? Ask questions that provide insight into their attitudes and beliefs. Questions that are directly related to how your company works. Make sure the survey responses are on a scale from 1 to 7. This will help provide better insights from the cluster analysis.
A short survey capturing demographic, behavioral data, as well as, your customer's attitudes and beliefs will let the data do the talking to create appropriate segments that are similar to each other and distinct from others.
Figure 1: how 3 segments feel about the importance
of price and how frequently they purchase
Cluster analysis helps you to find customer groups of similar people based on finding the smallest variations among customers within each group. This analysis helps you to select the appropriate number of clusters automatically by evaluating the similarities of the clustering of various numbers. The clusters can provide important insights to help you to create personalized marketing programs that provide relevant offers and incentives aligned with their wants, needs, and preferences.