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How to Do Your Own Market Research & Identify Your Ideal Customer
Customers today are looking for more than just products, they’re looking for a custom-tailored experience. According to a recent CEI Survey, 86 percent of consumers will pay more for a better customer experience. Of those customers, 36 percent perceive a memorable experience as one in which they receive personalized service. With new customer expectations come new ways of identifying your target market. The latest data mining methods combined with advances in technology create a marketing force to be reckoned with.
Controversial yet insightful methods of data acquisition provide business owners with access to real-time information based on customer shopping habits. Companies like Euclid help retail stores measure and optimize foot-traffic, visit duration, and repeat shopping by installing smartphone tracking sensors within the store. Using your existing Wi-Fi infrastructure, smartphone pings are tracked to show the natural flow customers take through your store. Although smartphone pings do not transfer personal data, this method of data mining could be viewed as invasion of privacy. To help retain customer trust, always make sure you have open communication about your marketing efforts.
For many years, the traditional RFM method (recency, frequency and monetary value) has helped marketers measure trends based on historical consumer information. Capturing information like purchasing frequency and spending habits provide a snapshot of the past. Rather than creating a guide to future marketing opportunities, the RFM method gauges customer value and is best used to determine who not to market to.
A step above the traditional RFM analysis model, the regression model measures customers shopping decisions based on a variety of changing variables. This type of data takes into consideration not only the purchasing frequency and spending habits but also how the data changes within given circumstances. The goal is to anticipate a desired behavior, by measuring one independent and one dependent variable. MailChimp, an e-mail marketing platform, did their own research to determine how e-mail subject lines correlate with open rates. Their findings are an example of how to use regression analysis to generate results.
The most advanced analysis method to-date, the predictive method, asses the qualities of a customer lifetime purchasing power rather than their one-time shopping history. This method allows business owners to anticipate a consumer’s needs, preferences and attitudes and how circumstantial evidence plays into the consumers purchasing decisions. Predictive factors provide insight into the on-going value of a customer by determining who will buy, convert or cancel. Companies like Foresight specialize in quantifying the impact of your customers’ store experiences and their satisfaction with your company so you can create a user experience that turns into a life-cycle of costumer loyalty.
Manage your Findings
There are a variety of software programs that allow you to manage client information. Look for systems like NetSuite’s point of sales software that also provides advanced analytics in its CRM package. This will allow you to mine the data from your current customer base and identify ideal clients. Based on those findings, choose which customers to keep and which ones to get rid of. To begin collecting data for new clients and prospects, try a combination of analysis methods and find the best fit for your company. Once you’ve gathered enough information to launch your campaign, it’s equally important to managing those results. When its time to re-analyze your target market, your campaign results will show it.
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