What You Need to Know about Gathering Customer Intelligence
Customer intelligence isn’t like competitive research. Informing yourself about your customer feels a lot like teaching yourself something you already know, except you gain more insight into how customers actually interact with your products. Rather than relying on market trends and making assumptions, you can utilize actionable data to build intelligence on your clients with the right software.
Gathering intelligence about customers actually falls under the umbrella of business analytics, and the situation can quickly get out of hand if you don’t have industry leaders guiding you. A clump of data is no use in a vacuum. Approaching it with a particular goal in mind is key for determining both what to look for, and how to read the data you find.
Personally identifiable information (PII) can also be a liability, so it’s useful to consider the potential threat that comes with hosting this information yourself. Many businesses will outsource data management because it removes that potential for trouble.
Customer feedback is one of the older mechanisms for gathering data about how the end user actually utilizes your product. What has gone right, but more importantly what has gone wrong are all clues toward making the best possible product you can make.
Not everyone will utilize feedback, and not all feedback is valuable. Good software suites that deal with feedback make it easy to identify the customers who left that critique and to ignore the data that isn’t useful. Examples of quick and easy delivery systems include sending a link via email or through social media. However, be aware that wider distribution comes with drawbacks. You might get more eyes, but less valuable feedback from actual customers.
In addition, you may want to consider what kind of survey you can present. Surveys that allow you to send something to the client, like a coupon code or a free eBook, may have a higher percentage rate. Interactive surveys also help lead to a higher completion rate.
A customer’s buying habits are very valuable. Amazon is a good example of what can happen when you understand more about the products your customers buy from you. By building profiles of purchase history, and comparing those profiles with other customers with similar buying habits, Amazon is able to find products to upsell to customers without them knowing they want it.
Predictive sales have long been the dream for retail, and Amazon is a major player so that kind of data takes years to build. Still, there are simple ways to have data you may already have. For example, do you notice that an increase in sales of one product leads to an increase in another related product? That could be a clue the two products offer some complementary service and an additional sales opportunity.
Understanding how a customer has interacted with your brand in the past can give you ideas on how to advertise to them in the future. Re-targeting is the most obvious example of this theory in practice.
Re-targeting shows customers ads only if they’ve seen your ads or your website before. The reason is twofold: the costs to utilize the service are lower than traditional outreach, and brands need exposure before they gain recognition.
Customer intelligence can be like the holy grail for business, but it requires some outside-the-box thinking to get to. The simplest way to figure out what you need is to work backwards, starting with what you want to learn about your customer.