Use Cases
These are some Customer Data use cases that you can solve with OmniPanel.
Promo Codes vs. Customer Reviews
In an age where online customer reviews are more accessible and influential in the purchasing decision than ever, knowing what actions led to the most vocal and supportive customers is vital to creating a vibrant community around your product. After all, how a customer is acquired often influences the customer-company relationship. Imagine identifying the promotions that lead to your most vocal, loyal supports. With OmniPanel, you can pull that up with a click of a button.
Breaking out Returns by Customer Segment
Returns are an inherent part of e-commerce businesses, from broken packages to customers having the wrong product expectations. However, the way many companies view these returns is on a case-by-case basis; this loses you the bigger picture and prevents you from connecting the dots of underlying issues that affect vast swathes of your customer base. Imagine you are a DTC apparel company. You want to see what categories of customers return items, ranging from repeat versus new customers or by CLV or marketing cohort. Knowing which customers are returning items will help you uncover customer insights and highlight hidden customer friction points.
Customer Feedback From Product Launch
Imagine you are a DTC apparel company that recently launched a new line of jackets for the first time. You want to analyze important customer feedback about how they view your marketing campaigns, use of the product, sizing and fit, and the resulting repurchases. Ordinarily, you would have to copy and paste the customer comments and questions by hand into a spreadsheet. But with OmniPanel, you can directly pull the relevant pieces of information automatically to complete your report.
Marketing Winback Campaigns
A batch of one of your newly introduced products was defective. You want to identify which customers were affected and directly reach out to them as part of your win-back strategy to keep their business. The problem was finding which customers were affected and how to contact them. An additional layer of difficulty was that the various ways customers responded to the issue differed. Some cases are located on your helpdesk, while some data are on your returns platform. There were even cases of customers complaining about the product online but never filling out a support request.