As consumers continue to hold onto their devices for longer periods of time, it’s more important than ever to build out a comprehensive data analytics program. But if you’ve been running a mobile device trade-in program for years, you already know how data can help you grow your program.
The first step of any trade-in data analytics program should be to focus on the device level. Data analytics should give you key insights into secondary market trends that will help you offset the costs of customer acquisition and promote early upgrades for customers with equipment installment plans (EIPs).
Finding the perfect balance between pricing, timing, and promotion for specific devices is just one way that data analytics can improve trade-in programs, though. Your next step should be to dig deeper and focus data analytics on the transaction level.
Maximizing Revenue Following Device Trade-Ins
Device-level analytics ensures that you are optimizing your trade-in program so you are setting the perfect trade-in values while maximizing profits in the secondary market, both of which are determined by device make, model and condition. You maintain a steady supply of devices for the secondary market, keep customers on installment plans, and set the perfect prices for device trade-ins according to condition and market value.
Transaction level data insights is an untapped use case that will help you maximize revenue through your trade-in program. There are three keys to unlocking this potential for your own trade-in program.
The first key is simply gaining the knowledge of what customers do with the money they receive from a device trade-in. Without visibility into this transactional activity, you won’t be able to gain revenue-driving insights. Are your customers applying the trade-in money to their device bill? Buying accessories? Adding new services to their plans? Effectively collecting that data will set you up for greater success with your trade-in program.
The second key is taking that knowledge and using it to gain incremental value from each trade-in. In the past, you might have been happy just to increase the number of consumers who traded their devices when upgrading. Now, you want to use data analytics to maximize the value of every transaction. Consider how the following three ways customers apply their trade-in value impacts your revenue:
- Bill Application: This is the most common way for customers to apply trade-in value. It provides a level of convenience that maximizes the customer experience. But as far as incremental revenue goes, it provides fairly low value.
- Accessories: Cases, speakers, screen protectors, and other accessories have long been the all-stars of trade-in programs. Because these items have such high margins, getting customers to apply trade-in credits to accessories can maximize revenue compared to simply offsetting costs with a bill application.
- Services: An emerging path to maximizing the revenue potential of your trade-in program is additional services. Plans aren’t as standardized as they once were. Now, consumers can invest in TV services, connectivity for devices like tablets and smart watches, banking services, and more. Getting customers to add these services to their plans by reducing some of the costs with trade-in credits can give you consistent revenue streams for months to come.
The third key to maximizing trade-in program revenue with data analytics is a focus on performance management. Data analytics should give you critical insights into sales rep performance that help you optimize productivity across your stores and improve training.
All three of these key components will help you maximize revenue in your trade-in program. The only challenge is figuring out how you can collect and analyze the right data to get the revenue-driving insights you need.
Get the Business Insights You Need to Maximize Revenue
Collecting and analyzing device-level trade-in data is critical for carriers, retailers and OEMs to optimize their programs. Going a step further to derive insights from every trade-in transaction is just as critical.
The key is to implement a data analytics platform that’s purpose-built for maximizing every aspect of a mobile device trade-in program.
At HYLA, we deliver a Business Insights component that provides performance and KPI tracking that will make the most of your trade-in data. From user penetration rates to store productivity rates, pricing discrepancies, sales associate performance, and more, our Business Insights features will put you on a path to maximizing revenue through your trade-in program.
If you want to learn more about Business Insights and the HYLA data analytics platform, contact us today for a free demo.