How to Understand the Impact of iPhone 15 on the Secondary Mobile Market Using Predictive Analytics

Apple’s latest iPhones were released in early September, and as usual, they started shipping soon after the announcement. This release consists of a Standard and Pro version, each available in two sizes and various memory configurations. Despite a long-rumored move to USB-C (which could be a must-have feature for some), the iPhone 15 doesn’t make much of a leap forward in terms of performance or features. From a consumer perspective, these advancements are largely iterative, with this upgrade cycle driven by contracts and retailer incentives rather than hype.

The launch prices for these newer models aren’t much different from past years, but they’re still premium devices, ranging from $800 to $1600. Naturally, consumers are looking for any way they can to get prices down, and many are perfectly content to return their current device in exchange for credit toward a new device.

Naturally, securing a trade-in that is fully functional and still premium has become a top priority for carriers and retailers.

Entering the secondary mobile market

The secondary market (the market for purchasing used devices at the consumer or enterprise level) continues to grow much faster than the new device market. In reality, there are several reasons and implications for this trend.

Catalysts like COVID-19 have driven many people to purchase additional devices (devices for children’s education, remote work, entertainment) as they are stuck at home, and often these buyers have been eyeing the used market and maintaining their habits since the pandemic. It sank.

Another key factor driving the used market forward is trade-in, which is one of the reasons why iPhone and Apple launch events are more important than ever. As any smart consumer knows, every carrier in America has endless promotions focused on reclaiming your old phone and offering you a discount on a newer model or credit for other items or services. This subsidy model means that high-quality devices enter the secondary market at a higher rate than before, each of which needs a home.

Before we discuss how the launch of the iPhone 15 will impact the secondary market specifically, let’s discuss how iPhone launches have historically played out in relation to the secondary market and some of the factors driving the iPhone market as a whole.

What have the iPhone launches been like over the past few years?

In pre-Covid times, these launches and declines in the value of Apple devices were very predictable, always following a very stable and easy-to-understand curve.

This chart shows the resale price of several iPhone models over a 60-month period as a percentage of their original retail price.

Of course, depreciation was quite simple and slightly accelerated in connection with new releases. Of course, nothing is as simple as it used to be, and major market changes have had a macro-level impact on the prices of used devices in the B2B market.

What large-scale, macro-level factors influence B2B markets?

The most influential drivers of the Used iPhone B2B market are::

• Growing demand for refurbished iPhones
  Domestic demand for used, certified pre-owned, certified renewed, and refurbished devices is increasing. Consumers now have multiple platforms to purchase these used devices, and rising direct-to-consumer prices have driven up B2B prices, revealing some interesting trends in the data and changing the shape of the traditional depreciation curve.
• supply chain issues
  Supply chain disruptions, a topic exhausted after years of COVID lockdowns, still occur due to disasters, geopolitical events, wars, etc., and these factors are always on analysts’ minds when looking at mobile resale data.
  
• market share
  Market share tends to decline. Not to mention the never-ending battle between Apple and Samsung for smartphone supremacy, we regularly see new competitors emerging. We make sure to look at the unit level, which devices constitute the market. This is because it changes trends and affects downstream prices.
• inventory level
  A basic principle of economics states that whenever a producer supplies large quantities of a particular good to the market, the value of that good is affected. And this is another thing our analysts are paying attention to. Several times in the past, industry leaders have pushed the panic button, releasing a series of devices on the market that have caused price collapse. These events are highly representative of the human element of markets that can have observable impacts at a macro level.
• Consumer Spending and Inflation
  Whether buying new or used, each consumer has his or her own budget and balances mobile device purchases with other financial responsibilities. Although mobile phones have proven to be a priority in many people’s lives, economic conditions and inflation will certainly affect the number of devices sold. New devices in particular affect trade-in value.
• competitive discount
  Apple is famous for maintaining its MSRP and, as a premium brand with very strong products, rarely offers competitive discounts or promotions. However, this phenomenon remains on B-Stocks’ radar. Some OEMs use these programs to lower the prices of new devices enough to steal business from others or discourage consumers from buying used.

What small, micro-level issues affect the price of a device?

Most Influential Determining Factors individual The values ​​for the device are:

• age
  Naturally, the simplest factor in determining the value of a phone is its age. Consumers prefer the latest upgraded version over the older version.
• Model
  In general, new product models are more valuable in B2B markets; This isn’t necessarily the case with iPhones. For example, Apple now offers a Pro model of each iPhone, which may be worth more than the base model of the subsequent generation.
• situation
  In a vacuum, an iPhone in good condition is worth more, and an iPhone in bad condition is worth more. An iPhone in excellent condition will command a much higher price than a similar lightly used device.
• Carrier lock status
  Unlocked phones tend to cost more than locked phones. Firstly, because it not only works on domestic networks, but also abroad, where there are many used, tertiary and quaternary devices.
• seasonality
  Holiday and seasonal discounts can lead to changes in consumers’ typical spending patterns, which can change the amount of inventory in the market and thus impact prices.

B-Stock’s Forecasting Toolkit

B-Stock took both these macro and micro factors into consideration when building its advanced machine learning algorithms. Our model helps each seller accurately predict the B2B and B2C market price of iPhone over the next 16 to 20 weeks at a very granular level. For example, it’s entirely possible to know what a red, B-tier, carrier-locked, 256GB, iPhone 13 will cost in our market two months from today.

This insight into secondary mobile market pricing is the value B-Stock provides to OEMs, retailers, trade-in services, insurers, refurbishers and third-party dealers. Based on years of market data Our resale expertise helps your organization make smart, data-driven decisions and optimize margins.

Data, AI, machine learning and predictive capabilities

B-Stock operates at scale and has collected the following B2B pricing data: every Auction every In fact, since 2017, we’ve sold 34 million units across 270,000 auctions, and used every bit of information available to build one of the largest proprietary B2B mobile data offerings in the world.

It is this data that provides deep insights through advanced statistical techniques, including outlier detection, interpolation, and machine learning.

Outlier detection

Outlier detection is the process of identifying unusual or anomalous data in a historical data set. For example, quick and seemingly random spikes can occur in any market but do not always reflect the item.

The blue arrow in the image above indicates a surge in secondary market prices for the C-grade iPhone 13 Pro Max. This is a clear outlier, probably caused by an extremely high bidding error or temporary market anomaly. Even if anomalies are corrected immediately, certain indicators may still be missing and need to be mitigated within the dataset. This is something B-Stock handles with ease.

interpolation

Simply put, interpolation is a statistical technique that uses existing data to fill in missing data. We use techniques such as spline interpolation, exponential moving average, K-nearest neighbors, etc. based on phone rank carrier lock status and many other factors.

Data before interpolation

Data after interpolation

machine learning

Predict B2B used mobile prices at a granular level (model, rating, carrier, lock status, etc.) using machine learning technologies such as Auto ARIMAA, KNN, XGBoost LightGBM, and DeepAR.

The above graph shows historical and predicted prices for iPhone 13 Pro Max unlocked grade C. The purple line is the historical B2B price per unit, the orange line is the weekly price per unit forecast for the next 16 weeks, and the green area represents the maximum change.

B-Stock Mobile Mind

This is B-Stock’s mobile pricing tool that gives sellers access to all of this. Historical and forecast pricing and sales data. The easy-to-use interface lets you view 12 different iPhone models, as well as filter results by tier, carrier, and lock status. Market price trends and forecasts.

With this knowledge, you can better plan when to sell your inventory and understand what margins you can expect and the trade-in value you will provide to your end users.

When it comes to accuracy, our dynamic modeling process ensures that the best performing algorithm outputs are reflected in MobileMind’s output each week. For example, at the time of this writing, the average prediction accuracy for different variants and conditions of the popular trade-in devices iPhone 12 and 13 was 96-98%.

What’s next for B-Stock predictive analytics?

To further its goal of enabling intelligent secondary market recommerce operations, B-Stock plans to expand its MobileMind tool to include more models and variables that can impact device pricing. This work has already begun, and full price predictability has been established for popular Samsung models in addition to the iPhone.

B-stock also plans to provide increasingly more information to its AI and machine learning models, with the goal of near 100% price accuracy.

Despite our reliance on B-Stocks’ predictive capabilities, there is still an element of human intelligence present in our service, and we check every forecast against our team of experts, taking meticulous care to determine whether the results truly reflect the markets in which our clients actually exist. Pay attention. Interaction, a phenomenon that AI does not tell us about.

What’s next for your business?

B-Stock is committed to providing data solutions to help every merchant make retail, trade-in, and insurance decisions. By building this intelligence directly into your mobile resale program. However, while information is valuable, no value is realized until the business makes a sale. That’s why B-Stock’s goal is to be a true end-to-end solution that serves as both an integrated advisory partner and a highly effective marketplace platform. .

Wondering how B-Stock can help your business make the most of its used mobile inventory? Contact us today.

You can watch the full webinar on this topic here.