How Watch Companies can benefit from the Grey Market

Posted on Jul 15, 2019



 Grey Market Watches?  


    Even though accurate timekeeping is easily accessible through commercialization of cell phones, people still buy watches to express their status and personality. Nowadays, watches are considered a luxury item more than ever, which has an impact on watch manufacturers' pricing strategy.

    There are official and unofficial methods of buying a watch. One of the official methods is to buy it directly from brand stores or websites. And the other is to buy from authorized dealer stores or websites. These routes guarantee that the watch is authentic and brand-new. However, brands rarely offer discounts. This is mainly because a brand discounting its watch prices above a certain level is equivalent to devaluing itself. Authorized dealers, who directly interact with brands, do provide discounts, but usually up to 25% due to the brand's policy. 

    The unofficial method of buying a watch is through the grey market. Grey market dealers usually buy watches in large volume at steep discounts from authorized dealers, reducing the uncertainty of sales and the inventory cost for authorized dealers. Since grey market dealers do not directly interact with the brands, they do not have such discount rate constraint as in the brands and authorized dealers, and are able to adjust watch prices based on consumer demand. Thus, grey market discount rate can directly reflect how much consumers are willing to pay for a specific watch. By using the grey market discount rate as a proxy for the consumer demand, watch brands can get a reference in formulating their business strategies. 


Data Description


  Data was scraped from the largest watch grey market website, Jomashop. Three high-tier brands (Rolex, IWC, Omega), three mid-tier brands (Hamilton, Mido, Tissot), and four entry-level brands (Seiko, Casio, Swatch, Fossil) were selected, as representing each tier. Features such as the watch's "original price (regular price)," "grey market price,” "discount rate,” "style,” "series,” "movement,” "color,” and "material" were scraped from the website for analysis. 


Correlation of Original Price and Discount Rate (Each Tier) 


    Naturally, watch manufacturers set higher prices for watches which they consider to have higher value. While the grey market discount rate is a proxy for consumer demand, the original price is a proxy for each watch’s quality and manufacturer valuation.

    However, a mismatch between the producer valuation and consumer valuation towards a watch can exist. Since consumers generally have different perspectives towards different watch tiers, to better capture the correlations between the original price and the grey market discount rate, the regressions of original price (producer valuation) on discount rate (consumer valuation) were done separately by different tiers. 


    As for high-tier brands (Rolex, IWC, Omega), when the original price increased, there was a tendency of the discount rate decreasing. This implies that consumers have lower price-sensitivity to higher-quality watches and agree to the manufacturer's higher valuation toward those watches. Wealthy customers, who can afford to buy expensive watches, are ready to pay nearly full price once the watch has high manufacturer valuation and quality.  




    For mid-tier brands (Hamilton, Mido, Tissot), the correlation between original price and discount rate turned out to be positive. This shows that within the mid-tier range, despite increase in the watch quality, consumers are not willing to pay additional price for the increment in quality. However, the relatively 'flat' slope of the positive regression line shows that consumers are price-sensitive, but not too much. 




    For entry-level watches (Seiko, Casio, Swatch, Fossil), there is a strong positive “correlation” between original price and discount rate. This indicates that consumers are exceedingly price-sensitive to entry-level watches. Even for entry-level watches having higher manufacturer valuation and quality, consumers are not willing to pay nearly full price. Rather, consumers want higher discount rates due to higher prices of those watches.



Then What Affects the Discount Rate Most?


    Through these three regressions, it is now clear that the discount rate (consumer demand) of a watch is neither determined by its quality nor the manufacturer's valuation. We saw that across different tiers there were different correlations between original price and discount rate.

    If this is the case, is the 'brand (tier) ' itself the strongest predictor for the grey market discount rate? To figure out which watch characteristic has the strongest impact on the discount rate, the regression tree method was used since all predictors (watch characteristics) are qualitative, while the dependent variable (discount rate) is quantitative. 

    Watch characteristics, used as predictors, consist of "brand,” "style,” "band colors,” "dial color,” "band type,” "movement,” "case material,” "band material,” "water resistance,” and "crystal." The first five are related to the appearance of a watch. "Movement" is related to functionality, and the next three correspond to durability. Lastly, 'crystal' is related to both appearance and durability.

    For comparison, not only a regression tree of "discount rate" on 'watch characteristics’ but also that of "original price" on "watch characteristics" were built.


1. Watch Features on Original Price Regression Tree 

&  Feature Importance 




    When interpreting the result of a regression tree, if the objective is to figure out which predictors have stronger impact on the dependent variable, rather than just finding out which model gives the lowest Residual Sum of Squares (RSS), it is important to check the feature importance measure. 


    As for the original price of watch, set based on manufacturer valuation, "case material,” "brand,” and "band material" turn out to be the three strongest predictors. This indicates that watch manufacturers focus more on material, than appearance, of the watch in setting the price. 

    Although the result shows that watch manufacturers take brand image into account too, the contribution of case material to the original price appears to be much stronger.



2. Watch Features on Grey Market Discount Rate Regression Tree 

&  Feature Importance 



    On the contrary, the feature importance measure on the grey market discount rate shows that "brand,” "style,” and "band colors" are the three strongest predictors. This indicates that, unlike manufacturers, consumers put greater emphasis on the appearance of watch, than on durability/material.



So How Can Brands Specifically Utilize Grey Market Discount Rates?

    The grey market discount rates can provide helpful information to watch manufacturers for their future business strategies. Such information can be utilized in the competition with other brands, and for matching the consumer demand. 



Case 1: In Competition with Other Brands


    First of all, watch brands generally compete with those in the same tier. Since consumers’ price-sensitivity and demand vary greatly by tier, there is no reason to formulate business strategies against brands that do not belong to the same tier.

    The following is an example of how the mid-tier brand "Tissot" could utilize the grey market discount rate, in setting a business strategy against another mid-tier brand "Hamilton." 

    Based on the previous finding that 'style' is a strong predictor for grey market discount rates, we will compare the "median" discount rates for both brands by different styles.

("Median," instead of "mean," was selected as the measure, for the purpose of minimizing the influence of outliers.) 


Median Discount Rates of "Hamilton" and "Tissot" by Different Styles


    The above result shows that, except for military style watches, the differences in median discount rates between "Hamilton" and "Tissot" for other styles, are slight.

    However, it is clear that Tissot's military-style watches face a much higher median discount rate in the grey market than their Hamilton counterparts. 

    Based on this information, "Tissot" could either consider reducing their investment in military-style watches and focusing on other styles which appear to have more competitive potentials, or consider investing more in military-style watches until the gap in median discount rate is reduced. 



Case 2: Matching the Consumer Demand


    By comparing the order of original prices in amount and that of median discount rates in size across different "watch-serii" in their own brands, watch manufacturers can estimate consumer demand for each watch-series and design a business strategy that can better match the consumer demand.

    The following is an example of how the brand "Omega" could adjust its business strategy utilizing the information from the grey market.  



    As previously mentioned, watches with higher manufacturer valuation have higher original prices. In the first bar chart, the "aqua terra" series has the highest original price among Omega's watch-serii, meaning that Omega values its "aqua terra" series the most. In the second bar chart, the median discount rate for the "aqua terra" series in the grey market appears to be the lowest, indicating that consumers are less price-sensitive to that series as compared to other serii. Thus, manufacturer valuation and consumer valuation towards the "aqua terra" series agreed to each other. 

    As for the "constellation" series, however, manufacturer valuation and consumer valuation do not match each other. In the first bar chart, it appears that the manufacturer value the "constellation" series more than the serii "de ville" and "sea master." However, in the second bar chart, the median discount rate for the "constellation" series appears to be the highest. In this case, the manufacturer overvalued the "constellation" series as compared to consumer valuation. Thus, Omega could consider lowering the prices of newly-launched watches in that series, investing less there and focusing on other serii with more consumer demand, or investing more in the "constellation" series until manufacturer valuation and consumer valuation match.



Welcome to the Github for this Project

The skills the author demonstrated here can be learned through taking Data Science with Machine Learning bootcamp with NYC Data Science Academy.

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