How Data Boutique Works #2: Volume Discounts
The volume-related pricing system explained
About Data Boutique
Data Boutique is the data marketplace for web scraping. We make buying and selling data faster and safer for everyone.
How Data Boutique Works #2: Volume Discounts
Large volumes of data
Offering discounts for large-size orders is an ordinary component of commerce. Sellers give up a portion of the unit margins in exchange for a bigger unit count.
This is also true for web-scraped data. Since Data Boutique's mission is to make data trades smoother, an embedded volume-related discount system is in place.
Understanding buying needs
There are multiple reasons why data buyers want different volumes of data, depending on their data usage, development stage, and horizon. The same buyer can behave differently over time or in different projects.
Retail vs. Professional data buying
Retail data buying refers to frugal, one-off data purchases. The buyer picks one dataset from the shelf and buys it, maybe for a research project or to try to better study its content. Retail buyers typically buy low volumes of data and are difficult to forecast as they are not planned in advance. They don’t represent a profit for data sellers individually but do when aggregated, even if keeping a high-risk profile.
Professional data buying refers to systematically using datasets within company processes, with recurring data updates and a known set of websites to monitor. It is a planned, regular, repeated data order, often very large, consisting of hundreds or thousands of datasets. It represents a highly stable revenue stream for data sellers, but the scale of their operations requires keeping costs as low as possible and substantial volume discounting.
Professionals start as Retail: The journey to large, wholesale purchases starts with one buy. It’s faster, cleaner, and fairer than the free trials in the rest of the data industry. Free trials are good for proprietary, unique datasets but not so much for web-scraped content.
Build new vs. Consolidate existing
When purchasing data, the more certain we are of the scope, the more discounts we can leverage. We have less leverage for discounts in a newly designed BI system where the scope is not consolidated (we might want to test which websites are more interesting to monitor). But once this scope is certain, we can increase the discount by committing to longer contracts.
This dynamic approach increases flexibility: Data buyers can try new datasets to see which has the most value and then later consolidate the scope to reduce costs.
Example:
If I want to build a discount alert system, but I’m not yet sure of which websites are more interesting to watch, or in how many countries, or if doing it weekly or daily, I could do short-term tests on each website, before confirming I want them regularly.
The volume-related pricing system variables
At Data Boutique, we apply the following elements of volume discounting, and they all cumulate to the final paid price:
Order size
Order size discount is proportional to the pure economic size (EUR value) of the order: Generically speaking, the bigger an order is (more websites, countries, higher frequency), the more discounted it is.
Frequency
The higher the refresh frequency, the higher the discount. Discounting increases progressively if the refresh order is only once, once every month, every week, twice a week, or daily.
Commonality
Buying different extractions from the same website is discounted more than buying extractions from different websites. This is related to the difficulty of web scraping. Example: Ikea Italy is similar to Ikea France, so I get a discount when buying Italy AND France, rather than buying them separately.
Duration
The longer the time horizon, the higher the discount. Data Boutique currently supports a 12-month minimum duration or a 36-month minimum duration for buyers with a long perspective, which gives a substantial opportunity to reduce data costs.
Loyalty
The more active a buyer is, measured in Recency, Monetary, and Frequency terms (RMF), the more they add value to the network; part of this value is given back to the buyer through discounts. The more active a buyer is, the more advantages there are.
Transparency is speed
Buying and selling are tough elements of human interactions. Our job is to remove all obstacles that prevent this exchange from happening smoothly.
The faster the trade happens, the less money both parties waste.
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