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Competitive pricing analysis: the product / pricing data pair

Competitive pricing analysis: the product / pricing data pair

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Associated with incomplete product information, pricing data will quickly show its limits when you try to compare references from different ranges, websites or countries. The solution: refer to a comprehensive and high quality product database. What method to use? What is matching? How do you build a comprehensive reference base? Explanations.

Start a pricing analysis: a method in 3 steps.
  • To efficiently track the prices charged on your market, you must first define a scope for brands and data sources (or e-shops in the case of web scraping).
  • You then need to determine, in detail, which competitor’s products you want to track as a priority. At this stage, it is important to ensure that the available data sources are sufficiently homogeneous and granular to guarantee a precise comparison with your references.
  • Finally, make sure that the names and technical descriptions of competitor’s products are unified between your different data sources (product matching). It is at this last step that your product reference system, enhanced and validated by business experts, comes into play.

Data matching: the key step to enhance the value of data ​

In order to decipher the competitive data collected, you must use a clean product reference system. To obtain the most representative vision of the market possible, you need to collect and unify the Data from the different sources, whether online or offline. Problem: the nomenclature, description and characteristics of a same product generally vary from one source to another, to the point of making the analysis imprecise, even impossible (duplicate data, holes in the data, etc.).
To address this difficulty due to the diversity of collection points, a data matching phase must be integrated upstream of any analysis. In practice, this step will link the price collected from a reference found on a source (site A or price list A), with the price of this same reference on another source (site B or price list B). The reference must also be identified in the certified product database to guarantee the relevance of the prices that are now attached to it. 
The operation is simple: each piece of product information collected during the collection of prices must be sorted automatically into three categories.
  • Unknown: the data can refer to a product that does not exist or to a new product to be created from a reliable source. We will then search for official documents certifying the existence or not of the product to complete the reference system and retroactively match the product.
  • Known: the pricing data must be associated with the corresponding product.
  • False: the product must be blacklisted. This is the case, for example, when a piece of technical information concerning a product available in a source is trivially false.
Automating this sorting operation cleans the data by excluding the incorrect information and duplicates with, in the end, real time savings. Result: the “matched” data is stored in a clean database by associating a single line of information per product.

The product reference: the N°1 asset for good matching ​

Are your products complex? Do they have many technical features? Building and using a reference database will simplify your matching operations.
To guarantee the quality and completeness of this product database, continuous enhancement process supervised by business experts is required.
Each element of the reference must be traced and created from official sources only (sales catalogue, manufacturer’s websites, etc.). The detailed qualification of each product assisted by machine learning should be validated by experts in the field.
However, note that to carry out matching, efficient reconciliation or linking, you will need an overall view of the product offers available on your market. The level of precision of this catalogue will determine the precision and depth of the price analysis carried out afterwards. Now, it only remains to define and select the discriminating criteria on your market to make your comparative analysis as relevant as possible, thanks to your teams.

The key points of a reliable product reference
  • Traceability: each product or attribute creation must come from an official source which will be archived.
  • Representativity: the level of qualification and clustering of competitor’s products must be defined by business experts and must reflect an unbiased vision of the market.
  • Completeness: the more complete the reference, the richer the analysis. This involves a balance between the automatic qualification and manual enhancement.

In the Big Data era, a preparation phase for the latter must be integrated in your data processing process. Don’t cut corners. Before moving to the competitive pricing analysis, cleaning and matching operations are essential. Would you like to find out more on how to build a reference product data base and on good matching practices?

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