Data Blog by Lizeo
Competitive pricing analysis: the product / pricing data pair
Associated with incomplete product information, price data will quickly show its limits when you try to perform a competitive pricing analysis across different ranges, websites, or countries. Therefore, the solution is to refer to a comprehensive and high-quality product database. What method should you use to ensure a successful competitive pricing analysis? What is matching? Furthermore, how do you build a comprehensive reference base? Here are the explanations.
Start a pricing analysis: a method in 3 steps.
To efficiently track the prices charged in the market, you must first define a scope for brands and data sources (or e-shops in the case of web data collection).
Next, you need to determine, in detail, which competitors’ 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 competitors’ products are unified between the different data sources, which is known as product matching. Indeed, 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
To be able to decipher the competitive data collected, you must use a clean product reference system. Specifically, to obtain the most representative vision of the market possible, you need to collect and unify the data from different sources, whether online or offline. However, there is a problem: the nomenclature, description, and characteristics of the same product generally vary from one source to another. Consequently, this can make the analysis inaccurate, or even impossible due to duplicate data, holes in the data, etc.
How data matching solves inconsistencies
To address this difficulty caused by 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). Moreover, the reference must also be identified in the certified product database to guarantee the relevance of the prices that are now attached to it.
Overall, the operation is simple: each piece of product information collected during the collection of prices must be sorted automatically into three categories.
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Unknown: The data can refer to a product that does not exist or to a new product to be created from a reliable source. In this case, we will search for official documents certifying the existence of the product to complete the reference system and retroactively match the product.
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Known: The pricing data must be associated with the corresponding product.
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False: The product must be blacklisted. For instance, this is the case when a piece of technical information concerning a product available in a source is trivially false.
By automating the sorting operation, it cleans the data by excluding incorrect information and duplicates, resulting in real time savings. As a 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? If so, building and using a reference database will simplify your matching operations.
To guarantee the quality and completeness of this product database, a continuous enhancement process supervised by business experts is required.
Specifically, each element of the reference must be traced and created from official sources only (such as sales catalogs, manufacturers’ websites, etc.). Furthermore, 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 in the market. Ultimately, the level of precision of this catalog will determine the precision and depth of the price analysis carried out afterwards. Now, it only remains to define and select the discriminating criteria in the market to make your comparative analysis as relevant as possible.
The key points of a reliable product reference
- Traceability: each product or attribute creation must come from an official source which will be archived.
- Representation: the level of qualification and clustering of competitors’ products must be defined by business experts and must reflect an unbiased view of the market.
- Completeness: the more complete the reference, the richer the analysis. Concequently, 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 into 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 database and on good matching practices?