An illiterate approach to choosing a time period or data volume
Posted: Wed Jan 29, 2025 6:09 am
If the volume of data or the time period under study is too large, the results may be biased. For example, when performing an ABC analysis of sales, there is no point in comparing thousands of product items.
You should analyze products within one category (all irons or all gift sets for men) or compare items with similar properties (all rubber boots, for example). Then you can make objective conclusions.
First example: the category "Shower gel" is fronk oil email list being researched in a chain of stores. The assortment includes 250 items belonging to nine different brands. The results of the analysis may be as follows.
Brand C offers the best sales. Brand G positions are the most expensive, but there are only four of them, this is an elite line, and this information is not reflected in the sales analysis results. It turns out that based on the collected information it is impossible to determine which of the 250 names presented should be promoted and which ones are better to refuse. It is important to take into account the composition of different shower gels, prices (including the size of the markup), turnover and profit for different positions, how close they are in characteristics, whether they are capable of provoking the "squirrel" effect or "product cannibalism".
It is necessary to identify the products that provide the greatest profit and those that represent a category of special positions. Simply put, consider not only the brand composition of the category, but all the properties of the products presented.
The second example: an erroneous approach when, when analyzing the turnover, you try to cover all the items of the selected category at once without taking into account the influence of logistics. An in-depth study of a category that includes more than three hundred items will yield nothing. Here it makes sense to consider broad time periods and turnover volumes with different suppliers, thus identifying those with whom cooperation should be developed or suspended.
Third example: you should choose the period for conducting sales analysis wisely. For example, when studying the volume of notebook sales (for XYZ analysis), it makes sense to cover not the entire year (then this product will fall into category Z as not in demand), but only August and September, when the demand for this product is the greatest and most stable.
Insufficient attention to the rapidity of the life cycle
Remember, no matter how thoroughly you conduct a sales analysis, its data is relevant today, but may mean nothing in a month. You have correctly placed products into groups, but fashion, or the season, or the market trend has changed, and now positions from category A are steadily creeping into C. Life and external conditions do not stand still, as they say, everything flows and everything changes. Be sure to remember this when conducting research.
Mistakes, both significant and not so, happen everywhere, in any calculations and studies. Take the examples given and try to avoid the mistakes described in them in relation to your business.
You should analyze products within one category (all irons or all gift sets for men) or compare items with similar properties (all rubber boots, for example). Then you can make objective conclusions.
First example: the category "Shower gel" is fronk oil email list being researched in a chain of stores. The assortment includes 250 items belonging to nine different brands. The results of the analysis may be as follows.
Brand C offers the best sales. Brand G positions are the most expensive, but there are only four of them, this is an elite line, and this information is not reflected in the sales analysis results. It turns out that based on the collected information it is impossible to determine which of the 250 names presented should be promoted and which ones are better to refuse. It is important to take into account the composition of different shower gels, prices (including the size of the markup), turnover and profit for different positions, how close they are in characteristics, whether they are capable of provoking the "squirrel" effect or "product cannibalism".
It is necessary to identify the products that provide the greatest profit and those that represent a category of special positions. Simply put, consider not only the brand composition of the category, but all the properties of the products presented.
The second example: an erroneous approach when, when analyzing the turnover, you try to cover all the items of the selected category at once without taking into account the influence of logistics. An in-depth study of a category that includes more than three hundred items will yield nothing. Here it makes sense to consider broad time periods and turnover volumes with different suppliers, thus identifying those with whom cooperation should be developed or suspended.
Third example: you should choose the period for conducting sales analysis wisely. For example, when studying the volume of notebook sales (for XYZ analysis), it makes sense to cover not the entire year (then this product will fall into category Z as not in demand), but only August and September, when the demand for this product is the greatest and most stable.
Insufficient attention to the rapidity of the life cycle
Remember, no matter how thoroughly you conduct a sales analysis, its data is relevant today, but may mean nothing in a month. You have correctly placed products into groups, but fashion, or the season, or the market trend has changed, and now positions from category A are steadily creeping into C. Life and external conditions do not stand still, as they say, everything flows and everything changes. Be sure to remember this when conducting research.
Mistakes, both significant and not so, happen everywhere, in any calculations and studies. Take the examples given and try to avoid the mistakes described in them in relation to your business.