The Buying Power Index Essay, Research Paper

The Buying Power IndexState: Pennsylvania City: Pittsburgh (1992)Total Population (thousands) Total EBI ($000) Total Retail Sales($000) Buying Power Index 366.4 5,141,995 2,963,456 0.1395 Part 2Buying Power Index (BPI):Sales & Marketing Management’s patented Buying Power Index, or BPI,providing marketers with a standardized measurement of the relative buying power of states, metros, counties, and cities. This weighted index that converts the Survey’s three basic elements-population (the demographic factor), Effective Buying Income(the economic factor)-into a measurement of a market’s “ability to buy,” expressing it as a percentage of the national total(100.0000%). The county’s (or other market’s) share of the U.S. total of each of these elements is multiplied by a fractional weight: .5 times the percent of U.S. Effective Buying Income, .3 times the percent of U.S. retail sales, and .2 times the percent of U.S. population. The sum of these weighted percents is the BPI.The BPI is one of the Survey’s most important measures, used to estimate potential for mass-marketed items sold at popular prices. For those who need to define their markets more specifically, however, it is possible to construct a customized version of the BPI, using any of the subclassifications of statistics in the Survey’s three basic data fields. By selecting a Demographic component (population labeled as A), an Economic component (income labeled as B), and a Distribution component (retail sales labeled as C), we can use the formula outlined below to convert data from individual markets into a custom BPI for your product or service. First of all, we need to look at these areas individually, and then select these three BPI components (A-B-C).A: Demographic We ‘ll need to isolate the population or household related factor that best describes our “ideal” consumer. B: Economic The next step involves selecting the income group(s) best suited to our product. Here, the Survey offers us five basic ranges of household incomes, and you can easily combine two or more groups to achieve a broader spectrum of potential.C: Distribution Isolating a particular store group that parallels your preferred channel of distribution is the final step in the preliminary selection process. Once these three factors have been selected, you can then compute your custom BPI by following this simple four-step process:Step 1 For each market (region, state, metro, county, etc.), you’ll first need to compare local activity to that for the U.S. as a whole, producing a ratio for each of three BPI factors (A-B-C). If your are selling video games, the 18-and under age segment maybe selected, and A component would be calculated as follows: Market’s Pop. 18-and-above ageU.S. Pop. 18-and-aboveNext, you might select households with incomes of $35,000 and above, so using this as B component, you compare the market with the appropriate U.S. total: Market’s Hshlds. W/EBIs$35,000+U.S. Hshlds. W/EBIs$35,000+And finally, we calculate the Distribution component C by constructing a ratio of market’s general merchandise store sales to U.S. market’s general merchandise store sales:Market’s general merchandise store salesU.S. general merchandise store sales

Step 2 we’ll assign weights to the three components(A-B-C), according to the three components’ perceived importance in the selling process. Since income is often cited as the most important indicator of potential purchasing power , your weighting of these factors might be as follow: Factor A (Demographic) -.2(20%); Factor B (Economic) -.5(50%); Factor C (Distribution) -.3(30%)Step 3 Mulitiplying each component ratio(X-Y-Z) by its appropriate weight and adding the resulting totals will then give you the BPI for a particular market: ( .2 x X%) + ( .5 x Y% ) +( .3 x Z %) = BPIStep 4 Repeat this same procedure for each targeted market, compiling a list of markets ranked according to their BPIs. If your particular product warrants the construction of a BPI with only two factors (or possibly four or five), remember that the percentages should still total 100%, regardless of the number of BPI components. Part 3 After we understand how to construct a BPI, and know that some factors would influence the BPI. Now I want to evaluate Pittsburgh as a market for some products selected as follow: 1. Products: Brand: YAYA Down-jacket .Low price ,for adult.2. Products: Brand: BinBin Ski-Wear. Monetary price , for adult3. Products: Brand: Cheetah Leather Jacket. Premium price, for adult According to the “Survey of Buying Power”, we know that the three components Demographic ( A ), Economic ( B ), and Distribution ( C ) might affect the BPI. Looking at these three products which are shown above, they are all clothing term, so the C would be the same as general Mdse. And because all of them are for adults, the A also might be selected as the same number which might be population of 18 and above age. Only because of the different price lengths, these B components would be different. For product 1, we would like to choose households with incomes of $10,000-$34,999; For product 2, we might choose $20,000-$49,999; and for product 3, we would select $50,000-&Over. Then, using the data of the “Survey of Buying Power”, we can calculate each product’s BPI by following the 4 steps shown above. As we know each BPI, we can compare with these three products’ potential markets. Of course, the most popular Product in Pittsburgh would be the one with the most biggest BPI. By comparing the different EBI groups, we can know the low income group is the most biggest one, so the BPI might be the biggest one. Thus, we would select product 1 to sell in Pittsburgh of Pennsylvania. In addition, also the winter in Pittsburgh is cold, so the weather factor would affect the BPI. On the other hand, from the information of the Survey issue, we can find that in Pittsburgh, 50 & Over age group was most biggest than the others’. And by comparing retail sales by store group, we can see that the Food store group was the most biggest one, in addition, the Eating & Drinking Places related to food group was also much bigger one. By looking at the EBI groups, we can find that the percentage of households with EBI of under $34,999 group is much bigger than the group with $35,000 & above. Therefore, we can know in this market, the are many old people with low incomes, of course the food market which is the nearest one relates to people’s lives might be most active market. . And the lower price products might be much popular than the others.