Here is an example of research data up close.
Table 1 shows five zip codes, A through E. Let’s say you live in zip code “C” and that these five are your targeted zip codes for finding more customers (such data is readily available to you). This demographic breakdown shows the ages of people living in the zip codes (zip code “E” has the highest number of 60-64 year olds, etc.).
TABLE 1
| Age | Zip Code A | Zip Code B | Zip Code C | Zip Code D | Zip Code E |
|---|---|---|---|---|---|
| 18 – 24 | 634 | 220 | 353 | 230 | 741 |
| 25 – 29 | 1367 | 496 | 850 | 541 | 1628 |
| 30 – 34 | 1748 | 680 | 997 | 784 | 1997 |
| 35 – 39 | 2111 | 886 | 1388 | 1039 | 2531 |
| 40 – 44 | 2835 | 1126 | 2082 | 1325 | 3300 |
| 45 – 49 | 3391 | 1501 | 2710 | 1739 | 4098 |
| 50 – 54 | 3780 | 1955 | 3181 | 2234 | 4505 |
| 55 – 59 | 3558 | 2424 | 3396 | 2731 | 4563 |
| 60 – 64 | 3885 | 3428 | 4129 | 3910 | 5011 |
| 65+ | 2796 | 4257 | 4637 | 4618 | 4430 |
| 65 – 69 | 2970 | 3029 | 3570 | 3396 | 3744 |
| 70 – 74 | 2888 | 2640 | 3346 | 3014 | 3586 |
| 75+ | 5623 | 4788 | 7798 | 5390 | 7929 |
Table 1. Five zip codes (A – E) showing the number of people in the age ranges.
Now, analyze your customer file and assume that most of your business comes from zip code “B.” Because you do some homework, you know your customers are in their early 40’s, have purchased a major bathroom or kitchen renovations from you in the area on average of $15,000 each, and have an annual income of over $100,000. How many customers did you have from that group? Five? Ten? You can see that immediately, you can “prospect” in zip code “B” for more of the same customers if they all are of the same income bracket. But, look at zip code “E.” There are almost three times as many from this early 40’s demographic there. Will it pay for you to prospect in that zip code? If only you knew their household annual income!
Table 2 shows you the same zip codes, but with the annual income overlay (again, this data is readily available to you). This is called “cross tabulation.” Researchers use it to further refine their knowledge to help them make better marketing decisions. In this case, it is known that our base is “B” and that “E” was looking better because it has more of the kind of target wanted. But with Table 2, it is clearly shown that “C” should be considered too. That zip code has more of the individuals that match the current customer profile.
TABLE 2
| Income | Zip Code A | Zip Code B | Zip Code C | Zip Code D | Zip Code E |
|---|---|---|---|---|---|
| $100,000 – $124,999 | 2644 | 2297 | 4681 | 3261 | 2883 |
| $125,000 – $149,999 | 848 | 1761 | 2692 | 2127 | 1202 |
| $150,000 – $174,999 | 410 | 1208 | 1791 | 1319 | 551 |
| $175,000 – $199,999 | 286 | 992 | 1318 | 1085 | 350 |
| $200,000 – $249,999 | 250 | 972 | 1604 | 1093 | 456 |
| $250,000 – $299,999 | 102 | 652 | 895 | 722 | 289 |
| $300,000 – $399,999 | 106 | 1085 | 1019 | 1146 | 317 |
| $400,000 – $499,999 | 50 | 569 | 500 | 612 | 214 |
| $500,000 Plus | 171 | 1232 | 1019 | 1338 | 831 |
| TOTAL | 4867 | 10768 | 15519 | 12703 | 7093 |
Table 2. Five zip codes (A – E) showing the number of people by income bracket.
Such research is just part of what you should do when you talk with people and when you prepare to market your services. The more you find out, the better decisions you will be able to make!