Forcing Quota Groups
Any survey population can be broken down into segments, from a simple male/female segmentation to a more complicated very
profitable/lesser profitable/unprofitable customer segmentation. For larger
surveys with broad segments such as male/female, representation is rarely an issue and therefore you rarely need to force quota groups.
For example, if you conduct a 1,000 respondent survey and the male to female ratio is 60/40, then you would expect to have approximately 600 males and 400 females
completing the survey, which is plenty for additional analysis of those two segments. This tends to happen more often with general consumer surveys then with business-to-business or customer surveys, where total populations and sample sizes are sometimes smaller.
Taking a real world scenario, if a company has 1,000 customers, they might wish to complete a 300 respondent survey, resulting in a total margin of error of +/- 4.7 percent with a 95 percent confidence level. More often then not, the company will have customers broken out in some way, such as 20 percent that are very profitable, 50 percent that are
lesser profitable and 30 percent that are unprofitable.
If the company did a random survey of all customers, it would be reasonable to expect to complete
approximately 60 surveys with very profitable customers, 150 surveys with
the lesser profitable customers and 90 with unprofitable customers. If this company is like most, however, they are much more interested in their very profitable customers then their unprofitable customers. Yet by doing random surveys, they will
likely end up with only 60 completes from this key group to analyze.
The answer for this particular company is to force quota groups of perhaps 100 completes per customer segment. This would give the company a much better +/- 6.9 percent margin of error for the profitable group with a 95 percent confidence level, as opposed to +/- 10.6 percent for 60 completed surveys.
Be aware though, that there are additional costs associated with forcing quota groups. To complete
300 random surveys with a total sample population of 1,000, you would have to achieve a 30 percent response rate (300/1,000), which should be easy enough. If you wanted to establish quota groups as suggested, since there are only 200 (20% of 1,000) very profitable customers to potentially survey and you would be looking to complete 100 surveys, you would have to achieve a 50 percent response rate with that key group. That can be done with additional creativity and work during the data collection process, but doing so
will likely translate into additional time and cost.
Developing Lifelong Customers
How does a company go about developing lifelong
customers? One way is to make sure its employee processes are completely attuned to keeping the
customer satisfied at every step along the way. Doing that requires a thorough and detailed feedback program, such as the one Polaris conducts for Arvida, a real estate development company owned by the St. Joe Co. of Florida.
Polaris surveys each Arvida homebuyer throughout the first year of the home buying process. Starting with an initial buyer profile
survey given when the homebuyer initially shows interest, Advida then conducts surveys about sales, design, construction, closing and
warranty. This process provides Arvida management with a full understanding of the entire homebuying experience from the customers' perspective. The data has helped Arvida build a strong connection between its internal procedures, its customer satisfaction numbers and its bottom line. In an industry where customers referred by existing homeowners can be 10 times more likely to purchase a home, the impact of the relationship is clear.
"We felt that if we could improve our processes, our customer satisfaction levels would improve dramatically, and they have," according to Arvida's vice president of sales. "We knew that, if we got them high enough, there would be significant financial benefits. Our referral rates would go up, and word of mouth would have far greater impact on our sales, so fewer marketing dollars would need to be spent. And most importantly, if we could improve our processes, customers would enjoy living in our communities even more."
|
