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EXECUTIVE SUMMARY

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					1533 E. SPRUCE

OLATHE, KANSAS 66061-3646

TELE 913.782.8544

FAX 913.782.0150

EXECUTIVE SUMMARY
OVERVIEW The following summary will help to highlight some of the key findings from the analysis Ruf Strategic Solutions performed on your data. The Smart Profile Analysis respects the rigors of statistics, assuring statistically valid numbers of observations as well as high degrees of predictability. The success of the Smart Profile Analysis is due to the expertise and experience needed to not only design an experiment but to evaluate it. Objective statistics are an important element of the analysis, as is subjective interpretation. Kansas Department of Tourism identified a need to answer the following questions to achieve its marketing goals: 1. Determine characteristic traits of Kansas Department of Tourism inquiries with an Inquiry per Household Profile. 2. Segment these inquiries by market penetration. Ruf completed analysis to meet these objectives by utilizing Smart Household clustering technology on 101,385 Kansas Department of Tourism inquiries. Our model appends a cluster code to each unique record on the customer database based on the respective demographic and psychographic traits. The records are grouped together and summarized by cluster code. We then compare the percentage of customers to the percentage of market-area households within each cluster code, and develop an index ((% of inquiries) / (% of households) * 100). Finally, each cluster is ranked from highest to lowest based on the index.

Inquiry per Household Profile
TOP PERFORMING CLUSTERS Kansas Department of Tourism penetration reports show strong segmentation opportunities. Below are the top performing household clusters: Cluster Inquiries % of Total % of Index (%I/% Inquiries Total.HH HH) A06 1,830 3.29% .81% 408.37 L10 2,219 3.99% 1.34% 297.91 L12 1,820 3.28% 1.20% 273.90 A07 1,871 3.37% 1.26% 267.62 E06 1,885 3.39% 1.75% 193.93 These top five clusters represent 17.32% of Kansas Department of Tourism inquiry file and only 6.36% of the market area. The lift for these top five clusters is 172.33% (272.33 – 100). Stated differently, the indices show that targeting these top five clusters would generate results 2.72times better than targeting the entire file. The top quintile of Ruf Household Clusters captures 44.79% of the total Kansas Department of Tourism inquiries. This quintile has an overall/cumulative index of 225.71, signifying over 2.25 times the likelihood to become a customer than the average market area household.

Executive Summary – Page 1

Analyzing the demographic and psychographic characteristics of the top ranked clusters, the segments show the following similarities: Strong Demographic Traits Married Householder Max Education Level – High School Occupation - Agricultural Weak Demographic Traits Female Householder White Collar

Strong Psychographic Traits Own workshop equipment Any civic/public activities in the last year

Weak Psychographic Traits Drinks any type of distilled spirits Bought CD’s, tapes in the last year

MEDIA ANALYSIS Our clustering allows us to segment the client’s data into finely tuned clusters. These clusters have similar traits in several aspects; the chart below highlights the media types most likely and least likely used by Kansas Department of Tourism inquiries: Strong Media Traits Reads Magazines in Family Circle/McCall’s Group Highly Loyal Reader of Reader’s Digest Read Women’s Seven Sisters Magazines Highly Loyal Reader of Prevention Watch TNN Read Seniors’ Interest Magazines Watch early evening news 3 or more times a week Highly Loyal Reader of Family Circle Listen to country (or western) radio Watch Country Music Television channel Weak Media Traits Listen to Spanish radio Read African-American Appeal Magazines Highly Loyal Reader of Ebony Watch BET Listen to urban contemporary radio Watch African-American Appeal Sitcoms Read women’s fashion, beauty & grooming publications Watch Dating/Matchmaking Shows Read Metropolitan/regional/state publications Read Women’s – Bridal Magazines

Lifestyle Analysis The chart below highlights the Strong and Weak lifestyle traits most likely displayed by Kansas Department of Tourism inquiries. Strong Lifestyle Traits Own a riding/tractor-type lawn mower Carry $50,000-$99,999 in home/tenant insurance Carry medical/hospital/health insurance from Medicare; Medigap/Medicare supplement; Medicaid Gardened (outdoor vegetable) in the last year Belong to American Association of Retired Persons (AARP) Obtained home/tenant policy through an agent Ordered from Lane Bryant in last 12 months Own a garden tiller Own a air compressor Weak Lifestyle Traits Visited South Pacific (Oceania) in the last 3 years Flex Mexicana for travel outside the continental US in last 3 years Rent apartment Attended Disneyland theme park most often in the last year Bought 3 or more formal/cocktail dresses last year Attended Universal Studios (CA) most often in the last year Drink malt liquor Bought men’s tennis clothing (not shoes/socks) in the last year Spent $500 or more on a watch in the last year

Executive Summary – Page 2

DEMOGRAPHIC ANALYSIS The following bar charts show the demographic makeup of Kansas Department of Tourism inquiries. Age
19 - 24 25 - 34 35 - 44 45 - 54 55 - 64 65 - 74 75+ 35% 30% 25% 20% 15% 10% 5% 0% 19 - 24 25 - 34 35 - 44 45 - 54 55 - 64 65 - 74 Age Range 75+ Customer 2% 8% 19% 24% 23% 16% 8% National 2% 15% 30% 26% 14% 7% 6%

% of Total

Customer Pct National Pct

Marital Status
Customer Married Single Unknown 80% 70% 60% 50% 40% 30% 20% 10% 0% Married Single Marital Status Unknown 75% 6% 19% National 51% 25% 24%

% of Total

Customer Pct National Pct

Executive Summary – Page 3

Homeownership
Own Rental/Unknown 100% 80% % of Total 60% 40% 20% 0% Own Rental/Unknown Homeownership Customer Pct National Pct Customer 87% 13% National 64% 36%

Dwelling Type
Apartment Multi-Family P.O. Box Single Family 100% 80%

Customer 8% 4% 3% 85%

National 16% 11% 4% 69%

% of Total

60% 40% 20% 0% Apartment Multi-Family P.O. Box Single Family

Customer Pct National Pct

Dwellling

Length of Residence
Customer
0 - 2 Years 3 - 5 Years 6 - 10 Years 11 - 15 Years 15 + Years 50% 40% 13% 17% 21% 23% 26%

National
39% 19% 18% 10% 14%

% of Total

30% 20% 10% 0% 0-2 Years 3-5 Years 6 - 10 Years 11 - 15 Years 15 + Years

Customer Pct National Pct

Length of Residence
Executive Summary – Page 4

Income Distribution
$ 1K - $14,999 $15K - $ 24,999 $25K - $34,000 $35K - $49,999 $ 50K - $74,999 $75K - $99,999 $100K - $124,999 $125K - $149,999 $150K+ 30% 25%

Customer 10% 11% 15% 22% 24% 9% 4% 2% 3%

National 17% 13% 13% 17% 19% 10% 5% 2% 4%

% of Totals

20% 15% 10% 5% 0%
-$ 14 $1 ,99 5K 9 -$ 24 $2 5K ,999 -$ 34 $3 5K ,000 -$ 49 $5 0K ,999 -$ 74 $7 5K ,999 -$ $1 99 00 ,9 K - $ 99 12 $1 4 ,9 25 K - $ 99 14 9 ,9 99 $1 50 K+

Customer Pct National Pct

$1 K

Income

CONCLUSION Ruf has been an innovator of market research and decision support tools for over two decades. Our intelligent marketing solutions are the most technologically sophisticated in the marketplace. The analysis performed by Ruf Strategic Solutions for Kansas Department of Tourism delivers extraordinary, actionable intelligence. The reports following this Executive Summary will provide additional detail on your specific data, which was only summarized in this section. These reports include the complete clustering results, from best to worst performing clusters, as well as detailed cluster descriptions for the best performing. In addition, we have provided extensive Smart Targets and Smart TargetsPlus information on all of the analyzed households.

Executive Summary – Page 5

1533 E. SPRUCE

OLATHE, KANSAS 66061-3646

TELE 913.782.8544

FAX 913.782.0150

KEY DEFINITIONS
CLUSTER CUSTOMERS DECILE HOMOGENEOUS HOUSEHOLD HOUSEHOLDS INDEX A group consisting of households that are similar across a wide range of demographic and purchase behavior variables. Customers of the client, as defined by an individual project. A grouping of ten percent (10%). Similar. Homogeneous customers will have similar characteristics (i.e., families, individuals living alone, or non-related individuals living together). Includes all household members – adults and children. Total households in the market area, defined as a comparison to the customers for each individual project. A comparison reflecting the relative degree of the penetration as compared to the overall penetration. Values above or below 100 identify propensities above or below the average, respectively. A way of life that reflects the attitudes and values of an individual or group. Lifestyle generally describes “what you do” as opposed to “what you are.” A specific activity, interest, or opinion. Customers with needs and/or wants to satisfy, money to spend, and the willingness to spend it. Client-defined target area of study. Market area can be project specific.

LIFESTYLE

MARKET MARKET AREA

MARKET SEGMENT Homogeneous subgroup of a heterogeneous aggregate market which is selected as a target market. PENETRATION Proportion of customers to households in the market area. PSYCHOGRAPHICS The study of consumers’ lifestyle traits. Psychographic data is used in conjunction with demographic and geographic data. QUINTILE RANK SEGMENTATION TARGET MARKET UNIVERSE A grouping of twenty percent (20%). Sequential ordering of data. Breaking a large group into smaller parts. A group of consumers to whom an organization specifically aims its marketing efforts. Client-defined area of total market potential. Universe can be project specific.

Key Definitions – Page 1

Kansas Department of Tourism CLIENT'S DATA SET - FREQUENCY DISTRIBUTION BY STATE
State AK AL AR AZ CA CO CT DC DE FL GA HI IA ID Count 143 1,197 1,752 1,308 4,055 2,080 531 70 166 2,717 1,620 130 3,068 308 Percent 0.14 % 1.18 % 1.73 % 1.29 % 4.00 % 2.05 % 0.52 % 0.07 % 0.16 % 2.68 % 1.60 % 0.13 % 3.03 % 0.30 % State IL IN KS KY LA MA MD ME MI MN MO MS MT NC Count 6,070 3,035 16,125 1,358 1,274 711 920 242 3,391 2,850 7,539 861 250 1,800 Percent 5.99 % 2.99 % 15.91 % 1.34 % 1.26 % 0.70 % 0.91 % 0.24 % 3.35 % 2.81 % 7.44 % 0.85 % 0.25 % 1.78 % State ND NE NH NJ NM NV NY OH OK OR PA PR RI SC 53 101,385 Count 345 2,195 253 1,224 461 418 2,393 3,299 2,948 758 2,320 82 128 806 Percent 0.34 % 2.17 % 0.25 % 1.21 % 0.46 % 0.41 % 2.36 % 3.25 % 2.91 % 0.75 % 2.29 % 0.08 % Invalid 0.13 % 0.80 % 2,806 State SD TN TX UT VA VI VT WA WI WV WY Count 492 1,714 5,879 482 1,359 3 131 1,270 3,347 489 212

V5.0

Percent 0.49 % 1.69 % 5.80 % 0.48 % 1.34 % 0.00 % 0.13 % 1.25 % 3.30 % 0.48 % 0.21 %

2.77 %

Total # of State Codes with Data: Total # of Inquirers:

The data reflected in this report is from the original client data file. Any code that varied from one of the standard state codes has been allocated to "Invalid". Cooperatively Developed by Ruf and Experian.

Please See Frequency Distribution by State Tab for Further Explanation. Frequency Distribution by State - Page 1


				
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posted:11/15/2009
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