Gain a clear understanding of their best target market as defined by customer value and determine where and how to target media for increased growth.

Eliminate waste in advertising for a product that had traditionally been advertised only in mass media.

Using their existing customer database, we segmented and identified their “best” customer with a value model (RFM). We had their database enhanced with demographic and lifestyle characteristics, from which we developed profiles and models. Regression models were created to identify which variables within each target segment had the greatest predictive power.

Our client’s perceptions about the customer base were demystified and the true customer profiles became evident, via the analysis of their customer database. There were, in fact, no significant differences between “best” customers and other segments of their customer base as had been previously believed.

This new insight allowed our client to consolidate and streamline pricing scenarios substantially. It revealed that every customer had the opportunity to pay top dollar. The analysis further revealed that the previously accepted trade area of 3-5 miles was far too narrow. The true trade area was an estimated 17.5 miles, thus opening a wider area for prospecting. The model provided an actionable tool for micro-marketing.

By enhancing, segmenting, modeling and analyzing this clients’ customer database, we were able to validate and/or invalidate certain assumptions at the center of their marketing plan. Additionally, we were able to identify variables and differences in buyers that had significant impact on strategy and contributed to the goal of growing their business. Efficiencies were increased for direct-to-consumer targeted marketing through the use of modeled list selection criteria, increasing both response and customer conversion rates.

Gain a clear understanding of the profiles and any potential cross-over of fans/ticket buyers of these two teams in near geographic proximity. A Secondary objective was to determine ethnicity, affluence and specifically which regional geographies were most dense with potential fans. We also sought to answer the question, “how are the season ticket holders different from the fans who attend only one or two games per season?” Special attention was given to the media habits of existing fans to determine where and how to target broadcast media and direct mail for the greatest response and overall growth of ticket sales.

Enhance and analyze ticket buyer databases to provide actionable information for optimal media targeting, planning, buying and implications to the overall marketing strategy.

Three Key Target Groups were identified for both teams, for both individual and season ticket buyers. Profiles were created to bring these groups to life. Geographic areas of high propensity conversion were identified. Key Target Groups were targeted on a micro level while prioritized demographic variables were used to increase effectiveness in media planning and buying of mass media.

This analysis illustrated clearly who the ticket buyers are for both teams. Synergies were discovered in unexpected pockets of each database, opening up marketing cross-sell opportunities. A large overlap in the actual databases, as well as both teams‘ primary and secondary profile projections, provided the impetus to jointly market the two teams, thus maximizing the marketing budgets for each and increasing ROI. The tertiary profiles differed greatly, however, indicating the need for independent efforts ion certain fronts. Also interesting was the unique profile differences of these fans from category level syndicated data (attend, watch on television and listening to radio). These instances were well defined as a result of the database analysis.

Furthermore, a few surprise answers to the question of ethnicity yielded the insight to resolve certain internal debates regarding overall media directions and strategies. Certain regional geographies rich in potential, for either or both of the teams, became apparent.

Finally, the results were implemented in a direct mail campaign promoting season ticket packages for one of the teams and targeting prospective geographic “hot zones”. This campaign pulled 20% greater response then previously employed techniques and helped to beat all previous year’ season ticket sales prior to opening the general ticket buying season. This is merely one of the ways that this client has put to use the intelligence from within their customer database.

1. Increase retention and loyalty through relationship marketing.
2. Increase walk-in sales through targeted direct marketing.

Harness and use the member (customer) database for member loyalty and retention and new member recruitment.

First, all data had to be centralized from all center (retail) locations. Information contained in each individual member card, or record was harnessed in order to determine the ideal “target”. Transaction data were extracted (such as date joined, meeting attendance records, program type, dollars spent and additional products purchased) allowing us to determine “best” members based on value modeling (RFM).

The file was then enhanced with household level data (e.g. age, income, length of residence, presence of children etc.) and lifestyle data. Models were created to determine the most significant variables for identifying the profile of their “best” members. The resulting profiles and models provided list selection criteria for targeted marketing and as creative input for loyalty and retention programs. Additionally, the Value Model identified which members required retention messaging and which members were best suited for loyalty marketing programs.

Significant cost savings were achieved in direct mail through elimination of waste and better targeting. The cost savings permitted heavier marketing activity to their “best” members, thus solidifying market-share and share-of-member. The analysis demonstrated that the distance of a member’s home to the meeting place was a major factor in determining actual trade areas and increasing retention. New attention was paid to determining retail referral in the sales process, increasing ROI. Higher conversions of prospective “best” members were occurring and a buzz of excitement was seen at the retail center level. This boosted morale and created a ripple effect on sales. In the long term scheme, customer loyalty was boosted by highly targeted, personalized communication, a loyalty marketing database strategy recommended by our team.

Gain understanding of their customers demographically to improved direct mail targeting and ROI while increasing insight for creative development and future site selection.

No customer database had been maintained at the restaurant prior to this project and all direct mail efforts were targeted only by Zip Code, leaving lots of room for improvement via database marketing.

Create a database of current customers and develop profiles based on both demographics and geography.

A current customer database was created using hardcopy delivery receipts that included telephone numbers for reverse appending of addresses. We then had this database enhanced with demographic, buying behavior and lifestyle information. Profiles were created to give dimension to the picture (creative) of what the customer looked like. Demographic and geographic variables were prioritized for direct mail targeting.

Direct mail response rates increased by 7% and share-of-customer increased by 15%. This chain now has a customer loyalty program in place to reward frequent patrons and encourage repeat business, contributing to the increase in share-of-customer. They revisit their database frequently with value modeling for intra-database marketing and promotions.

1. Provide ”industry accepted“, quantifiable, information about subscribers for use in advertising sales materials.
2. Create subscriber profiles for new subscriber acquisitions programs.

This new magazine began their distribution in Sunday newspapers. Subscriptions to corresponding services were available using a toll-free 800 telephone number. The magazine planned to be distributed via subscription to homes/offices on a roll out basis.

Primarily to effectively quantify and describe the magazine’s actual and potential reader and subsequent subscriber base, to the advertising community. The goal is to provide the appropriate rational for the advertising within the publication. Secondarily, to use this description to determine the correct and optimal target audience for subscriber acquisition for the magazine’s rollout.

Since the magazine is distributed via newspaper (versus actual magazine subscriber), use and 800 number within the publication (with an incentive related to the publication subject matter) as a response vehicle to create a “responsive reader” database. The information contained in each responding individual fulfillment record, was harnessed in order to define the profile of a “responsive reader”. (Note “responsive readers” have greater value to advertisers because they take action on what they see). These data were then enhanced with demographic, lifestyle, buying behavior and financial information which linked to industry recognized syndicated research. The final analysis created both advertising sales materials and target definition for future subscriber acquisition programs.

Our study provided the necessary tools for the ad sales team to increase pages sold by providing media planners and print buyers with appropriate information for consideration and rational for the media plan. The resulting target definition was incorporated into targeting a rollout subscriber based version of the magazine. The program was very successful and the publication is now one of the leading consumer publications on newsstands today with a corresponding radio and cable television show.