Database Marketing Consultant
Many of you contact yours truly (Kevin Hillstrom), your humble database marketing consultant, asking for a cheat-sheet that outlines the most popular projects clients ask me to work on. Here is a list of the four projects I am most commonly asked to complete for clients.
Most Popular = Multichannel Forensics Project
- Explain how customers interact with advertising, products, brands or channels.
- Illustrate the long-term impact of a catalog marketing program on online and retail sales.
- Describe how product classifications interact with each other in an e-commerce environment.
- Outline the ways that online advertising channels interact with each other to grow customer value.
- Develop a segmentation strategy or mathematical algorithm that forecasts customer segments unlikely to respond to print advertising.
- A typical project takes thirty days, and often includes a one day on-site to present results and discuss additional analytical requirements.
Second-Most Popular = Catalog Marketing Strategy Evaluation
- Evaluate contact strategy.
- Illustrate interaction between catalog marketing and sales in other channels.
- Develop a contact strategy that maximizes ROI, while growing the customer file.
- Suggest what might happen if a catalog strategy is discontinued.
Third-Most Popular = Hillstrom's Zip Code Forensics
- Incorporate your data into the overall algorithm.
- Provide descriptions of direct marketing responsiveness by zip code.
- Provide you with a zip code model personalized to your data.
Fourth-Most Popular = Database Marketing Audit
- A two-day on-site project.
- A full audit of catalog marketing and e-mail marketing strategies.
- Grades (A,B,C,D,F ... C = Average) are given for the following combinations:
- Customer Retention, Customer Acquisition, Data Mining/Analytics and E-Mail/Online Strategy.
- People, Techniques, Tools.
- An outline is created for improvement in the areas outlined above, coupled with the expected financial impact of recommended strategies.
Fifth-Most Popular = E-Mail Targeting Algorithm
- Use past customer purchase behavior, past clickstream behavior, and past user preference information.
- Develop a scoring algorithm to assign customers to multiple versions of an e-mail campaign.
- Anticipate a 20% to 25% increase in sales/e-mail for customers eligible for multiple versions of an e-mail campaign.
Labels: Consultant, Database Marketing
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