Acquisition Modeling: Not Your Grandfather’s Modeling ApproachMarch 30, 2018
“How do I best spend my advertising dollars to maximize the success of my business?” This was the question asked by retail and advertising pioneer John Wanamaker, and it’s a question that has only grown more complex in the omni-channel, disintermediated, digital world.
I began my career advertising in print media, radio and TV in the 80s, doing retail buying and merchandising before the advent of the world wide web.
I first began using “data” when I moved into manufacturing, supplying large retail brands with their private label apparel. Around that time, clients began to share data for decision making via electronic data interchange (EDI). We projected demand curves, did inventory forecasting, and scheduled production in our factories. It wasn’t until the mid-nineties that EDI began to be exchanged via the internet and I became an integrated partner to my clients and began to run my first vendor managed inventory (VMI) programs, relying on data to manage supply and demand according to a reliable demand curve forecast.
We were truly partnering with brands and transcending the typically dysfunctional buyer-seller relationship.
Later leveraging our supply side data management skills and our design, manufacturing, forecasting and inventory management skills, we launched our startup catalog company, Tiburon. We began prospecting for new customers by working with consultants and list brokers. We learned that for acquisition, catalog brands each had their own customer “list” and that they would exchange their lists with similar brands via list brokers. As brands objectives became to find more accurate and reliable solution than those obtained using the traditional acquisition method, early adopters started embracing data science.
In hindsight, this traditional acquisition method was outdated and ripe for disruption.
Enter the Model
Joining major retail brands, we began “prospecting at a profit,” which was terrific, but our best list by far came from database company Abacus, a behaviorally targeted transactional co-operative. With Abacus, members pooled their data and Abacus modeled a preselected universe built upon a client’s closest competitors’ active buyer universes. This synergy model was both my best list and my first experience with modeled acquisition data.
So, why do modeling?
Modeling enables a more efficient use of resources, replaces trial and error with predictive science, can increase list response, decrease churn, accelerate speed to break-even, enable data driven decision making, etc. Algorithms calculate the unique combination of demographic, lifestyle, income, and hundreds of other predictive data elements that can replace the trial and error methods of the past. Efficiency and performance gains increase ROI and optimize your advertising budget. Until recently, co-op databases and variable printing were the two most innovative disruptions in the industry.
In the late nineties, when all the PE firms were looking to invest in Internet companies, Tiburon grew to second tier equity stage. The importance of new Internet technology was becoming clear to the direct mail and catalog industry but e-commerce was still in its beginning stages. Like most direct merchants, Tiburon did not even have a website. An innovator at the time, Catalog City, a website on which consumers could request any of 17,000 catalogs or order merchandise from – Tiburon joined Catalog City and garnered several online orders, but it was not enough to convince investors that we had an internet play.
Co-ops were succeeding alongside the Internet and dominating direct mail acquisition. Intrigued, I went to work for Abacus from 1999. Two years later, we were acquired by DoubleClick with a promise of joining the online and offline data worlds, but it took 10-15 years to begin realizing the value of the promise of bridging the online/offline worlds.
While digital thrived during this period, it has only recently that we are succeeding in leveraging “de-anonymized” browse and cart data with behaviorally predictive offline data.
Future State Is Today
Direct mail acquisition methods haven’t changed much in the past 18 years. Co-ops still dominate share even while many marketers are less-and-less pleased with their lack of innovation and declining performance.
Clients are looking for incremental acquisition solutions that can be delivered in real time and with high satisfaction from a CX perspective.
Custom modeling has always been an expensive, time consuming process with a high cost, but predictive analytics is now available in the cloud, with end-to-end automation that includes cleansing, deduping, appending, modeling and reporting, all in real time for any budget. Without data curators, database administrators or data scientists, marketers can build profiles in minutes. Thanks to modern technology, customer profiles deliver valuable insight prior to investing in a prospect campaign and key elements are available for review by the marketing team in less than 5 minutes.
Knowing your customer this way is powerful in improving your relationships, maximizing lifetime value, and perfectly personalizing and timing messages by channel.
The time has come to once again disrupt the space. Test a “Blue Ocean” strategy, powered by modern technology, and find incremental new customers. Reach beyond your existing methods to find greater success.
Read the full white paper here.
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ABOUT THE AUTHOR
Thomas E. Smith, VP Enterprise Solutions at Anchor Computer
Tom leads strategic client development at Anchor, utilizing a variety of integrated, multi-channel, data-driven solutions to a range of industries and organizations, including; direct marketing, advertising, retail, finance, healthcare, telecom, insurance, transportation, education, public sector, non-profit, and associations.
Tom previously led the 100+ person Epsilon – Ryan Partnership business, growing the data-management group which included e-commerce, database marketing and analytics. Tom managed client relationships with Catalog/Retail MCM brands including, J.Jill, Plow & Hearth , Potpourri Group, Vermont Country Store, Yankee Candle and others. Tom’s experience also includes leading business development at Merkle – CognitveDATA specializing in data accuracy, data management and analytics.
ABOUT ANCHOR COMPUTER
Anchor Computer provides marketing professionals with innovative, intelligent and cost effective solutions designed to turn marketing data into actionable, profitable strategies. Celebrating 40+ years, as a leading provider of data processing and marketing services to thousands of marketing professionals across the US and Canada, Anchor offers a variety of integrated, multi-channel, data-driven solutions to a diverse range of industries and organizations, including; direct marketing, advertising, retail, financial, healthcare, insurance, automotive, education, and the public and non-profit sector. Learn more at www.anchorcomputer.com.