Customer Acquisition Done Right

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Customer acquisition is the result of a truly remarkable process. It entails the perfect convergence of a relevant offer from a compelling brand, delivered to the right consumer at the right time in the right channel. This process is then repeated thousands, even millions, of times to fuel a company’s revenue growth and market share.

To focus acquisition marketing efforts accurately and profitably requires a data-driven methodology. Yet, a 2014 study from COLLOQUY notes that, “60% of US retailers said they lacked reliable data to execute effective customer acquisition initiatives.”

Even while empowered with vast customer data, the majority of marketers still lack the actionable insights necessary to effectively target prospects. Cooperative databases help bridge this gap.

Understanding Cooperative Databases

The power of a cooperative database (a repository with large amounts of customer data from different organizations) is derived from both its quantitative and qualitative dimensions. Quantitatively, its sheer mass of billions of transactions representing trillions in customer spend offers a wealth of information to analyze. Qualitatively, the diversity of data sources that fuel cooperative databases—multichannel retail, store retail, publishing, nonprofit, political, travel and leisure—offers a 360-degree view of virtually every adult consumer in the U.S.

Together, this quantitative and qualitative data fuels predictive analytics and audience modeling, which can identify the most responsive prospects for virtually any brand—consumers who resemble the brand’s best customers. These audiences can then be deployed across all channels, including direct mail, email and digital display advertising, with remarkable precision. This data-driven approach reduces marketing costs while increasing response rate at an attractive customer acquisition cost.

Loyalty and Lifetime Value (LTV)

One of the most significant advantages of data-driven customer acquisition is the ability to target prospects based on their likelihood to become loyal, lifetime value (LTV) customers. Using predictive analytics, it is actually possible to target individual consumers whose past transactional behavior suggests a higher likelihood of becoming LTV customers. This enables marketers to focus their efforts at the outset of acquisition campaigns with both immediate response and long-term sustainability in view.

Affordability of Customer Acquisition

It is clear that retaining an existing client is more cost-effective than winning a new one. In fact, research has shown that it is five to seven times less expensive to retain an existing customer than to attract a new one. But even the most successful brands with the most loyal customers must continue growing their customer base. This has to be accomplished based on an acceptable Cost Per Acquisition (CPA) and other Key Performance Indicators (KPIs). “Acceptable” is defined differently by every organization, but once KPIs are defined, companies like Wiland can provide prospect audiences, even at large volumes, to fuel customer growth in every channel.

Eliminating Waste through Optimization

Marketing pioneer John Wanamaker famously said:

“Half the money I spend on advertising is wasted; the trouble is I don’t know which half.”

That adage still rings true today. Every marketer is painfully aware of the large amount of wasted spend on non-responsive prospect audiences. Most of the customers within these low-performing file segments are undesirable customers with poor lifetime value. The cost of acquiring them and continuing to promote to them is so great and their performance is so poor that they will never be profitable.

Marketing intelligence companies can help address this challenge by examining the results of a client’s recent, similar campaigns and using this data to create a new predictive model that optimizes the list by scoring and segmenting all names in the file. The result is the identification of 1) high-performing segments that merit continued (maybe even increased) investment; and 2) inferior prospect segments that should be removed entirely from further promotion. The same methodology can be applied to digital marketing, where programmatic buying is governed by how online prospects score in data-driven customer acquisition models.

Digital Channel Opportunities

Marketers can affordably acquire new customers through targeted display advertising that combines direct marketing best practices with programmatic ad buying technology. The result is a new category of addressable digital marketing that can truly be described as digital direct advertising. By viewing digital display advertising through the lens of direct marketing principles, a rigorous test and measurement methodology can be employed that optimizes not just for clicks but rather for online and offline revenue. This is especially true of retargeting, as data-driven solution can recognize and differentiate between current customers, known prospects, and new site visitors, enabling marketers to target each group differently and bid accordingly.

Digital display also creates effective co-targeting opportunities that reach prospect audiences with simultaneous digital and offline marketing. These efforts can be synchronized to maximize response, conversion, and revenue. Co-targeting is an affordable yet highly targeted way to drive response from direct mail promotions by providing that all-important second touch at a significantly reduce cost when compared to an additional mailing.

Conclusion

By combining the power of data with predictive analytics, companies can optimize marketing spend, decrease marketing costs, and most importantly, connect with prospects that will buy from them for years to come. That is the definition of customer acquisition done right.

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