Emails That Target Customer Behavior Without Using Big Data

The ever increasing volumes of data used by companies like Target, Walmart and Amazon to carefully target their customers is cumbersome and difficult to manage. Analyzing patterns to find the right trigger that will motivate an individual to buy requires gifted statisticians that combine art and science into marketing magic. But what if you are not quite ready to use big data in your business? Can you still reap some of the benefits?

The ever increasing volumes of data used by companies like Target, Walmart and Amazon to carefully target their customers is cumbersome and difficult to manage. Analyzing patterns to find the right trigger that will motivate an individual to buy requires gifted statisticians that combine art and science into marketing magic. But what if you are not quite ready to use big data in your business? Can you still reap some of the benefits?

Fortunately for companies that don’t have a team of statisticians standing by, customer behavior and activity can be used to increase sales without the challenges that come with big data. It’s as simple as watching for specific activity or changes in customer behavior and being prepared with a customized response to encourage people to buy.

If this is your first venture into customer behavior marketing, start with the people who are the easiest to identify. Seasonal and discount shoppers are relatively easy to recognize because they have very specific buying patterns. Creating customized marketing for them increases their response and reduces costs. The dual benefits make this a logical place to begin.

Seasonal shoppers are the people who purchase items at specific times of the year. Traditional RFM (recency, frequency, monetary value) analytics flag them as top buyers shortly after a purchase and then systematically move them down the value chain. When they place the next order, they move back to the top and flow down again. Creating a marketing plan that sends materials when they are most likely to buy reduces marketing costs without affecting sales.

Discount shoppers only buy when there is a sale. This segment can be further divided into subsets based on how much discount is required to get the sale. If the marketing is properly tailored, this group of people serves as inventory liquidators. Minimizing the non-sale direct mail pieces they receive and heavily promoting sales increases revenue while reducing costs.

Both groups respond well to promotional emails. Capturing email addresses should be standard operating procedure. It is especially critical for seasonal and discount shoppers because they tend to be more impulsive than other segments. The emails that remind seasonal shoppers that it is that time again and tell discount buyers about the current sales are economical and effective.

The next step after targeting shopper segments is adding specific product category information based on the individual’s shopping history. When my daughter was younger, my shopping behavior with American Girl included two orders per year for regular priced items and sale purchases in between. The two full price orders were placed just before Christmas and her birthday. Sale purchases were impulse driven and triggered by emails announcing clearance items.

Bitty Baby was the category of choice in the early years of buying from American Girl. The shift to the character dolls didn’t happen until my daughter was nine. She received her first Bitty Baby at two. During nine years of systematic purchases, no one recognized that I only ordered certain things at specific times. How much would your company save if your marketing was tailored to customer purchasing patterns?

What about targeting people who haven’t purchased from a specific category?

The ability to predict what people want before they know it is one of the advantages of analyzing trends and activity in big data. Before moving to that level, start with the information that shoppers are providing. This trigger email from Amazon was sent two weeks after I searched for soda can tops on their site without purchasing.

The email avoids the creepy factor by saying, “are you looking for something in our Kitchen Utensils & Gadgets department? If so, you might be interested in these items.” Instead of, “because we noticed that you spent 14.34 minutes searching for soda can tops you may be interested in the ones below.”

The best practices included in this email are:

  • It doesn’t share how they know that the shopper is interested in a specific category or item.
  • The timing from the original search to email generation is long enough to allow time to purchase, but not so long the search is forgotten.
  • It makes accessing the items easy by providing multiple links.
  • The branding is obvious with links to my account, deals and departments.

Targeting customer behavior can become very complicated very quickly. Starting simple with specific segments and activity allows you to test and build on the lessons learned. The return on investment is quick and may surprise you.

Take Command of Marketing Data Governance—Because We Have To

The emergence of “big data” as an enterprise concern for many businesses and organizations is, as with most trends, both an opportunity and a concern. I recently was involved in reviewing new and recent Aberdeen Research on “Big Data”—how it is defined, how it is changing information volume (astounding in quantity), variety (both structured and unstructured, with tremendous pressure to integrate and make sense of it), and velocity (pushing the insight, analytics and business rules that flow from such data to lines of business that can best profit from it).

The emergence of “big data” as an enterprise concern for many businesses and organizations is, as with most trends, both an opportunity and a concern.

I recently was involved in reviewing new and recent Aberdeen Research on “Big Data”—how it is defined, how it is changing information volume (astounding in quantity), variety (both structured and unstructured, with tremendous pressure to integrate and make sense of it), and velocity (pushing the insight, analytics and business rules that flow from such data to lines of business that can best profit from it). An infographic that captures some of this research is now posted at Mason Zimbler, a Harte-Hanks Company, which created the visual presentation.

Alongside this current fascination and business trend, perhaps it’s not surprising that members of Congress, both Democrats and Republicans, also are posing questions at the marketing business as to how we collect, buy/sell, rent and exchange data about consumers online and offline, and if there is adequate notice and choice in the process. In the rush to capitalize on Big Data, we need to ensure that we’re collecting and using marketing data for marketing purposes only, and doing so in a manner that is respectful of fair information practices principles and ultimately serves the end-customer, be it consumer or business individual or enterprise. [See Rep. Ed Markey, D-MA: http://markey.house.gov/content/letters-major-data-brokers.]

All too often, privacy adherence is considered a legal matter, or an information technology matter—but I maintain that while these two business areas are important in respecting consumer privacy, it is marketers who have the most to gain (and lose) by smart (or insensitive) information practices. Data is our currency, and we must treat data (our customers as data subjects) as our primary asset to protect. Our method of marketing is in the balance. One or two major privacy mishaps can spoil it for everyone.

Of course, marketing data governance is far more than privacy compliance. Data quality, data integrity, data security, data integration, data validation and data flows within an enterprise all, too, are part of marketing data’s customer intelligence equation. It is in this spirit that the Direct Marketing Association recently introduced its newest certification program for professionals: “The Institute for Marketing Data Governance and Certification,” taught by marketing veteran Peg Kuman, who is vice chair at Relevate Group. The three-day course, which has launched on a two-year, multiple-city tour, is indispensable in understanding how multiple channels, multiple data sources and platforms, customer expectations and business objectives combine to command better understanding, tools and processes for data handling for smart integrated marketing. Forthcoming course dates and registrations are available here: http://www.dmaeducation.org/dm-essentials/marketing_data_governance.php

For three days last month in New York, approximately two dozen professionals from large and small enterprises, both commercial and nonprofit, attended the first seminar. I, too, attended. There were representatives from marketing, public relations, analytics, legal, IT and fundraising, representing brands, agencies and service providers. This group was engaged—providing examples, asking questions and reporting experiences as the curriculum moved along. (For those who don’t know Peg—a former client of mine—she is quite the facilitator.)

Alongside a workbook, I took home some great handouts, too:

  • A sample security policy; a sample information security vulnerability assessment;
  • A security due diligence questionnaire;
  • A sample vendor risk management program vendor questionnaire;
  • The latest copy of the DMA Guidelines for Ethical Business Practice (recently updated with new email append guidelines, by the way) and a bevy of news articles that captures the media’s and public policymakers’ current attention on consumer data in America.

The meat of the course tackled, among other topics:

  • Categorizing data and assigning priority and sensitivity (personally identifiable information, sensitive data and other categories);
  • Mapping data flows and interactions with customers; enhancing data with appended information, and ensuring its use for marketing only;
  • Having a data quality strategy as part of a data strategy;
  • Calculating return on data investment;
  • The emergence of digital, mobile and social data platforms, and how these present both structured and unstructured data collection and insight analysis challenges;
  • Assigning data “ownership”;
  • Calculating and assigning risk regarding security;
  • Monitoring security, investigating potential incidents of a breach, and handling a response to a breach were it to occur (using recent breach response examples of LinkedIn and Epsilon); as well as
  • Laws, ethics and best practices for all of these areas.

One of my concerns is the importation of European-style privacy protection in America, and current fascination with such protections by U.S. regulators and elected officials. That is worth another blog post in itself, but I can assure you that we need to educate politicians about the superiority of self and peer regulation where no consumer harm exists.

Thank you, DMA. Marketing data does not harm. It only creates consumer choice, commerce, jobs and (tax) revenue—and pays for the Internet and other media, too—and it is ridiculous to even entertain government-knows-better regulation of such information through a potential omnibus law in America, or other notions such as a government-mandated “privacy by design” requirement in marketing innovations. (On the other hand, I’m more than happy to see laws pass that protect Americans from potential government abuse of private sector marketing data—Big Brother should not be getting access to marketing data for non-marketing purposes, unless there is a demonstrable greater public good, where subpoenas are served and heard.) Privacy by design is smart business, but only when left to the innovators, not the policymakers.

Which brings me to close—and if you’re still reading this, I congratulate myself for not chasing you away. Big Data (which can incorporate far more than marketing data) goes hand-in-hand with marketing data governance. Whether a Big Data user or not, we all use marketing data everyday as our currency. Protect it. Respect it. Serve it. Govern it. So we can use it.