Marketing With a Tailored Fit

How personalized does marketing really need to be?

Not only does marketing personalization substantially increase your chances of success, but consumers are demanding it, as well. They want consistent, relevant communication with brands that offer them content they’re likely to respond positively to, not content that annoys them or makes them less responsive in the future.

Here are three critical reasons why marketers should be personalizing their efforts:

1. Customers demand relevance

A recent Forrester mobile report emphatically states, “Customers demand personalized, relevant attention designed around their needs and wants rather than around your marketing channels.”

Consumers have made it clear that they want personalized communication, and they’re willing to give companies access to social and personal data as they download mobile apps, use social sign-in, share information across social media accounts, and so on. Of course, there’s extensive consumer concern regarding data privacy.

Most Web users say they’d trust companies more, and agree to release more data, if they had a clear explanation of how their information will be used to personalize and improve their experience. For example, Burton Snowboards customers are told that if they agree to share their location within Burton’s mobile app, they’ll receive updates on snow conditions only for the mountains they want to visit.

By focusing on trust, clarity, and utility, companies can play an active role in the acceptance of personalized marketing.

2. Personalization is dripping with ROI

When we talk money, we need data. According to Econsultancy:

  • 68% of marketers using personalized communication report a boost to their marketing ROI, and 74% report increased customer engagement
  • 80% of marketers think personalization from social graph data, explicit user data (e.g., interests), and behavior on the company’s Web properties each have a high impact on ROI and customer engagement

And let’s not forget opportunity cost. Every time a consumer sees an irrelevant email, ad, pop-up, app, or text message, the consumer becomes desensitized to the company’s communication. This leads to a consumer base that is habituated to not open the company’s messages and to feel less positive about the company.

As marketers continue to communicate with generic messages to consumers, return rates on opens, clicks, visits, purchases, downloads, and other desired actions suffer. People want to be understood. But many marketers are often more focused on cost than opportunity cost.

When considering the cost of increased marketing personalization, we should calculate the opportunity cost (real dollars that are lost) of reducing the effectiveness of upcoming marketing efforts, damaging relationships with consumers (or at least missing the chance to improve consumer relationships), and losing consumers as they unsubscribe from mailing lists, cancel subscriptions, or no longer return to a company’s site.

3. Machine learning predicts the future of marketing

Let’s also consider how marketing personalization is evolving. Data scientists are now using machine learning and predictive analytics in jaw-dropping ways, creating opportunities and insights that in the past marketers could only dream about.

Uplift modeling predicts the difference that additional targeting and segmenting will have on a marketing campaign. Combined with predictive analytics, it becomes even more powerful. Companies can now determine, prior to a marketing campaign, which consumers are:

  • Persuadables (people who may buy or renew)
  • Sure Things (people who would have bought without the marketing campaign)
  • Lost Causes (people who won’t buy in any circumstance)
  • Sleeping Dogs (people who will have a negative reaction like cancel, unsubscribe, complain)

By focusing solely on the Persuadables, companies save the time and expense of marketing to three types of consumers they should avoid in a campaign.

Machine learning has the power to personalize marketing in brilliant ways. For example, machines can analyze natural text from support tickets, emails to the company, and social media. They can analyze all standard data (demographic, explicit consumer information, purchase history, website behavior, social graph information), and look for relationships between all data for any one user, as well as relationships between users. Suddenly, when you want users to respond to a Twitter campaign, you know who’s likely to tweet, who likes the type of campaign (e.g., contest), and who likes the subject matter (e.g., product review), and you can then ensure that only those people are targeted for the campaign.

Overall, customers are becoming increasingly familiar with personalized marketing, and they’re starting to demand it. The ability to personalize information, segment customers, and understand user interests, behaviors, and likely actions, is improving so rapidly—and with formerly unimaginable possibilities—that cost efficiencies, opportunity costs, and customer value make the aggressive pursuit of marketing personalization a must for every marketer.


Joseph Pigato, Sparked

Pigato is managing director of customer engagement platform Sparked, where he heads marketing strategy and product development. Pigato, a marketing veteran with B2B and B2C experience, has worked with clients such as China Unicom, Google, HP, Intel, and Sony. He’s also helped to build and then lead technology startups in seven cities across four continents. Pigato, a Stanford University graduate who earned his Marketing MBA from The Wharton School, started his career as marketing director of education management company [email protected] Later in his career he served as a budget analyst intern at The Washington Post, cofounded, was president of A.S.K. Soutions, worked as a consultant for Symantec, and served as CEO of Edvance Online.

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