In an era when the average consumer is bombarded with thousands of marketing messages per day, personalization has become a key way to break through the noise.

And consumers are asking for it: 75% say they prefer personalized offers (Aberdeen Group), and 61% say they're even willing to give up a degree of privacy to enable personalization (Compass Intelligence) on a continuous basis.

Marketers who are not yet paying attention to the consumer preference for personalization are carelessly leaving money on the table. Personalized emails generate up to six times higher revenue per email than non-personalized emails, according to Experian Marketing Services' 2013 Study. And that's just one channel of communication.

Personalized multichannel marketing campaigns consistently and overwhelmingly beat out static campaigns in generating high response rates, a MindFire study of 650 campaigns concluded.

In today's on-demand, highly digital world, personalization can be defined by several tactical components. However, the widely accepted most common and executional definition is an organization's ability to immediately engage with a consumer when that customer mentions the organization's brand or searches for key terms from a campaign.

So how can companies, regardless of size, effectively deliver personalized communications to a consumer base of thousands or even millions of customers and prospects? These five steps can help.

Step 1: Combine email and CRM data with social media

An easy method of personalization (and eventually a higher ROI on CRM) begins by matching a current CRM system or email data with data collected from all social media channels. Several tools on the market, and even some within platforms, allow plug-and-play options to sync such data, and any of those options are well worth the investment.

Of course, the more data a business has, the harder it becomes to interpret that data with the precision required for highly personalized communications. Thus, for any personalized messaging campaign to be successful, data gathering and interpretation must be the first step.

By combining traditional datasets with more authentic pieces of data, such as data discovered from social media profiles, email addresses can be transformed into records of real people with lives and jobs, families and friends, interests, and passions. Harnessing that magnitude of customer insight allows marketers to trigger communications when customers' interests most intersect with specific marketing campaigns.

Step 2: Learn customers' personal preferences via social behaviors

Social data provides marketers with unprecedented insight into their customers' lives, subsequently creating an abundance of opportunities for personalization that reach far beyond surveys, focus groups, and feedback forms.

What's great about social data for businesses is that it presents the ability to analyze, in real time, what a customer thinks, feels, and cares about, by simply "listening" to their online conversations—and then reacting with predetermined triggers.

The frustrations companies face with customer analytics initiatives aren't with the collection of data but, rather, about how that data is interpreted and ultimately used.

Much as how we learned to interpret email metrics and click worthiness over the past few decades, now is the time to achieve the similar outcomes with social networks. As a medium now foundational to the lives of the majority of consumers' worldwide, social media uniquely provides the tone of authentic insight through mentions, comments—negative and positive—brand and product engagement, and real-time conversations.

Use that authenticity! If a customer or prospect is clearly unhappy and has taken to social networking to vent frustrations, your business has an opportunity that it never would have had five years ago: to resolve a problem through a highly personalized and direct response. In addition, if prospects are on the hunt for a product in your industry, target them!

Social data takes us one step closer to delivering real-time communications without missing real-time opportunities.

Step 3: Create custom audiences for ad targeting

Once you're able to effectively collect social data, you're likely to discover trends, categories, and opportunities that may not have been available solely from email and CRM data. Use that information for new "categories" and to segment your list into custom audiences. By doing so, you'll be able to create ads highly specific to those unique audiences and ultimately address new prospects that fall within those audience segments.

For example, insight into social data may uncover a market opportunity for a niche segment such as "unhappy Apple users." For stores that sell competitive products, such as Best Buy or a local mom-and-pop electronics store, this type of knowledge is actually a form of lead generation. With proper keywords and brand name identification, this example category can easily translate into an automated ad with a promotion for a new computer.

Would you have identified an "unhappy Apple user" via your last email marketing click rate? Probably not.

Step 4: Deliver personalization with newfound customer knowledge

Ever since marketing emerged as a profession, its challenge has been to influence purchase by delivering the right message, through the right channel, at the right time.

With the latest breed of marketing automation tools, companies are beginning to learn how to routinely address marketing opportunities uncovered by data. Social automation, triggered emails, and even social advertising all allow marketers to have the ideal, perfectly tailored message ready to go as soon as customers mention a brand or keyword, open an email, or display interest of any kind.

Once a custom audience is created and you have a better understanding of the "categories" your audience falls into, you'll need to create the messages you want delivered to those customers and prospects (with the understanding that categories and messages may evolve over time).

Tailored messages can include anything from a response to unhappy customers to offer them a discount, to an encouraging promotion for particular products or product categories based on interest, and to a cross-sell or upsell on a particular good or service.

Once those messages are pre-created, you've almost reached real-time response capabilities. So what comes next?

Step 5: Ready, set, automate!

To summarize: if you've completed Steps 1-4, and your pre-created ads are ready and waiting, then Step 5 involves the (automated) send button. Using your newfound knowledge about your customers, prospects, and influential audiences on social media, your next task is to set up the processes or "rules," depending on your marketing automation solution.

Queue up the Facebook ads so that they're ready to be sent to audiences that have been categorized per their Facebook posts. Save the promotional emails and other custom messages so that once an opportunity is identified, all you need is a click—and out goes your message.

The task can seem daunting, but available solutions can plug into existing systems and deliver the valuable insights that previously took thousands of hours and more dollars to uncover.

Through data, analysis, and automation, the process of sending personalized marketing messages has become easier. No longer does your entire audience have to see the same message. You can gain insight from the data, and use it to strategize for all marketing efforts. The key is finding a way to integrate the real, authentic insight from social media data and combine it with what we already know about customers via our CRMs.

Finally, automation will allow you to deliver those personalized communications on time so that opportunities are never missed—and the likelihood of a sale or conversion dramatically increases. Now you are communicating directly to that person, formerly known as "Customer X."

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Put the 'Person' in Personalization in Five Steps

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image of Roz Lemieux

Roz Lemieux is CEO and co-founder of, which enables digital engagement teams to harness rich social behavior data to personalize audience messaging.

Twitter: @rozlem

LinkedIn: Roz Lemieux