Knowing who your customers are is great, but knowing how they behave is even better. Their personas and demographics tell you what they might be interested in, but their behavior tells you what they definitely are interested in.

Behavioral data can be highly predictive of future decision-making patterns and road-to-purchase activity. A prospect’s browsing and search activity relates directly to his intent; his social sharing activity can indicate future purchase possibilities; and emails opened, links clicked, and content consumed indicate good old interest.

The information gleaned by paying attention to a consumer’s digital behavior is her online body language. By tracking and interpreting online body language, you can determine where she is in her buying journey and what problems she might be trying to solve. You can even begin to figure out what interests her, what annoys her, and what persuades her.

This gives you solid and very powerful information to go on. As McKinsey wrote in The Coming Era of On-Demand Marketing, “Online behavioral models built with Web traffic, search behavior, lifestyle data, and demographics are particularly effective at identifying prospects not found with traditional demographic prospecting models.”

Examples of Behavioral Targeting Some basic examples of behavioral targeting:

Email: Which emails did a consumer open and/or click on?

Which emails did she NOT open and/or click on?

Which type of offer does she respond to most often?

How long ago was her last interaction with an email — three days, three weeks or three months?

Who responds frequently, who rarely interacts?

Did a consumer mention your company on Twitter?

Did she navigate to your site from Facebook?

Did she share one of your messages?

Website: Did a consumer visit your website? If so, how recently?

What content did she download or view?

What keywords were used to navigate to your site?

How many pages did she view while there?

Behavioral Targeting Drives Opens, Clicks, and Engagement

When David Daniels, founder of the Relevancy Group, was an analyst at Jupiter Research (acquired by Forrester Research in 2008), he reported that targeting emails based on Web click-stream data increased open rates by more than 50%, and increased conversion rates by more than 350%.

Marketo open rates clickthrough rates

At Marketo, we found that our lead nurturing campaigns that use behavioral targeting have 57% higher open rates, 59% better click-to-open rates, and a whopping 147% higher overall click rate. Research from Gareth Herschel at Gartner found that event-triggered campaigns (e.g. those based on behaviors) performed five times better than traditional batch campaigns. On top of that, Forrester Research recently found that only 17% of companies assessed themselves as mature practitioners of behavioral marketing — but those mature practitioners grew revenue faster than they planned (53% versus 41%).

And just in case you needed more convincing, MarketingSherpa research also shows that triggered emails and segmenting campaigns based on behaviors are the top tactics to improve email engagement.

Marketing Sherpa Email Marketing Benchmark SurveyDumb Lists and Complex QueriesSo it’s clear that behavioral targeting is valuable. But while this engaging level of targeting is not a new concept, it’s still not commonly put into practice. Why? Because traditional email service providers (ESPs) have not made it easy.

In a perfect world, every interaction that individual consumers have with your brand would be collected and stored in behavioral databases, so you could target and customize every single message easily. Unfortunately, many marketers don’t yet live in that world. According to Forrester, only 45% of marketers are currently capturing and consolidating customer behavioral data from multiple channels into a single database. Data come from many sources, and customer-facing systems don’t always talk to each other. Social data, for example, are sometimes connected; sometimes not. Website data are almost never connected to transactional data.

Traditional email providers don’t help much with data aggregation. Sure, they can track email behaviors and feed their customers reports on open and click-through rates. But they lack connection to other behavioral data and are unable to inform communication with more personal behavioral cues. These ESPs work primarily from imported lists and spreadsheets. We call these “dumb lists,” for obvious reasons. Anything sophisticated requires pulling custom lists with complex queries written by technical experts — they are made up of API calls, SAS code, and SQL queries.

When marketers are forced to deal with complicated technical jargon and customized code, they are at the mercy of IT. This means acting on behavioral data is challenging for the average marketer using a traditional ESP. Less agility means it takes longer to react to opportunity. Ultimately, it means that sophisticated behavioral targeting is often not done because it’s too difficult.

A Smart Database with Smart Lists

That’s why modern, engaging email marketing needs to be powered with a behavior-smart database at the core. This database serves as the system of record for all prospect and customer interactions within marketing, sales, and transactional systems. The result: a single place from which marketers can build highly targeted campaigns tied to trackable information about each individual contact.With a smart database, marketers can easily target their subscribers using demographic AND behavioral filters and triggers, such as:

Demographic: name, location, age, registration source, household, preferences, score, custom fields, etc.

Email history: sent, opened, clicked, bounced, unsubscribed, etc.

Social: shared content, referral, poll answer, etc.

Website: visit, clicked link, completed form, referral source, search query, etc.

Campaign history: campaign membership, campaign response, campaign success, etc.

Custom: purchase history, deposit, withdrawal, cart abandonment, data usage, etc.

“Smart lists” can combine filters to create specific target segments: subscribers aged 18-25 who shared content via social, or customers with balances above a certain amount who visited the loans page twice in the last month. Plus, you can track campaign and response history for a solid record of how segments have performed.This type of email marketing system makes marketing self-reliant, so that marketers can easily create and manage sophisticated behavioral-targeted campaigns on their own, without having to enlist the help of technical support. That means they spend less time modifying spreadsheets and waiting for IT, and more time building engaging, relevant campaigns.