Today's blog post is written by Aleksandr Peterson is a technology analyst at TechnologyAdvice

How to Target the Right Prospects at the Right TimeThe fragmentation and complexity of the digital world is forcing marketing to become more agile and reactive. In coming years, the strongest brands won’t be the ones who target the most prospects, but the ones who target the right prospects at the right time.

According to Salesforce’s 2015 State of Marketing report, this year’s top marketing strategies will include email marketing, social media advertising and listening, data targeting and segmentation, and location-based mobile tracking. These multi-channel trends are being driven by increasingly nuanced consumer preferences: people want to be known and understood by businesses. They want to be courted. For example, over forty percent of respondents to an Axicom survey said they would value a brand more if it remembered their buying and browsing behavior.

The indiscriminate “batch-and-blast” approach is quickly becoming an anachronism for successful companies, replaced by more precise tactics that respond to customer data in near real time.

What is This Magic You Speak Of?

Engaging the right prospects at the right time is a matter of contextualization. For example: If someone just posted a vitriolic rant about how terrible your services are, and you ask them to recommend your company to their friends, you’re delivering the right message in the wrong context. Multiply that customer by a dozen, or a hundred, and you’ve got a big problem.

On a larger scale, contextualized marketing relies on big data to track and respond to cues. This has become easy to talk about (mine your data, turn big data into “actionable intelligence”), but difficult to accomplish. A recent study revealed that over 60 percent of companies are planning to expand their big data marketing budgets. But delivering timely, context-specific content isn’t just about the “bigness” of data. It’s about turning big data into relevant data. What you know about your prospects should determine how, when, and where you engage them.

In the previously mentioned State of Marketing report, the three most important technologies for serving the customer journey were reported as CRM software, marketing analytics, and mobile applications. And in reality, these systems work best when they work together. As consumers’ digital lives become increasingly splintered, brands need to implement systems that provide central control and visibility across multiple channels. This need for unification, plus the reciprocity between marketing data and customer identity makes CRM software an obvious choice for many marketing teams, especially since CRM suites can incorporate social data and often include built-in marketing automation tools (or can integrate with dedicated programs).

Ways to Contextualize

Contextualization is a little more complicated than mail merging names into your subject lines, although that’s a nice touch. In addition to data analytics and contact management, contextualization requires the ability to segment prospects based on events and behavior and deliver dynamic content at the most opportune time. Some of these deliveries can be automated, depending on the medium (such as email, web content, or sms marketing); others may require manual execution (such as social media posts).

There are several different kinds of data you can use to do this:

  • Situational Data: This information is not directly related to the prospect, but may affect their receptiveness to certain kinds of engagement. Examples include weather, time of day, and geographic location.
  • Historical Data: More often than not, people associate this with purchase history, but it can also include browsing behavior on your site, service disputes and resolutions, previous companies they’ve bought from. Even abandoned shopping carts data can be used - almost 50 percent of online shoppers who abandon an item more than once will buy it if directly prompted.
  • Demographic Data: This information is not directly related to products or service, but can nonetheless inform purchase intent. Examples include age, education, job title, place of residence, and communication preferences (phone, email, chat, etc.).

Using these data points as a springboard, you can program a rule schema into your marketing automation software. These rules trigger marketing actions based on prospect behaviors or events, such as a “change in state” or passing of a threshold. Here are some examples of common trigger sequences:

  • Welcome emails/confirmed opt-in: when a prospect or customer joins your mailing list or subscribes to a newsletter.
  • Ratings and Reviews: Ask for feedback through surveys or questionnaires after product/service has been delivered.
  • Abandoned shopping carts: Remind potential customers to complete their procrastinated purchases, or even provide a special incentive to do so (like a discount).
  • E-receipts: Deliver a digital transaction record with suggestions for similar products.
  • Loyalty triggers: Automatically reward/reach out to customers who reach certain purchase thresholds, or who share select social content.
  • Browsing behavior: “You might also like . . .” or “Customers who viewed X were also interested in Y.”
  • Customer churn: Tell unsubscribers or service-cancellers you’re sorry to see them go, and give them a second-chance incentive to mend the relationship.
  • Date and Time-based Triggers: Remind customers when it’s time to renew their contract or service their product, or notify prospects of seasonal and limited-time offers.
  • Dynamic calls-to-action: Present unique offers to site visitors based on the pages they view or information they supply.

There are hundreds of different triggers you can use to contextualize your marketing efforts across every channel, whether it be email, social media, ecommerce, or mobile. These triggers help you divide your market into smaller pieces. Instead of a one-size-fits-all approach, where you market to prospects as a monolithic group, data-driven marketing acknowledges the diversity of subsets. It tailors timing to behavior and content to context, which is a fancy way of saying it delivers value. Soon, everyone will be doing it, and yes, that makes it cool.