Vitamin H

What is Predictive Marketing Communications?

By Tim Weinheimer


How a 3D Approach Delivers a New ROI

You are a brand. You have an audience you invest dollars to reach. What is going on in your audience’s head today? How about in three or six months? If you’re drawing a blank right about now, you’re not alone. The good news is they have left you a clue in the data trail they have already blazed. How can you see it, and what will it tell you?

Predictive marketing communications may sound like science fiction, but it offers brands a very real way to understand how you can connect and engage with prospects based on their preferences, interests, and needs using a predictive marketing communication approach. Here are the basics to get you started.

Harnessing the Power of Predictive Marketing

What is predictive marketing?

Predictive marketing is designed to promote your brand through knowledge gleaned from detailed data about customer behaviors and patterns. The patterns, fed by a constant stream of user-provided information, are developed into models, and it’s through the models that the guesswork gets minimized in your marketing campaign planning. Every time a member of your target audience searches Google or posts on social media, they give you direct insight into their politics, interests, passions, and pain points.

With predictive marketing, we help our clients diverge from the linear marketing model of objective, target audience, call-to-action. Instead, we create a continuous engagement cycle that fosters organic connection with clients and prospects throughout each step on their purchasing and decision paths. The key is to create a cycle, a system, of ever-evolving insights.

A 3D Model: Making Predictive Marketing Work

The Hahn Agency has developed a flywheel model our clients use to take full advantage of available first-party data and build a successful predictive marketing program. The three-part system consists of Data, Design and Delivery occurring in a continuous-learning cycle. This approach focuses on clearly formulating audience challenges as business problems to solve based on a birds-eye view of customer behavior.

Phase 1: Digging into Direct Data
Gather data directly from sources such as:

  • Open data APIs, such as government and client databases
  • Marketing technology solutions
  • Client first-party customer data
  • Historical data
  • Fundamental intelligence from tracking of purchases and other events

While collecting and analyzing this information, seek the most telling insight about prospect or customer behavior related to your business or brand. Based on that insight, triangulate the data to determine how a client’s website, mobile app, product, service, or brand can address the audience’s specific problem or pain point.

This data-driven approach represents a shift from the “push” marketing model –– in which brands tell customers what they want based on media buying indexes, secondary research, and other off-the-shelf sources of information –– to a more effective “pull” model that reduces friction by designing solutions directly for customer needs.

To succeed in the data phase, three key factors are essential:

  • Assurance in the quality of input data
  • Human insight from an internal or external team member with exceptional skill in data interpretation (someone who can read the proverbial tea leaves)
  • A clear path forward with established key performance indicators informed by audience intelligence

These requirements hold true whether you’re gathering data for a paid media campaign, strategic influencer engagement, or any other form of creative outreach.

Phase 2: Design: Expectations versus Experience
We all expect an outstanding online experience. Consumers demand engaging, creative, interactive content and engaging touchpoints with the brands they like. Failure to deliver a CX (customer experience) or UX (user experience) to meet these expectations creates resistance. A clock metaphor is useful here. Draw a vertical line to represent 12:00 o’clock. This is the line of expectations. Now draw a line 45 degrees toward the 2:00 position. This is the line of experience. The gap between expectations and experience is filled with resistance and friction. That magnitude of that gap illustrates the degree to which you are risking, or actively losing, affinity with your audience.

During Phase 2, use design-centered thinking to build an experience that aligns with client expectations by focusing on the direct actions you want your audience to take based on the data you already analyzed. Influence your audience toward these actions using everything from earned media, social media, or paid media in the form of graphics, animations, or video.

Phase 3: Adaptive Delivery
The delivery phase is all about release and response. Effective campaigns address both short-term and long-term challenges, so plan to assess influence content that has been released and quickly adjust to audience feedback. Stop looking for silver bullets or home run hits. Adaptive delivery means continuously engaging with how your audience responds, then predicting what they might enjoy knowing about you next. Even limited-time marketing projects never truly sunset since the resulting data can deliver continuous improvements to optimize engagement and drive other business objectives.

The key to adaptation is measurement-as-a-service. Live dashboards that show audience changes swing the 3D cycle back around to the data arena to track real-time usage, performance and anticipated audience behavior. Smart dashboards and visualizations transform your data from raw numbers to actionable insights that inform strategic decisions and shape the next cycle of your marketing plan.

Good dashboards are challenging to build. Wiring into a reliable data set is a complex task but once completed, you can track everything from public awareness to sales lift, new service adoptions, and so much more. The point is to move beyond fundamental campaign metrics to track actual engagement return on investment (ROI) and return on ad service (ROAS). Another advanced measurement called the closer to net promoter score allows you to pinpoint users who are most likely to share your content and otherwise develop an affinity with the brand.

Pulling the Envelope with Predictive Marketing

Perhaps the most significant benefit of a predictive marketing approach is its ability to improve over time. As the process learns, just like machine learning promises, you develop a sixth sense of what your audience wants and needs. New questions will pop up that had not been considered before, and just as important, old assumptions can be swept away to provide a better view of the future, eliminating the guesswork of campaign planning and messaging.

Since we started in 1974, the Hahn Agency has grown from a small public relations shop to a 50-person agency specializing in high-performing campaigns that deliver the precision of predictive data science. Connect with us to foster a partnership with an agile team of storytellers with the design and data focus necessary to move your brand into a new age.