Reactive, Assumptive and Behavioral Modeling: Marketing’s Quest for Humanized Content

Are you marketing like a robot?

Marketing has come a long way. While automation was once considered the “bleeding edge” of marketing technologies, the industry has caught up and most SaaS companies provide at least some level of automation.

Right now, marketing can be divided into three approximate categories:

  • Oh, reactive marketing. Think about the Netflix PR crisis of 2011, when the CEO issued a flimsy, belated apology after completely changing the company’s core offering. We’ve come a long way since then, and with the advent of Twitter and social media pages that demand immediate reaction, “reactive” is now almost “real-time.”
  • Formerly known as “assumptive,” predictive analytics is at the root of most marketing cloud applications today. Predictive marketing leverages your company’s empirical successes to inform its marketing plans for the future.
  • The new kid on the block to marketing is behavioral marketing, though this is not the first use of its methodology. The science behind Google Analytics, behavioral modeling aims to collect data external of your website, before customers have even visited it for the first time.

So, let’s break down how companies can use reactive, predictive, and behavioral marketing to create a complete campaign.


Reactive marketing, though an essential part of every marketing team’s toolkit, isn’t your strongest option in creating brand visibility and authority. However, many companies operate strictly using this method – either because they lack the planning to pursue other, more sophisticated campaigns or because it offers immediate and, at times, lasting success. With reactive marketing, you create content, social strategies, and/or other marketing assets based on what your audience has told you they want.

Listening to your audience is, of course, a key component to creating brand evangelists, repeat customers, and growing your business through word of mouth. Reactive marketing is almost like customer service, however. It gives attention to existing customers without aggressively pursuing untapped markets. Though a good option for brand protection—not development—or community building, a campaign relying solely on reactive marketing is lazy at best, and detrimental at worst.


Marketers, realizing the shortcomings of reactive marketing, started using what they called a “predictive” model, although that’s a somewhat misleading name. First of all, predictive modeling does anticipate what will work for a company who is laying out a marketing plan; however, it informs marketers only on what strategies have worked in the past, using proven models to develop future plans.

This is problematic for many reasons. The most salient one for a start-up is that it necessitates a sample size. For many companies, marketing already feels like a risky investment. Having to wait weeks, months, quarters, or even years to get empirical results to study is costly and ineffective and could time your company right out of the market.

Additionally, predictive marketing pushes no boundaries. Your company is relying on existing successes to drive its future ones. Predictive marketing doesn’t help you jump shifts, as you can’t use legacy data to create assumptions that drive new-wave digital marketing. Proliferating predictive marketing into future iterations of your campaigns is simply validating assumptions within the data that you have already extracted.


So if assumptive is a top-down approach, and reactive is a volley—neither strategic nor proactive—what’s a marketer to do to find a way to reach their audience from the ground up?

The answer is behavioral marketing.

Wouldn’t it be great if your customers told you what they wanted before you even approached them with your offering? Behavioral marketing uses data about people’s actions to inform your campaign decisions. Google Analytics spearheaded this model, using behavior flow to help analysts determine what various website elements caused customers to engage with the page, move down the sales funnel, buy, leave, etc. Pretty genius, right?

The main problem with behavioral marketing when it comes to building a company’s marketing presence is that it requires a high volume of traffic to your website for definitive conclusions. Most of your potential customers have not yet reached your site, so the collection of data about behaviors must happen externally, as an approximation.

Ideally, we’d all have overwhelming site traffic.

There are many advantages to behavioral marketing:

  • Less work. The market tells you what to do, meaning you spend less time trying to guess your way to your next customer.
  • More opportunities. Identifying the buying personae of your base works with new markets or areas where your marketing is not yet optimized, relying on proven behaviors that have worked in other, similar fields.
  • Paradigm shifts. Assumptive marketing optimizes your existing successes, while behavioral marketing helps you identify new audiences and influencers, expanding your content and messaging across new channels.

Being only an assumptive or only a predictive modeler is like being an analog marketer in a digital world. While manually gathering data is resource-intensive and unrealistic for most companies with small marketing budgets, automated software can replace an employee when it comes to researching customer behaviors. As a result, you can build stronger marketing programs, save money, and get better results across paid, search, and social campaigns.

As automated marketing continues to progress toward human-like intellect, it’s important to keep a balance among your marketing strategies. Assumptive and predictive marketing have had their heyday, with plenty of successes for big companies with big budgets. As you go about strategizing your marketing campaigns, be sure you’re focused on forward-facing strategies like behavioral marketing to make leaner, meaner, money-making business plans.

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