We know–data models can be intimidating. As analytics and science remain central to Marketing’s success, models are now among the primary vehicles every marketer needs to know how to develop and leverage. If you’ve already dived into the deep end on models, congratulations. On the other hand, if you’re just dipping your toe into the water, have no fear, because while there may be a bit of a current, it is time to venture forth.

Mathematical models help us describe and explain a “system,” such as a market segment or ecosystem. Marketing models enable us to study the effects of different actions, so we can begin to make predictions about customer behavior, such as purchasing behavior. There are all kinds of mathematical models-statistical models, differential equations, and game theory.

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Define the Scope of Your Model

Regardless of the type of model, all models use data to transform an abstract structure into something we can more concretely manage, test, and manipulate. As the mounds of data pile up, it’s easy to lose sight of data application. Because data has become so prolific, you must first be clear about the scope of the model and the associated data sources before constructing any model.

Marketing data models to master
Define the scope of your Marketing model.

Marketing Models for Every Marketing Library

You’re ready to take the plunge–good for you! What models should be part of every marketer’s library? Whether a novice or a master, we believe that every marketer must be able to build and employ a number of primary models, with these four being your starting point:

  1. Customer Buying Model: How do your customers and prospects move through the various stages of their buying process? Illustrates the purchasing decision journey for various customers (segments or persona-based) to support pipeline engineering, content, touch point, and channel decisions. This model should account for all the behaviors from investigation to consideration and from purchase to advocacy.
  2. Customer or Market Segmentations: How do you know which markets to pursue or which customers are the most valuable? That is the purpose of segmentation models. They enable you to evaluate the attractiveness of segments, markets, or targets.
  3. Opportunity Scoring Model:  How do you know which opportunities to nurture and which should be forwarded to the Sales team?  This is the purpose of an opportunity scoring model. It enables Marketing and Sales to agree on when opportunities are sales-worthy and sales ready.
  4. Campaign Lift Model:  The point of any campaign is to create an incremental positive shift in buying behavior.  This shift, called lift, estimates the impact of a particular campaign. Campaign lift models help you ascertain whether the campaign you’re considering will produce the desired results.

While there are many other models that should be in your Marketing library, incorporating these four models serve as an excellent starting point. For those who have already developed models within your Marketing organization, we would love to know whether you have conquered these four or even whether you agree that these four should be at the top of the list. As always, we want to know what you think, so comment, tweet, or contact us with your response!

FAQ:

(written by Penn of Sintra.ai)
Q1: Why do marketers need to get comfortable with data models now?
A: Because analytics and science are central to Marketing success, and models have become primary vehicles for describing systems, testing actions, and predicting customer behavior. They are no longer optional.
Q2: What is a marketing model (in practical terms)?
A: A mathematical representation of a “system” (e.g., a segment or ecosystem) that uses data to make the abstract more concrete—so you can manage, test, manipulate variables, and predict outcomes such as purchasing behavior.
Q3: What kinds of mathematical models might marketers encounter?
A: Statistical models, differential equations, and game theory—among others. The type depends on the question you are trying to answer and the system you are modeling.
Q4: What is the most important step before building any model?
A: Define the scope of the model and the associated data sources. With data proliferation, it’s easy to lose sight of application; scope discipline prevents building a model that cannot be supported or used.
Q5: Why does every model start with data?
A: Models use data to transform an abstract structure into something measurable and actionable. Without the right data sources, even a well-designed model cannot be validated or operationalized.
Q6: What is a Customer Buying Model and what decisions does it support?
A: A model of how customers/prospects move through buying stages (often segment/persona-based), from investigation to advocacy. It supports pipeline engineering and content, touchpoint, and channel decisions.
Q7: What are segmentation models and why are they essential?
A: Customer/market segmentation models help determine which markets to pursue and which customers are most valuable by evaluating the attractiveness of segments, markets, or targets.
Q8: What two additional “must-have” models belong in every marketer’s library?
A: An Opportunity Scoring Model (aligns Marketing and Sales on when opportunities are sales-ready) and a Campaign Lift Model (estimates incremental behavior change attributable to a campaign to determine whether it will produce desired results).

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