Cognitive Science + Data Science: Next-Gen Data Driven Marketing

Next-Gen Data Driven Marketing What are the psychological motivators driving customer purchasing decisions? The era of ubiquitous digitalization, advanced analytics, and big data is here. Yet marketers frequently grapple with obtaining information that answers critical questions surrounding the purchasing behaviors Source

Cognitive Science + Data Science: Next-Gen Data Driven Marketing
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What are the psychological motivators driving customer purchasing decisions?

The era of ubiquitous digitalization, advanced analytics, and big data is here. Yet marketers frequently grapple with obtaining information that answers critical questions surrounding the purchasing behaviors of consumers.

Amidst a persistent, highly competitive advertising landscape and pervasive disruption that has profoundly impacted consumer behaviors, beliefs, and habits, marketers must deliver the right message to customers based on what’s really motivating their behaviors and decisions. When cognitive science and data science merge, a crucial gap is filled that enables marketers to not only customize customer interactions and optimize campaigns, but accurately anticipate future needs.

Ronald van Loon is an AnalyticsIQ partner, and as a global thought leader in predictive analytics and big data, extends his unique expertise into a deeper exploration of this provocative topic.

Though cognitive psychology and predictive marketing analytics are distinctive domains, there’s a shared dependence on statistics, surveys, and scientists. A blended approach can provide unique data expertise from each discipline to generate cognitive-based data that leverages the inherent motivators and values of customers to forecast their future decisions.

DIFFERENTIATING MARKETING EXPERIENCES AMIDST CONSUMER DIGITAL FATIGUE

Organizations have integrated statistical models in their marketing initiatives, but these are prone to failures across categories like Poor Model Design, Bad Data, and Incorrect Modeling that occur throughout any stage of a project.

This is extremely problematic given the economic and social turmoil emerging from the pandemic and its relative influence on consumer purchasing behaviors. Marketers have been wrestling with the opportunities and challenges arising from the past year, and how to best deliver innovative, transformative experiences in an increasingly virtual-first world.

This challenge is even more complex given that recent research indicates 30% of consumers are already fatigued by how much of their lives have transitioned online. The ability to sustain customer engagement in a modern marketing environment therefore hinges on the ability to provide deeply relevant, engaging content and digital experiences that speaks to who the customer is on a multidimensional level.

Laying the groundwork into a new frontier of sophisticated analytics and psychology, AnalyticsIQ has created a curated data set that enables marketers to wield data-driven insights into the psychological decision drivers of their audiences and develop purposeful predictive models.

THE ROLE OF PSYCHOLOGY IN ACHIEVING VALID RESULTS

Cognitive psychology targets the relationship between information processing and corresponding behaviors. When this is infused with predictive analytics, accuracy can be validated via data comparisons.

Marketers often use surveys to drive their marketing campaigns, but the results may not be a trustworthy reflection of a customer’s true motivations and characteristics. Individual respondents interpret and reply to answers differently based on perceived social values, or a desire to avoid personal questions, among other reasons.

But when this data is captured and analyzed using psychological techniques that address these challenges, it can lead to survey outcomes that support robust predictive models. For example, rather than inquiring if a respondent possesses a specific characteristic, the survey could ask if they have formerly engaged in precise behaviors that indicate the psychological element being investigated. A conclusive group of responses provides data analysts with more dependable, predictive datasets to model for marketing analytics.

This cognitive-based data helps marketers understand who an individual customer truly is, what types of daily actions they take, and why they make decisions on an unprecedented level of depth:

  • Specific purchase predictors by key product attributes.
  • Psychological motivators like green consumerism, introversion, or impulsiveness.
  • Economic considerations that impact the household.
  • Discretionary spending for different product types.

This infusion of cognitive psychology and data science helps organizations deliver surprising, delightful marketing experiences and continuously shape product innovation according to who their target customers are on a psychological level.