Influence the online shopper journey by applying psychographic insights

Influence the online shopper journey

When looking to understand and influence the online shopper journey, there is a tendency to focus on touchpoints, like social media, reviews, and online retailers. However, there’s an alternative view of segmentation that digital marketers could consider: psychographics.

Because consumer journeys are highly personal – dependent on traits, habits, and context – consumer behaviours are not homogenous. Psychographic segmentation (personality traits, beliefs, values, etc) adds another level of accuracy to predicting online decision behaviour.

Your digital marketing strategies and spend could be more impactful and generate greater online conversion and loyalty, when truly customised to your audience. Learn how 4 personality traits represent subconscious drivers influencing the online shopper journey and implications for digital marketing strategies.


Using psychographics can reveal a more holistic picture of the online shopper’s mindset and where brands can better influence it. Personality, values, interests, and lifestyle subconsciously determine how consumers browse, research, and ultimately make their final purchase decision.

Whether you want to reinforce consumer habits or disrupt them1, psychographics can help you target the right customers and tailor your online messaging more effectively. Examples include personalised ads, emails, product offers, and promotions. Remember to ensure that any psychographic data usage is done properly and ethically (i.e. implement user transparency, data protection/ privacy compliance, etc).


Personality is one psychographic that yields useful, actionable information for brands. Here are four examples and marketing implications:


Risk is a familiar and popular area of study in finance, for example, choosing between buying a high-risk, high-return stock, in comparison to a low-risk, low-return stock. Risk attitudes can also be a useful factor for consumer goods marketers.

Risk appetites indicate openness to trying new products and can reveal which online triggers could influence product trials. Consider those shoppers who keep searching for information to validate their choice or to get reassurance that they are making the right decision. These people are likely to be risk-averse, as they prefer outcomes with lower uncertainty. They need more reassurance and credible information.

These shoppers may be more likely to be triggered by a social media ad promoting a free trial. You would need to tailor the ‘free trial’ message to influence these shoppers accordingly.

In a recent Decision Journey Modelling (DJM) project for a leading household care product, we found that the need-for-certainty trait can indicate the length of the consumer decision journey. Risk-averse shoppers had a higher than average number of touchpoints before the final purchase decision. For marketers, a DJM project can uncover the best touchpoints to influence this segment. Once you uncover the segment, use an implicit, mobile-based research technique2 to determine which messages or visuals could subconsciously offer the most assurance to this segment.


The need for affect (NFA) refers to the variation in motivation for how individuals approach or avoid situations or activities that are emotion-inducing, such as watching a sad movie where characters die. Those individuals with high NFA would be more affected by the death of a public figure. A shopper with a high NFA would prefer more visuals and stimuli, as emotional appeal works more effectively on them than logic. Vice versa, a shopper with a low NFA would prefer more text-based information. If you want to convert a shopper with the NFA trait, you could optimise both the company-owned channels, such as the brand website, and the assets developed for third party-owned channels, such as digital ads.

For example:

Brand website: Personalise product content and site navigation to drive online engagement. For example, steer the high NFA consumers towards more visual information, such as product images or videos, to induce emotions. The low NFA group might be more interested in reading product reviews to educate themselves and better understand the product.

Digital advertising: Tailor messaging and visuals based on personality traits to drive online conversion. For example, consumers with high NFA would prefer more visual ads that make them feel emotional and sentimental. Relying on more emotional, rather than rational, stimuli is more likely to capture their attention and trigger action.


Need for uniqueness (NFU) is an individual’s pursuit of difference relative to others that is achieved through the acquisition, utilisation, and disposition of consumer goods for the purpose of developing and enhancing one’s personal and social identity.

A shopper with low NFU could be reached through a social influence nudge, which aims to trigger decision behaviour by providing encouragement by stating what other people do. For example, consider Netflix’s ‘Top 10 Movies Today’. Alternatively, personalities with high NFU are less susceptible to nudges. These consumers prefer scarce, customised, and less popular products, rather than being spurred on by other people’s choices. They can be targeted with ‘limited edition’ products.


Need for cognition (NFC) is a personality trait reflecting a person’s tendency to enjoy engaging in extensive cognitive activity. A person with low NFC will not enjoy or would prefer not to engage in making a choice or an active decision. Using default nudges is a way to reach this type of shopper – presenting a pre-selected option.

That option is likely to be chosen because switching to another option would require more effort. For example, food delivery app Grab Singapore uses the default nudge effectively by pre-selecting the ‘no cutlery’ option. You can also encourage low NFC shoppers to trial a new product by bundling it with an existing product.


With the proliferation of big data, you likely have many internal, public, and third-party data sources available. Combining these data sources with predictive analytics, can improve e-commerce decision-making. Equipped with a holistic 360-degree view of the online shopper, you will be able to make more accurate predictions. In addition to your own website or app, you can uncover psychographic data from ‘walled garden’ sites like Taobao, Alibaba, Rakuten, Lazada, and Shopee. Impossible? No.

Consider a research solution which realistically replicates e-commerce environments and apps to test how online shoppers make choices3, like SKIM DigiShop. With these insights, marketers can increase their agility – shifting content or offers to better influence shopper choice.


When speaking to consumers in a language they relate to brands can best facilitate their decision journey and increase online conversion and engagement.






By Chrislyn Tang LinkedIn, Analyst at SKIM Singapore