Mere exposure effect
Familiarity breeds enthusiasm. The better your audience knows your brand, the greater its appeal. This is why both exposure frequency and retargeting strategies are so important. Targeting consumers who have already seen your content or visited your website delivers greatly improves conversion rates.
AI can help optimise retargeting efforts by creating further targeted and customised experiences. An individual consumer’s user journey can be analysed to identify what stage they are at and predict where and how it will be most successful to target them. What creative will work the best? How many times do they need to see it? AI makes customising experiences much more accessible.
The ‘Generation’ effect
Information is better remembered and valued if you’ve generated it yourself, rather than just having it told to you. Advertising that requires interaction from the consumer, perhaps requiring them to conclude something themselves, even solve a puzzle, invites engagement and increases the chances of the consumer holding positive perceptions of that product or brand. It’s similar to the ‘IKEA effect’, where consumers disproportionately value something they’ve ‘assembled’ or had a part in creating.
AI can be used to enhance the interactive experiences in advertising – whether that’s through personalised messaging based on analysis of individual consumer data or messaging that adjusts in real-time, dependent on consumer interaction. It can manifest in sophisticated, game-like features that respond to decisions the consumer makes, or simply through improved targeting.
‘Anchoring’ bias
Here, consumers put disproportionate emphasis on the first piece of information they receive about something. The earliest piece of information becomes the anchor point ‘control’ that all new information is compared against. A good example of its use in advertising is when dramatising price cuts; establishing a high initial price sets the anchor for the price of the item, so the cut price appears more appealing. Anchor bias can be applied to a broad range of decision-making and perception guidance.
AI can identify the ideal anchor point for different audiences, or even the best way to target specific consumers, to set up messaging for success. As well as price cuts, other examples include competitor comparisons: “competitors charge ££££ but we only charge ££” or, “while regular providers offer this [limited, less appealing solution], we offer this [superior solution that addresses your needs]”.
Being aware of these consistent patterns of deviation allows marketers to leverage them to help consumers make the right decisions. The same is true for creating more engaging advertising – strategy that utilises the understanding of these biases leads to creative that complements them. With the advancing integration of AI and machine learning, more and more possibilities will emerge.
