Head of Media & Digital, Japan
In trying to improve the return of investment (ROI) of marketing activities, it has become important to understand the effectiveness and efficiency of each of a brand’s media touch points. In areas like “product experience,” “point of purchase,” and “TV advertising” – all touch points that are ranked high for marketing effectiveness – a top brand with a wide customer base tends to maintain its advantages, because gatekeeping research allows top brands to continually verify and strengthen quality of their brand experience.
On the other hand, some emerging challenger brands manage to encroach on the stronghold of top brands, and succeed in gaining market share. The reason why these challenger brands are successful is not always obvious; challenger brands do not achieve efficient brand growth by adopting typical marketing activities, or by concerning themselves with typical advertising questions like, “How much budget should we shift from TV to digital?” Rather, they look at how they can create a differentiated brand experience outside their traditional advertising channels, and how they can make best use of each and every touch point in a manner appropriate for the brand. They cultivate their brands quietly, figuring out which touch points are their forte and then leveraging them as their brands’ breakthrough points. Furthermore, challenger brands spur consumer choice not only by seeking to influence “memories in the consumers’ mind,” but also by seeking to influence “memories in the machine” in order to achieve an accumulated brand effect; that is, they also look to understand and influence the data modeling that’s attached to individual consumers, such as their SNS and shopping data. A data-rich experience such as, “A person buys a product based on an algorithmic recommendation, and then reports that they are pleased with their purchase,” will certainly result in the accumulation of brand equity - not just in that consumer’s memories, but also by validating and strengthening a brand’s recorded data modeling.