As consumers engage increasingly with their brands on a personal level, brands have unparalleled access to consumer buying behaviours. As a result, brand offers have had to become hyper-personalised. However, hyper-personalisation runs the risk of eroding a company’s core brand identity
Today, consumers are sinking under the weight of advertising messages. The average person is exposed to approximately 5 000 pieces of advertising, in different formats, every single day. This number is growing as we speak. We also have an ever-growing number of touchpoints, which increases the complexity and noise. As a result, it has become critical for brands to generate clutter-cutting advertising, which is unforgettable and drives the correct messages.
The challenges of advertising
However, creating distinctive as well as memorable advertising is not sufficient. Consumers are much more developed in terms of their engagement with brands. This is supported by the fact that they do not wholly trust brands anymore but are actively looking for information before making any decisions.
A study by Accenture shows that 75% of consumers are more likely to buy a brand, which offers personalised services that are based on individual preferences. In a survey done by Infosys, 86% of consumers say that personalisation has some impact on their purchasing decisions and 25% mention that personalisation substantially influences their buying decisions.
Owing to unparalleled access to detailed information about consumer buying behaviours and needs, brands now have in-depth insight into consumer preferences. These requirements can be addressed at an individual level, in a highly customised way and with the power to scale. This has resulted in hyper-personalisation of brand offers.
Brand management in a data-driven culture
A data-driven culture encompasses the use of data in decision-making. It handles data as a strategic asset of the organisation through the process of making data widely available and accessible. It focuses on securing, cleaning, and curating significant data from across the company.
It promotes regular experimentation to learn in addition to improving. It realises that a solid foundation of data is critical for distinguishing the organisation through artificial intelligence (AI) and machine learning (ML). It is a culture with a high degree of data literacy as well as a belief that data helps everyone perform better.
In many companies, data silos are guarded enthusiastically by organizational silos. Frequently, it is coming from an important place, that of making sure that the rest of the organisation understands the context, variables, estimates, and patterns of certain data elements to use them the correct manner.
Do not allow this to be yet another reason to deny the enterprise access to data, but rather to convert these guardians into educators. Let these departmental data experts take over ownership of teaching and assisting others in the organisation to use data the right way and enhance the data literacy of the enterprise.
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