These days, the terms ‘data’ and ‘data driven’ are indispensable in our daily life. Responsible used data is a powerful tool for brands and is proven to be a recipe for success. Especially when it comes to create brand experiences – a rarely measurable and intangible “product”- data, and therefore required transparency and measurable tools, is inevitable.
Integrating data-driven analytics into brand strategy will empower clients to make informed and quantitative decisions and even offers a valuable source of competitive advantage if suppliers command required tools. The more integration of data within brand experiences the more transparency, trust and insights they provide for stakeholders. Of course, decision-makers have a better feeling to conduct a certain event if the choice is not solely based on gut feelings – as even the best gut can fail sometimes. Data is unlikely to be misleading as its integration from inception all the way to execution and after is necessary in order for brands to build upon previous successes and previous failures.
There is million of data out there – but which is important for brand experience? Which data is transferable to actual advantages and delivers added value to both, customer and brand? It is crucial for companies to know their consumer. However, it is just not enough in 2018 to only have geographic, demographic, psychographic, and behavioural segmentation. To put them in conjunction with one another is key and will create maximum impact on real claims regarding brand experience. Second, to fully understand your target market, you need a certain tool to transfer all the gathered information in actual unique experiences. Only the big picture about the customer can really tell companies how to create the maximum successful brand experience. Marrying the brands visions and values with accurate target market data, the event will be a customer driven/shaped and consequently memorable event.
During the event itself, gathered data predicts, informs, or even warns brands on making appropriate decisions. All data helps brands to predict certain incidents and offers the chance to react quickly and change parameters in order to make experiences more valuable. An example: If there is an interactive activity at an event, such as projecting your own quote on a huge, common screen, and the whole technical equipment was assigned to IOS devices, however it turns out all the participants use Android, intelligent data analysis systems can help to recognize such problems and swop the technical orientation to Android.