Big Data, Consumer Behavior and The Consumer Packaged Goods Blindspot
Name: Joanna
Student ID: D0711965
Blog#3: Big Data, Consumer Behavior and The Consumer Packaged Goods Blindspot
As we know that, big data is very valuable. By this article, we can see that big data has three sources;
- Social data: Social data is build up by customers’ online behaviors.
- Machine data: Machine data is mostly build-up by actual human behaviors.
- Transactional data: Transactional data is comprised of online and offline transactions and records.
But these data don’t really help those providers know how to improve their products better to let more customers buy their products or make the products match user behavior. Therefore, develop a big data source which catches the real-world user behavior will help those providers know what the customers want and needs.
The most useful data is tracking usage; from the product’s package, which will be kept the longest in the whole useful life. If providers add a chip and Bluetooth transmitter in packages, for example, place the chips within bottle caps and lids, that it can connect with customer’s mobile devices. Hence, the providers can capture the informations like how often do the customers open it, how long to customers finish it, do customers follow the directions, and so on. Moreover, when the products’ packages knows that the product is almost empty or expiring soon, they can remind the customers to order a new one, and they also help providers to keep customers loyalty.
Almost everyone knows that we live in a world that our “mobile devices” listen to what we say, thence, providers can capture the information. Although big data are using this way, but not everyone accept his/her privacy is known without reservation.
In conclusion, data’s “privacy” is still an issue that we should think and pay attention to.
The key to success in the business is to know what your customers, but each product has its own customers, and these customer types are different. If there is no customer group, the marketing method will become very vague and not efficient. In addition, by grasping the ideal customer, you can accurately define the marketing language, so that the customer can connect with you without obstacles. For example, the ideal customer base of a technology company today is someone who is 30-40 years old, has a physical storefront, and has no in-depth knowledge of technology. If the marketing personnel repeat the words big data and AI, they have more sense of distance. The target customer group will be confused and will not consider this technology company, so it is necessary to choose their language to communicate in order to increase the affinity. Therefore, it is very important to find the target customers! If companies want to find the target customer group, they must first subdivide all consumers, and classify consumer behavior into categories, such as region, what kind of product to buy, gender, age, etc. Through these "adjectives", you can leave a number of each product Adjectives, these are the sources that define the "target customer group". From here, you can find that you can more accurately describe marketing statements to attract different target audiences. What they need is a website analysis tools. If the company has its own official website or shopping page, there are many tools to collect consumer behavior information on the site, such as the well-known tool google analytics, intuitive hotjar, can help you understand consumers.
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