Facebook and Big Data Insights

Facebook live is a new addition to the social networks. It allows users to record videos and broadcast live to friends and followers. Although the live broadcast is not a brand-new thing, it receives huge success in Facebook. The database of Facebook is enormous and outstanding, which brings valuable big data insights.


Facebook, Big Data Algorithm


big data insights 2


There are over 2.27 billion monthly active Facebook users for Q3 2018. (Source: Facebook 10/30/18). Facebook is the world’s most popular social media with more than two billion monthly active users worldwide. Facebook stores large amounts of data. It’s predicted that there will be more than 170 million Facebook users in the United States by 2018. Facebook is too big to ignore.


There are thousands of posts that might be displayed in the user’s News Feed. The algorithm analysis these posts and arranges their order according to the preference and relevance of users. The Facebook algorithm is constantly improving, in order to provide a good experience for users. Facebook prioritizes posts from family and friends over public because they treasure the connection of person to person.


Facebook, Big Data Insights


Every activities and engagement such as clicking, browsing, like, sharing, follow and etc. They are being collected and monitored by Facebook. Those data became valuable assets of the big database. The big data analysis produces insights. Insights can accurately foresee the user’s interests. Therefore, we can always see the most related post up front. Facebook live apply the same mechanism. In the News Feed, those videos we interest the most will be prioritized.


The emergence of Facebook Live has made the “personal TV station” no longer an obstacle. Everyone with a Smartphone can manage their personal TV channel. Facebook tracks its users by cookies. If a user is logged into Facebook, Facebook can track every site they visited. Facebook grasp the technology of facial recognition which presents its skills in photo tagging and image management.




big data insights 3

TVmost and Facebook


TVmost anniversary award broadcasted live on the free TV network ViuTV, which announced the cooperation between online media and traditional media in content and distribution. The TV online station owns over 7 hundred thousand followers on Facebook. It is a big asset to TVmost. All it has to do is a one-time authorization from fans. It allows TVmost to access fans’ Facebook profile and personal information such as gender, age, location, and ETC. The insights it brings assist TVmost to understand the interests and the characteristics of fans. It benefits TVmost to strengthen their digital marketing services.


The success of Facebook live and TVmost emphasizes the importance of Big Data insights. It helps to improve the customer experience and customer loyalty. Adopting of Big Data solutions helps analyze customer interests and consumption behaviors across multiple channels to determine when, where and how customers are most likely to buy.


Other articles:


Social CRM: Game Changer

Big Data Analysis-CRM Big Data

Big Data Analysis- Collection


Extended reading:


Understand your customers better with big data

Will Big Data Finally Turn CRM Into Something Truly Valuable?

What Is Social Marketing? And How Does It Work?

CRM System, Improved and Evolved

The importance of big data analysis cannot over-emphasize nowadays.  “Customer Relationship Management (CRM)” is the most well-known and introductory application of big data analysis in the business. CRM system is actually an old vocabulary, which highlighted on increasing customer loyalty. Today CRM means something more.


Why is the Incentive Program ineffective?


The incentive program was the mainstream in the marketing industry. Marketers spent most of their time working on the program. They used different discounts to recruit members and increase the revisit rate. However, the effect was unsatisfied. The initial revisit rate increased for a while but not long lasting.

Why is it ineffective? This is because human estimation is unreliable. The marketing staffs designed the program schemes according to their own experience and assumptions. It is more like guessing. Sure they can rely on marketing research, but the marketing change can be rapid. The results can only reflect the preference of the majority. What we need is something more accurate and efficient, a tool that can achieve precision marketing while catching the speed of the changes.


Data analysis is the booster to CRM System


Big data analysis understands the preferences and interests of each member. It can dig in and find out what incentives can motivate customers the most. The focus should now shift from “member incentive plan” to “big data analysis.”  Know your  each customer. A customized, unique promotion and discount to each customer was once impossible but now become doable with the help of big data analysis.


Collect Data and Draw Customer Portrait

CRM System

What is customer portrait? It is to draw a portrait for each of your clients. The more detailed the lines, the better the data will be used to shape the customer’s tastes. What data should we collect?

First, we need to focus on customers’ attributes, their lifestyles and consumption behaviors.

  • Fixed features: gender, age, region, education level, birthday, occupation, constellation
  • Interest: hobbies, APP, website, browsing/collection/comment content, brand preferences, product preferences
  • Social characteristics: living habits, marriage, social/message channel preferences, religious beliefs, family composition
  • Consumption characteristics: income status, purchasing power, product type, purchase channel preference, purchase frequency
  • Dynamic characteristics: current activities, demand, location, surrounding businesses, surrounding people


How to collect the above data to build a CRM system? Some are already in your CRM database (customer database), and some can be collected through their “footprint.” Every their activities on the internet such as clicking and browsing can be monitored. For example, visitors’ browsing cookies remain in the browser. The server can identify and record their browsing behavior from various actions, clicks, paths and etc. We can further analyze their long-term and short-term needs and interests.


You can create tailor-made incentive plans for each customer. Not just different, but also dynamically adjusted according to the customer’s consumption behavior and feedback on the incentive plan. What you need is to find a company to build and design a “CRM System” for you, so the above program can function automatically.


Other articles:


Big Data Analysis-CRM Big Data

Big Data Analysis- Collection


Extended reading:


Understand your customers better with big data

Will Big Data Finally Turn CRM Into Something Truly Valuable?

What Is Social Marketing? And How Does It Work?




Big Data Analysis-CRM Big Data

Some may see Big Data as something distant and complicated therefore not applicable to small and medium enterprises. The truth is Big Data can be practical and profitable. We can use the CRM (customer relationship management) system to practice big data analysis. Let’s see an example of CRM Big Data.

CRM Big Data


Akindo Sushiro is one of Japan’s number one chain sushi restaurants with more than 440 stores nationwide. It takes the lead in implanting wafers under sushi plates to calculate the distance travel by sushi on the slewing belt. Each dish of sushi walking at a predetermined distance will be withdrawn to maintain the freshness of the food to guarantee the quality.

In June 2015, Merchant Sushi Lang launched a Smartphone app (App), allowing guests to book a table through the app. Guests enter the telephone number, region and schedule time. The app will display the waiting time of all the stores in the area. The app will then issue a reservation number. Once the customers arrive at the store at the preserved time, they key in the reservation number on the electronic board outside the store. The electronic board receives the message and the seat will be arranged.


CRM Big Data-Collecting Effectively


This app solves the problem of long waiting time, also making the booking much easier. It benefits customers and most importantly, customers are giving out their information willingly.

Some guests may provide false information in phone or paper during the registration and booking, which affects the accuracy of big data analysis.

By using the Smartphone app’s online booking system, guests can learn the availability of the table, obtain the reservation number and compare the waiting time between different restaurants. The popup notification function is also available. The app notifies users once the table is ready. These user-friendly and convenient functions successfully motivate lots of guests to download the app. They are now happy to leave their true information like phone number, GPS location, age in order to place the booking, which guarantees the validity of the data.


CRM Big Data-Analysis and Insights


The app includes membership program, promotions, and coupons. This package offers not only discounts but also a more convenient and easier way which saves time for guests. All they need to do is to download and register. When the app became more mature and smooth, they further released the take-out service function. This required customer to provide more detailed personal information like the delivery address. Address of your customers can be very useful because it can tell whether it is a business or residential. It indicates the income level of your customers which suggest which groups you should target on.

The merchant’s CRM System integrates the guest’s data and carries out an analysis. The system tracks customers all activities like which store he went to, how many people visited, when did he enter, when did he left, what did he eat, how much he spent, did he use any coupons, did he click the promotions/advertisements through the app and etc.

Once the guest books through the app again, the data management systems will analysis the previous consumption data and conduct preliminary data mining and analysis. The app will offer custom, unique and attractive member discounts which base on the customer’s preference. In other words, every guest may receive different member discounts. If the CRM system detects a customer prefer salmon than tonguefish, the app delivers promotions on salmon more often. This is so-called Precision Marketing or Targeting Marketing, which significantly increases marketing successful rate.

CRM big data 3


Know Yourself, Know Your Customers. CRM Big Data assists you to draw up successful marketing strategies and giving you insights on managing existing customers.  Small, medium and big enterprises can utilize the advantages of CRM system through big data analysis.



Other articles:


Big Data Analysis- Collection


Extended reading:


Understand your customers better with big data

Will Big Data Finally Turn CRM Into Something Truly Valuable?

What Is Social Marketing? And How Does It Work?

Big Data Analysis- Collection

The Membership Management System achieves a new level in CRM because of the Big Data Era. Nowadays the business industries and the political parties are trying everything to participate in Big Data Analysis. The use and influence of big data can be promising. In this article we will focus on how to collect the big data.

Big Data Analysis


A startup company called Synapbox has developed a facial recognition system. It combined with the big data database, in order to assist companies to conduct large-scale marketing research.

They used desktops, tablets, and Smartphone to catch the facial expressions, eye movements and changes while the consumers browsing an advertisement. Then they conducted a big data analysis to calculate the conversion rate, i.e. turning viewers into potential customers. With that accurate data, they can assist companies to carry a more effective marketing campaign to increase customer loyalty.

So here is the question, how do we collect the data effectively and efficiently?

Big Data Analysis


Big Data Analysis – Membership Management System


The first step is Collection. What is the right way? The ideal way is that the customers give you their data willingly. First, you must meet the needs of your guests. Offering discounts through the membership management system is one of the efficient ways to motivate customers. Their registration of membership leave lots of personal information such as age, gender, occupation and etc. It is the foundation of a member database. Once they are registered members, their further consumption activities also provide large amount consuming behavior data, which helps us to draw  the customer profile.

Big Data Analysis – How to collect the data ‘quietly’?


Big Data Analysis

Sure you don’t want to alarm the customers. Most people are quite sensitive and protective referring their personal information. Moreover, you do not want to annoy the customers and affect their shopping experience. So how do you collect the data without interfering the customers?

Membership Management System


Both Google and Facebook are fully committed to Big Data Analytics. Their data analysis software is free and public. You can use the Analytics Software to track the visitor’s all activities such as clicking, login, registration, browse history, region and etc.

Even the visitor is a non-member, you can use the “cookies” function to learn the visiting rate and the devices that the visitors are using. Most importantly, visitors are not aware that their browsing behavior is being closely monitored, recorded, and analyzed.

Japanese Toys “R” Us combines their membership management system with the mobile app to motivate visitors to watch their advisements. The apps also set up a ‘’Kazasu Camera’’,   which allows visitors to visit AR content and watch 3D videos. While their visitors browsing the apps, those AR contents introduce and promote their hero products in a more fun way. It successfully attracted customers to leave more data willingly.


Big Data Analysis – Connecting Social Media Account


The past registration procedure was not effective enough which the visitors were required to fill in a long registration form. Visitors may give up in the middle during the complicated procedure. Now you can shorten the procedure by inviting them to log in with their social media account such as Facebook, Google, Twitter and etc. It saves time and troublesome for visitors and they don’t need to remember one more password. This allows you to give them each a unique identity. You can access their personal data from the social platform to strengthen the quality and number of the customer database. The easier they become a member the more data you collect.

To sum up, it is the best policy to attract customers to participate actively in the process of collecting consumer behavior data. If you finish this article, congregations! You know the key concepts of collecting data. Big Data Analysis is unstoppable, and it is a train we all need to catch up with.

In the next article, we will further discuss a real case.

Extended reading:

Understand your customers better with big data

Will Big Data Finally Turn CRM Into Something Truly Valuable?

What Is Social Marketing? And How Does It Work?


或者我們舉出一個更具體的例子,說明-大數據銷售-分析如何捕捉客人的喜好。Netflix 影片推薦系統就是大數據分析與CRM(客戶關係管理)結合的例子。它容許Netflix 使用更有效率的方式,把適合的內容,推薦給有興趣的特定客群。精準內容推薦或者精準行銷並不是一件新鮮的事,Amazon、Facebook、Google 都是使用用戶歷史行為資料,來推薦商品或產出個人化客製化的頁面,以優化使用者體驗。




但這件事對 Netflix 非常重要,因為在使用影音串流平台時,大多數的用戶是漫無目的尋找能打發時間的電視節目,如果Netflix 無法在短時間內精準推薦用戶喜愛的影片,用戶很容易就被別的平台或傳統電視吸引走而流失。根據 Netflix 2015 年發表的報告 ,80% 的用戶觀看時數都是靠推介而得來的。

為了滿足不同口味的用戶們,Netflix 一直致力於優化推薦演算法。而優化推薦演算法的最有效方法,便是進行大數據分析(big data analysis) 解剖客人的口味和消費模式。

在過去,Netflix 試圖去預測每位用戶對於每部影片的評價 (分數 1-5),藉此推薦用戶可能感到有興趣的內容。不過隨著 Netflix 掌握更多用戶行為資料 (包括用戶觀看的內容、使用設備、收看時間、觀看頻率和長度、觀看地點、性別等等),現在更以機器學習 (Machine Learning) 來進行大數據分析,並以此為基礎建立推薦演算法,對預測顧客喜好行為相當有幫助,例如:觀看影片的順序、不同因素之間的交互作用等等。




Netflix 的用戶都知道,Netflix 的首頁是由不同主題的影片列組成的,這些主題選擇、影片挑選、排列順序背後便是由不同的演算法推算出來,成為一個個客制化的推薦界面。例如,先找出喜好恐怖片類的的用戶,藉此推斷這類觀眾會喜愛與此相關影片。

演算法除了應用在推薦影片之外,其實 Netflix 更加依照個人興趣來客製化電影海報和圖片。如果用戶 A 曾看過較多奧瑪·花曼(Uma Karuna Thurman)的影片,那麼演算法會判斷用戶A 是Uma 的粉絲,因此會將Uma 優先展現在電影的海報上,提高影片對於指定客群的吸引力。










提供限期優惠是吸引客人登記成為會員的有效方法,但如果登記會員程序若過於繁複,會令人望而卻步。在會員系統上,Netflix 善用APPLE這個戰略伙伴。Netflix 容許Apple TV 機頂盒用戶直接連接並註冊Netflix,用戶亦能夠透過iTunes帳戶來支付服務費用。這除了可以節省客戶登記時間、登記手續和付款時間外,更加是一個訪問接觸Apple龐大客戶群的重要商機。最重要一點,是做到神不知鬼不覺地收集客戶數據。最佳的收集數據方法,從來是讓客人自願地提供。利用CRM會員系統,與社交帳號或者APPLE帳號的連結大大加快登記程序,提供多一個便利客人的誘因,便能成功增加客人忠誠度。










Understand your customers better with big data

Will Big Data Finally Turn CRM Into Something Truly Valuable?

What Is Social Marketing? And How Does It Work?