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?

How Big Data Change Journalism?

Journalism is the activities of gathering, evaluating, creating, and news and information delivery. It requires verification, accuracy, and creativity. The recent development of communication and mobile technology made the process more efficient and influential. The evolution does not stop there. The emergence of Big Data may once again alter the game rules of journalism.

 

Big Data and Article Screening System

 

big data

 

Lifehack is a leading online media. It produces articles daily, which about making things easier and better in every aspect. It provides practical and adaptable knowledge dedicated to improving Health, happiness, productivity, relationships.

 

The monthly page views of Lifehack in 2017 exceeded 20 million. It has over 1 million followers on Facebook. However, the company has only a dozen people operating, most of which are IT programmers. Leon is the founder of Lifehack. He chose English as the language of the online media at the beginning, therefore the readers extended to English speakers worldwide.

 

big data

example of Lifehack’s article

 

Leon used Big Data to further expand Lifehack. Leon had a programmer created an “Article Screening Automatic System.’’ It monitored the vastly updated articles on more than 200 of the world’s most popular online media. It estimated the popularity of each article, by calculating the number of Like and Share in social media. The system highlighted the articles automatically once it qualified.

 

The editor Anna was responsible to interpret the results. She grasped and studied the themes, structure, and style of those popular articles. She anglicized them and integrated a manuscript, then sent out to their writers. The manuscript was more like a guiding book, which includes the suggestions on writing directions, styles, and keywords. It adopted the Big Data concept gathering mass data from the internet. It spotted out successful popular articles automatically, which reduced labor force. We called it Data Driven Journalism.

 

 

SEO Results Supervisor: Robot

 

Lifehack further developed a ‘Robot’ system for internal supervising and analysis purposes. Robot monitored the SEO ’‘search engine optimization’’ results and scored them based on their popularity. The good or bad standard toward an article was subjective. The Robot made it an evaluable and objective scoring system. Lifehack exploited the A/B choice to determine the best writing scheme. Lifehack published A and B version under the same topic, then Robot compared the SEO results. Journalism shift from editor-driven to data-driven. The change is controversial. Some argue that themes and style are being influenced by Big Data, which endanger creativity and diversity. Let’s see some headlines we can find in Lifehack.

 

‘’ 7 Simple Hacks To Make Your Days In The Kitchen Easier、10 Effective Leg Exercises You Can Do On The Couch、7 Easy Body Language Tricks to Help You Get Over Anger and Get You Back to Feeling Great and etc.’’

Above headline’s style are quite similar. Styles become singular and dull.

 

The consequence of data-driven journalism is that labor is being replaced by AI. Bad news for employees but absolutely good news to entrepreneurs. An automatically accurate system brings insights on customer’s interest. It allows understanding the demands of your market while improving your work to satisfy the needs of customers.

 

Other articles:

 

CRM System, Improved and Evolved

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?

Social CRM: Game Changer

Customer Relationship Management System (CRM) is a system to manage current and potential customers. It usually makes use of the incentive program and membership program to attract customers, thereby enhancing revisit rate and customer loyalty. The system collects data from members and customers to conduct big data analysis. Today it isn’t enough! You have to collect the ‘’Fans’ ‘data as well. We call it Social CRM.

 

Social CRM

Social CRM-Fans to Customers

 

‘’Fans’’ is a new keyword which emerges in recent years. Fans are potential customers who have interest in the products or services. The keyword “fans” is closely related to social media. Many merchants start running their own Facebook, Twitter, YouTube, We Chat and etc. Social media allows footprint collection and interaction with fans. You can engage with fans and ‘get likes’ to increase loyal customers.

 

Social CRM: Low Conversion Rate?

 

Just recently, I was invited to ’like’ and ‘follow’ a Facebook page by a restaurant. As a return, it offered a cocktail for free. I believe everyone shares the same experience right? Shops offer discounts to induce fans on Facebook, and most people will do that. However how many of you un-follow the Facebook page afterward? The promotion is effective but only work for a while. Only a few fans will keep following the Facebook page. Therefore, the conversion rate is low while the cost can be quite expensive.

’Content’ and ‘engagement’ is the foundation of Social CRM. Fans may leave you once they found your content not interesting. Continued engagement is more important than discounts. Instead of spending money to offer discounts, it is more effective to spend resources to enrich your content.

 

Social CRM-Big Data

 

Social Marketing is the trend of the times. Many enterprises reduce traditional media advertising and spend more resources on Social Media. They made videos, info-graphic, text to interact with fans. Fans and visitors response and sometimes even engage with you.

Those engagements from fans are valuable data, which represents the consumption behavior and preference. Don’t waste them! What you need is an automatic CRM system which allows data analysis, data collection, continued monitoring and prediction. Like Google Ads, they collect your footprint and cookies on internet, analysis and then deliver related advertisements. If you search shoes on the internet then you will most likely see a shoe advertisement on Facebook.

Social CRM allows enterprises to engage with fans and customers across multiple channels. This is precious because it understands of customer needs more effectively than more marketing research ever could. Social CRM is redefining customer relationships management and also reshaping long-standing business processes.

 

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?

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?

大數據銷售-比顧客自己更了解顧客(下)

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。

 

大數據銷售-演算法先知系統

 

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。

 

大數據銷售-客制化的推薦界面

 

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。

 

大數據銷售

奧瑪·花曼

 

 

Netflix針對每天過百萬次的搜尋、評價、以千萬計的播放量進行觀測,整個過程的搜尋、點擊、播放、暫停、快轉、罷看、重播、添加書籤、正負評價,都會被視為事件紀錄在系統當中。同時整合地理位置、使用收看裝置、收視率、社交媒體分享等,通過大數據分析和的演算法,Netflix就可以精準分析與理解觀眾的收視習慣,判斷有那些內容比較受到會員的青睞,根據這項結果Netflix的推薦引擎可以激發觀眾的興趣,協助每個人快速找到自己想看的內容。

 

大數據銷售-利用CRM會員系統

 

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。

總結來說,如果企業能藉由大數據分析,結合CRM系統,能精準地將推銷優惠內容呈現給最適合的顧客,必定能大幅提升客人消費體驗。如此一來,用戶也就有更大的誘因繼續留在你的企業上,而不會輕易被新進業者的低價促銷或大製作內容吸引走。更重要的是,一個優惠推廣或者銷售策略,並不能針對所有的客人,由於每個客人都是獨一無二的,只有能掌握每位觀眾的喜好,才有機會趁勢而起提高銷售命中。

 

其他大數據銷售故事:

大數據分析-比顧客自己更了解顧客(上)

大數據行銷-是捕捉客人的真命天子?

客戶關係管理-邂逅大數據

從粉底說數據行銷

數據行銷第一步

延伸閱讀

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?

大數據分析-比顧客自己更了解顧客(上)

大數據(Big Data)的收集、分析,對於計劃營銷策略和提高客人忠誠度有多重要?串流影音龍頭 Netflix,劃時代的成功,再一次印證了客戶關係管理(CRM) 與大數據所帶來的龐大效益。Netflix是首個利用大數據演算的電視媒體-大數據分析-這項技術能精確採集電視顧客信息。並以這些信息為參考依據,掌握客戶的喜好、消費模式與習慣,繼而要對他的未來購買行為有準確預測,商戶就可以在適當的時間、以適當的手法和符合客戶心意的激勵計劃誘導客人進行消費。

大數據分析-帝國的形成

近年來,隨著互聯網技術的發展與各類流動裝置的廣泛普及,再加上各種新媒體平台科技的發展,整個社會完全邁入大數據時代,每天產生出難以估算的海量數據。而電視媒體在這種時代背景下,Netflix積極改變營銷策略,與時俱進,利用大數據與CRM (客戶關係管理) 的結合,將自己打造成串流影音的王國。

Netflix 的大數據分析帝國已經成型。五年來,Netflix 股價大漲十倍,並在今年六月市值突破 1,700 億美元,超越 迪士尼。今年第二季,Netflix 共新增 620 萬用戶,其中 510 萬來自美國以外的海外市場,據估計,Netflix 海外用戶在 10 年內,將從 2018 年底的 8,300 萬,會以每年平均兩成的速度成長至 2.5 億。

這些數字或者你並不感興趣,但Netflix 正掌握龐大的顧客消費數據和消費模式,而且擁有非常準確的收視紀錄。這些就是大數據,被喻為21世紀的石油。

隨著它的用戶不斷增加,商品(電視)種類越來越多,它的大數據資料庫越來越準確和完整

 

大數據分析2

Netflix ,你一定認識這間公司,它旗下的作品你亦一定略有所聞,從英國女王傳記《王冠》、懸疑驚悚片《怪奇物語》、現代科技反思路線《黑鏡》到青少年霸凌題材《漢娜的遺言》。Netflix 製作影集的範圍很廣,Netflix 又是如何讓觀眾在成千上萬種影音內容中,找到自己喜歡的影片?

答案正是應用大數據分析(big data analysis) 進行個人化的推薦,將不同但更適合的內容推送到個別用戶眼前,亦即是達致精準行銷

在大數據時代,網絡搜尋度、網站訪問量、影片點擊、觀看、留言等多種互聯網的活動全部都會產生大量複雜的數據,這些數據可以收集、計算、量度、統計和分析。 這能夠有效反映出不同電視受眾對同一電視節目的接受認同度、喜好等等。

而電視媒體則可以通過不同渠道,精確採集電視受眾信息,並以這些信息為參考依據,制定針對性強的營銷策略,打開目標受眾市場。 舉一個簡單的例子,透過大數據分析,Netflix發現一些都市戀愛劇這類節目的電視節目主要受年青的都市上班族歡迎, 並且發現這類節目在年未、聖誕節臨近推出會獲得較佳的播放效果。於是乎調整上映節目時間表,以獲得更佳收視鞏固現有客戶。

除此之外,影片推薦系統亦是大數據分析的著名例子。有關內容將會在下一篇詳盡說明。

 

其他數據行銷故事:

 

大數據銷售-比顧客自己更了解顧客(下)

大數據行銷-是捕捉客人的真命天子?

客戶關係管理-邂逅大數據

從粉底說數據行銷

數據行銷第一步

延伸閱讀

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?

大數據行銷-是捕捉客人的真命天子?

大數據行銷-這架列車亦吸引了台灣速食連鎖龍頭麥當勞搭上,麥當勞目前已有多項支付方案正在進行或計劃推出,包含「麥當勞點點卡」、「信用卡小額支付」服務、與發卡銀行合作發行「麥當勞聯名卡」等。沒錯,以提供優惠來吸引和鞏固顧客絕非新鮮事。然而,在大數據爆炸的年代,這些客戶產生的數據就是21世紀的新石油,只要好好利用,香港的企業其實可以同樣借鏡參考。

 

大數據行銷

 

大數據行銷-提高精準行銷命中

透過這些會員管理系統(Member Management System),能有效精準地收集顧客消費數據。以台灣麥當勞的會員卡系統為例,客戶持卡消費除了免卻現金支付及找零的麻煩外,最有價值的部分莫過於蒐集大量且精準的客戶消費資訊。在顧客點擊、瀏覽產品、下單、付款等等這些客戶接觸點中,顧客都會產生大量數據。就好像是一幅幅客戶的自畫像。零售商可以清楚地掌握會員消費的時間、地點、品項、數量及金額,這些都是非常寶貴的企業經營數據,有助了解客戶的喜好、消費行為與消費模式,並可掌握產品銷售的情報與熱度。

要知道,同一套的優惠計劃並不能吸引所有人,正所謂「一樣米養百樣人」,折扣(discount)對某些人很吸引,但對另一些人,出席活動的優先性或是會員特權(privilege)才更具吸引力。

透過大數據分析(Big Data Analysis),可以精準掌握客戶需求和喜好習慣,零售系統便可以各類型的溝通管道,例如簡訊、App推播、Facebook、Line或是email,不定期或在特定節慶或時間(event-based)將客製化、個人化的產品與促銷活動訊息提供給會員,達到精準行銷的目的。你亦可以將會員分門別類,提供針對以特定客群為導向的市場營銷策略,提高銷售的命中。

新零售新行銷,都是基於大數據。只要好好利用,與CRM (Customer Relationship Management System)結合,便能加強對顧客需求的了解,改善顧客消費體驗,以提高顧客忠誠度(customer loyalty)

其他數據行銷故事:

客戶關係管理-邂逅大數據

從粉底說數據行銷

數據行銷第一步

延伸閱讀

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?

客戶關係管理-邂逅大數據

客戶關係管理 , (CRM) 是指企業透過實踐、策略和技術對整個客戶生命週期的管理,及對客戶互動和數據的分析,目標是管理及保留現有客戶和推動銷售增長。這種概念其實並不新鮮。但隨著資訊科技、流動裝置普及、以及大數據(BIG DATA)的崛起。這些因素和市場轉變使到CRM(客戶關係管理)更準確容易收集客戶數據。CRM的系統能以不同渠道收集客戶數據,包括公司的網站、電話、實時聊天、直接郵件,營銷材料和社交媒體。 CRM系統還可以收集和分析提供有關客戶個人信息,購買歷史記錄,購買偏好和顧慮的詳細信息,有助企業有效管理現有客戶和掌握他們的消費行為。你能夠把握市場的轉變,利用大數據和CRM的結合契造商機嗎?

客戶關係管理

客戶關係管理(CRM)-組成部分

CRM軟件將客戶信息和數據整合到一個CRM數據庫中,以便業務用戶可以更輕鬆地訪問和管理。隨著時間的推移,CRM系統中添加了許多其他功能,包括括通過電子郵件、電話、社交媒體或其他渠道記錄各種客戶活動,從而跟踪客戶的消費模式。

最新的CRM系統還有以下的功能,進一步加強客戶關係管理的成效:

營銷自動化

具有營銷自動化功能的CRM軟件可以自動執行重複性任務,從而加強生命週期中不同階段的營銷工作。例如自動向潛在客戶及現有發送營銷材料、推廣資訊,將客戶忠誠度最大化。

地理定位技術或基於位置的服務

一些CRM系統包括可以根據客戶的地理位置創建地理營銷活動,有時可以與流行的基於位置的GPS應用程序集成。地理定位技術還可以用作網絡或聯繫人管理工具,以便根據位置查找銷售前景。

工作流程自動化

CRM系統通過簡化普通工作負載幫助企業優化流程,使員工能夠專注於創造性和更高級別的任務。 領導管理: 可以通過CRM跟踪銷售線索,使銷售團隊能夠在一個地方輸入,跟踪和分析潛在客戶的數據。

分析(Analytics)

CRM中的分析有助於通過分析用戶數據和創建有針對性的營銷活動來推動更高營銷策略命中。

 

要了解CRM可以如何幫助企業,歡迎瀏覽網站其他文章,或點擊以下連結。

大數據行銷:為客戶畫像

無人機送貨不遠了!大數據分析將是零售業關鍵

[CRM Big Data]數據行銷:如何讓客戶自願給你個人數據?

 

延伸閱讀

Understand your customers better with big data

Will Big Data Finally Turn CRM Into Something Truly Valuable?

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