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- 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?

大數據行銷:為客戶畫像

 

crm big data

什麼是客戶畫像(Customer Profile)?顧名思義,就是為你的每一個客戶畫一幅畫像,這不是一幅抽象畫,而是寫實畫,線條愈是細緻愈好,用數據將客戶的面貌特徵完整地表達出來。

Jeff Tsui在媒體行業擁有超過30年的經驗,在主流和新興媒體等領域擁有廣泛的專業知識。他創辦了多家IT公司,在戰略規劃,工作流程和公司結構設計,營銷和銷售以及管理積累了豐富的經驗。Jeff是一位受歡迎的專欄作家和電台主持人。

這篇有關CRM & Big Data的文章嘗試為大家解答以下三個問題:

  • 為什麼大多的「會員激勵計劃」效果總是有限?
  • CRM如何才Work?
  • 如何令客戶持續跟商戶「交往」

在今天這個大數據時代,數據分析的重要性已經不用多作強調了,其中在商業社會的應用,最普遍的就是「客戶關係管理」(Customer Relationship Management CRM)。

沒錯,CRM已經是一個十多年的舊詞彙,它強調的是如何增加客戶的忠誠度(customer loyalty)。不過今天的CRM強調點和著力處其實跟十數年前的已有所不同。

為何CRM成效不彰?

十數年前,做CRM工作的市場人員,花最大的精力在設計一套「會員激勵計劃」(Incentive Program),用廣東話來說,就叫做「著數」,期望這些「著數」大幅增加會員的「重訪率」(Revisit Rate)。

效果如何?大部分從事會員事務的市場人員都會告訴你,相當有限!但老闆不滿意,向市場經理問責,市場經理於是重新設計會員激勵計劃,初期部分會員的重訪率或許增加了,但過不了一段日子,報表上的重訪率依然固我。

除了重訪率之外,還有新會員註冊率、會員消費平均金額等等報表都給出類似的狀況。於是有不少負責CRM的市場推廣人員開始懷疑CRM的價值。

若果你就是上述的市務推廣人員,我希望你花大約五分鐘的時間繼續閲讀下去。

CRM沒有Big Data,靠「估」的會員激勵計劃

為什麼CRM的會員激勵計劃產生不到預期效果?因為是由「你」設定的!

先別生氣!我的意思是設計會員激勵計劃的市場推廣人員,大都是按照經驗訂出一套他們認為具吸引力的會員激勵計劃。不過,這有點像是碰運氣,給你猜對了,就會work一陣子,猜錯了,就唔多work 。

為什麼說work一陣子?因為商業世界變化迅速,市場上眾多的競爭對手同時在給出不同的激勵計劃吸引客戶的眼球,對吧?!還有,一條橋總有用老的一天,今時今日,一條橋的壽命愈來愈短。不過,經常轉橋又可能令會員難於適從。這又該如何是好?請容我稍後一次過給出我的答案。

CRM的會員激勵計劃唔work還有另一個更根本的原因,就是「一套」激勵計劃根本刺激不到所有人,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)才吸引到他。也就是說,「一套」激勵計劃不可能令所有或說大部分的會員持續光顧。

必須承認,若然你的CRM就停留在不斷給「著數」會員,CRM的績效也只會停留在某個水平。

Big Data Analysis是CRM的新「著力點」

要突破CRM績效,必須從「數據分析」(data analysis)入手,也就是說,要了解每一個會員的喜好、興趣,最重要的是了解最能刺激他們消費的「誘因」(incentives)。若你能夠了解你每一名會員的程度超出他的朋友、父母、伴侶甚至他自己,你就有可能為這個人設計出能刺激他購買你的產品/服務的「會員激勵計劃」。

這也就是我在本文之初所說的,今時今日經營CRM的「著力點」已經改變了,由設計一套「會員激勵計劃」轉為「客戶數據分析」。

說到這裡,我要引入一個近年經營CRM的重要概念,它叫做「客戶畫像」(customer profile)。

為每名客戶畫一幅寫實畫

什麼是客戶畫像?顧名思義,就是為你的每一個客戶畫一幅畫像,這不是一幅抽象畫,而是寫實畫,線條愈是細緻愈好,用數據將客戶的面貌特徵完整地表達出來。

要為每一個客戶用數據畫像該如何開始?首先當然是採集有關客戶的數據,愈多愈好。在這一點上我必須作出補充,在採集數據時,除了要符合當地法例之外,還不要引起客戶的反感,最好就是在他們的同意而不作滋擾之下,又或是客戶主動提供資料以換取他們所需要的服務或便利。這方面若大家有興趣了解更多,可參考拙文《收集客戶數據的三個最佳方法》( https://bit.ly/2P4JZa1 )和《如何讓客戶自願給你個人數據?》( https://bit.ly/2wqdJGr )。

好了,讓我們來談談客戶畫像要採集哪些數據。

建立自動化的「用戶模式」(Customer Profile)

所謂「客戶畫像」是根據客戶的「社會屬性」、「生活習慣」和「消費行為」等訊息而作出標籤(tagging)的「用戶模型」。具體包含以下幾個維度:

• 固定特徵:性別,年齡,地域,教育水平,生辰,職業,星座

• 興趣特徵:興趣愛好,使用APP,網站,瀏覽/收藏/評論內容,品牌偏好,產品偏好

• 社會特徵:生活習慣,婚戀,社交/訊息渠道偏好,宗教信仰,家庭成分

• 消費特徵:收入狀況,購買力水平,商品種類,購買渠道喜好,購買頻次

• 動態特徵:當下時間,需求,正在前往的地方,周邊的商戶,周圍人群

如何採集上述數據?有些是已經在你的CRM數據庫(customer database) 內的,有些則要透過將所有客戶會經過留下「足跡」的網絡平台如公司網站、社群媒體、電郵、App、活動登記⋯⋯都要進行有系統的數據採集、儲存、標籤和分析。

這𥚃舉一個例子,客戶登入公司網站或App後,其Cookie就一直駐留在瀏覽器中,從客戶在網站上的各種動作、點擊的位置、路徑等方式,便可識別與記錄他們的瀏覽行為,然後持續分析瀏覽過的關鍵詞和頁面,從而分析出他的長短期需求和興趣。

每一名Member都有一套動態的激勵計劃

當拿這名新會員的數據與數據庫內其他客戶的數據作出比較,就可初步為這名新會員作出標籖並消費行為預測,按著這個預測,為新會員設計符合他的「會員激勵計劃」。

當這名新會員的數據愈來愈多,可作的標籤亦愈來愈多,作出的消費行為預測就愈來愈準確,你可以為每一個客戶訂出度身訂造的激勵計劃,人人不同,而且計劃的設計不是猜的,而是有數據支持。每一個客戶的激勵計劃不但有別,而且是按照客戶的消費行為和對激勵計劃的回應而作出動態式調整,令客戶的回訪率不斷增加。

說到這裡,或許有人會說,每一個客戶都有自己的一套激勵計劃,市場人員豈不疲於奔命嗎?!

上述採集、儲存、標籤、分析、訊息回饋、再儲存、再標籤、再分析⋯⋯,若是使用「大數據系統」(Big Data System),將會是一個自動化的過程。你需要的是找一家公司為你建立一套「數據模型」,上述的程序就會自動運行。

首三個月決定客戶是否跟你「交往」

好了,是時候解答之前在本文留下的一個問題了,CRM總要有一套「會員激勵計劃」吧,經常轉橋又可能令會員難於適從,該如何是好?

沒錯,一套「會員激勵計劃」是必須的,也不用頻密轉橋,但當有客戶加入成為會員,你就要按著現存的數據為客戶畫像,並在首三個月,頻繁地按照畫像的分析結果給予不同的優惠,這名新會員的回饋訊息將增加畫像的線條,令畫像更加清晰,讓每次的推廣更加準確有效。

一名客戶成為會員的首三個月是「活躍黃金期」,就像初拍拖的男女,因為新鮮感而處於開放和樂於分享的狀態,他會更樂意收到優惠資訊,會更傾向點擊或回應優惠訊息。所以,要建立客戶跟商戶的互動性(interactivity),首三個月,給他們多些符合心水的優惠,之後他們就會傾向一直保持與你「交往」(engage)。

作者:徐少驊 (先達智能有限公司行政總裁)

作者其他數據行銷故事:

從粉底說數據行銷

數據行銷第一步

差異化定價與大數据

數據行銷:如何讓客戶自願給你個人數據

收集客戶數據的三個最佳方法

延伸閱讀

Understand your customers better with big data

Will Big Data Finally Turn CRM Into Something Truly Valuable?

八大数据分析模型(一):用户模型

 

[CRM Big Data] 收集客戶數據的三個最佳方法

Jeff Tsui在媒體行業擁有超過30年的經驗,在主流和新興媒體等領域擁有廣泛的專業知識。他創辦了多家IT公司,在戰略規劃,工作流程和公司結構設計,營銷和銷售以及管理積累了豐富的經驗。Jeff是一位受歡迎的專欄作家和電台主持人。
今時今日,無論係商界定係政界,都在「拚數據」,千方百計「收集」(collect)數據,然後拿來「分析」(analysis),再看有什麼「洞見」(insight),說穿了,所謂的「大數據分析」(Big Data Analysis)就是這麼一回事。這一篇文章,講的就是客戶大數據分析( CRM Big Data),文章是長了一點,但花大約五分鐘掌握如此重要的商業新概念也是值得的。

Synapbox

新聞一則:一家叫做Synapbox的初創企業(Start Up)自家研發一個表情識別技術和大數據平台,通過桌上或是平板電腦、智能手機的鏡頭幫助企業進行各項市場調查,方法是透過辨識消費者在瀏覽廣告時出現的眼球活動和面容變化,就可以推測消費者對這則廣告的真實反應並計算出他們的「廣告轉化率」(Conversion Rate),即由看廣告化為購買行動的機率。

大數據分析三步曲:收集、分析、洞見

要玩「數據行銷」(Data Marketing),第一步是「收集」數據。這一步,說容易不容易,說很困難嘛也不是,主要是用「合適的方法」加上一些數據收集的技術工具即可。

什麼是合適的方法呢?我在之前的《如何讓客人甘心情願給你數據》一文提到:

要客人願意提供個人數據,必須首先符合客人的需求,這方面比起提供優惠更加有效。在招募會員時,很多時我們都會著力於提供『著數』(優惠),這當然是必須要的,不過有時優惠計劃未必符合每一個客人的口味,要客人甘心情願的留下個人資料,應該從需求著手。愈來愈多零售業提供免費送貨服務,既讓客人感到方便,亦能夠讓客人心甘情願留下不少個人資料。

免費送貨服務只是一個例子,原則是當客人提供數據就可以滿足到他們的需求,客人就甘心情願提供個人真實數據。

把會員表格都丟進廢紙籮吧!消費者的數據不是這樣收集的!而且問卷調查收取回來的數據根本沒有太大的分析價值。

把會員表格丟進廢紙籮吧!

我提供「客戶關係管理系統」(Customer Relationship Management System CRM System)這個業務不經不覺已經有十五年,人生有多少個十五年啊(慨嘆mode)!不少客戶都告訴我,要消費者成為會員難,好了,用眾多優惠成功說服他們願意入會了,遞上入會申請表格,客人就立即扁晒嘴,有一半人打退堂鼓。於是,為了減少這種「縮沙」的情況出現,不少商戶的入會表格所需填寫的資料愈減愈少,什麼教育、喜好……這類問卷調查,想也別想了。

若你曾經是或現在仍然是市場部負責會員業務的,你一定是看得連連點頭吧!

不過,今時唔同往日,讓我大膽說一句,把會員表格都丟進廢紙籮吧!消費者的數據不是這樣收集的!而且問卷調查收取回來的數據根本沒有太大的分析價值,一來問卷調查的答案不一定是真的,譬如說,你問我的喜好,我說愛旅行,我「愛」,但不一定有時間、金錢去旅行啊,你要我填寫學歷,我填大學畢業,但其實我是中學畢業生,難道你要拿我的畢業證書來核實嗎?

CRM Big Data收集消費行為數據(consuming behavior data)

不過,其實問卷調查最大的問題也不是答案的真實性,而是數據的分析價值(data value)很低。怎麼說呢?譬如說,我是大學畢業生又或是企業主管,難道我的消費力就一定高於一名小學生或是初入職場的菜鳥?當然不是啦!當中有太多變數了,譬如說消費意慾的高低啦、可支配收入的多寡啦、有否其他收入來源啦(菜鳥原來是富豪的私生子)……,要數下去可以再寫上千百個變數。所以,今時今日,沒有數據分析師太過著重這些靜止的(static)人口統計數據(demoghraphic data),而是集中火力收集動態的(dynamic)消費行為數據(consuming behavior data),也就是說他們實實在在的跟消費有關的行為數據,從他們瀏覽廣告追蹤至購買的行為,推算他們下一次的購物時間(Next Purchasing Time, NPT)

要獲取消費數據,是不一定要由消費者「提供」的,而是在得到他們同意後,無須滋擾客戶的情況之下「收集」的,當然一切都必須符合當地的私隱法例,有些鬆有些緊。

給客戶一個獨一無二的ID

通常操作的第一步是給與每一名消費者一個「獨一無二的身分」(unique identity),最佳的方法是設立會員制度 (Membership Program),用優惠措施和特別待遇(飲食業會員可獲優先入座、商場和超級市場會員可獲免費送貨或折扣日優先購物)鼓勵客戶成為會員。然後給每一名會員會一個會員編號,以後他的所有消費行為都會集中記錄在這個身分之下。不是會員的客人就收集不到他們的消費數據嗎?也不是的,這一點容後再說。

有了客戶的ID,就要「千方百計」的收集「消費行為數據」。不過,所謂的「千方百計」,首先你最好先想想,有什麼數據是「必要」的,因為收集數據是要費用的,多一個數據區(data field),就需要多一筆費用。

要收集數據,有一些是要驚動客戶的,但絕大多數情況是在不用滋擾客戶下密密收集的,以下是最常用的方法:

crm big data

Google和Facebook都全力向Analytics進發,容許所有網站、網店、App免費使用它們的數據分析軟體。目前很多中小企的網站、網店和App都沒有使用數據分析軟體,即使有使用的也沒有作有系統的數據處理與分析,但我相信無論是Google Analytics還是Facebook Analytics都會很快成為市場人員必須懂得使用的工具。

市場人員必須學懂Google AnalyticsFacebook Insight

1/ 無論是網站、網店、移動程式(App),你都可以連結數據分析軟體(Analytics Software),就可以知道來訪者的登錄網頁、離開網頁、瀏覽過的網頁、逗留時間、瀏覽軌跡、來自區域、重覆到訪還是首次到訪…..。如果到訪者是會員,就可以結合會員數據作出分析,若然來訪者不是會員,也可以透過「網路小甜餅」(Cookies)知道每一次的到訪是來自那一部電腦、平板或是手機。當會員或是到訪者在瀏覽網站、網店、App時,他們不會覺察到自己的瀏覽行為正在受到密切監察、記錄和分析。

事實上,GoogleFacebook都全力向Analytics進發,容許所有網站、網店、App免費使用它們的數據分析軟體。目前很多中小企的網站、網店和App都沒有使用數據分析軟體,即使有使用的也沒有作有系統的數據處理與分析,但我相信無論是Google Analytics還是Facebook Insight都會很快成為市場人員必須懂得使用的工具。

文首的Synapbox所提供的服務或是工具其實是屬於這個範疇,不過他們使用的數據採集工具是鏡頭,而收集到的數據是瀏覽者的眼球活動和表情。在這𥚃我想多說數句,老實說,我對這種技術有保留,最困難的不是數據收集,而是數據「定義」(definition),有了定義,我們才可以進行分析,表情和眼球轉動的詮釋是一個不容易的學問。這使我想到社媒大數據(Social Big Data)「語意/語態分析」(Semantic Analysis),究竟社媒貼文和留言的語意/語態是屬於正面、負面還是中性呢?由於語言使用的方式千變萬化而且不斷有新詞彙出現,到今天,提供語意/語態分析服務的公司也只敢說準繩率大概只有六至七成。我看面容表情和眼球轉動的數據定義遇到同樣的問題。

鼓勵到訪者以社交平台戶口登陸

2/ 鼓勵到訪者以社交平台(Social Media)戶口登陸,過去,有網站要求到訪者首先登記(register),然後登陸(login),這個方法不太有效,跟上述會員表格的情況差無幾,使來訪者卻步。不過,現在有超過八成人都擁有社交平台戶口,你可以邀請他們用社交平台戶口登陸,對到訪者來說,他們只是按一個扭,而不是要填寫什麼login nameemail addresspassword既要花時間又要記多一個password,他們的抗拒沒有那麼大。當然,你要人家用社交平台戶口登陸,總得給人家一個理由,這方面的技巧我就留待另一篇文章才交待了。

成功地讓到訪者以社交平台戶口登陸有兩大好處:一、每一名到訪者都有了一個獨一無二的身分;二、你可以收集他們在社交平台的個人數據,強化客戶數據庫的質與量。當然,若果到客戶或是來訪者使用匿名或是沒有活動的戶口,第二點好處就欠奉了。

在店舖安裝數位身分追蹤器也可收集到有用數據

3/ 收集數據,不一定是在網上的,在店舖內也可以。其中一個有效方法當然是搞會員制啦!(你唔係仲未搞呀?!)會員什麼時候到訪買了什麼消費多少都記錄在案。不過,你就不會知道他們曾經拿上手看過感興趣而最後沒有買下的貨品了。要收集這樣的數據,可以在店舖安裝不同的數位身分追蹤器,包括你可以追蹤哪一部手機或平板電腦使用過你的WiFi、你也可以用一些方法鼓勵客戶來訪時開啟藍芽裝置,與店舖的一些裝置產生互動,若果你在店舖不同的區域也安裝了這些數位身分追蹤器,就可以得知到店的客戶去過什麼區域,逗留了多少時間。若你在每一件貨品都貼有無線射頻識別標籤(RFID Tag),則到店者拿過什麼貨品來看,端詳了多久,到最後有沒有買下,都可以知道。

早前震驚中外的一則中國新聞,中國公安透過廣佈全城的「面容辨識」(Facial Recognition)鏡頭,在7分鐘之內就成功抓捕參與實驗的BBC記者。其實面容辨識技術當然也可以應用到店面。不過,除了涉及私隱法律的問題,若商戶真的應用了這種技術,只怕也收集不到什麼數據,因為消費者都給你的裝置嚇跑了!

Japan Toyrus

日本玩具反斗城開發了一個會員App,除了有基本的會員功能,下載了App的人進店後,開啟App,透過所謂的Kazasu Camera對準產品,就可以看到擴增實境(AR)的內容或是介紹商品玩法的影片。

日本玩具反斗城用AR吸引客戶用鏡頭留下數據

在店面收集客戶數據這一點上,我想用一個真實個案來指出,其實你是可以讓來店的客戶主動參與的。

話說日本玩具反斗城開發了一個會員App,除了有基本的會員功能,下載了App的人進店後,開啟App,透過所謂的Kazasu Camera對準產品,就可以看到擴增實境(AR)的內容或是介紹商品玩法的影片,這個Kazasu Camera功能成功地吸引客戶到店購物,同時亦在客戶自願參與的情況之下,收集客戶在店內的消費行為數據,進一步加以分析,並進行「精準行銷」(Targeting Marketing or Precision Marketing)

若你能夠讀到這𥚃,證明你對於數據行銷真的很有興趣。恭喜你,因為無論如何,千方百計地收集客人的消費行為數據這個趨勢是停不了的。作為中小企業的負責人,收集什麼數據是一個策略與資源運用的問題,這個肯定是所有企業未來必須著力思考及處理的問題。

總結一句:能夠讓客戶在被收集消費行為數據這個過程主動參與是上上之策,而在收集過程中在合法範圍內不去驚動消費者也是上策,下策是要客戶填寫任何長度的問卷調查。

作者:徐少驊 (先達智能有限公司行政總裁)

作者其他數據行銷故事:

從粉底說數據行銷

數據行銷第一步

差異化定價與大數据

數據行銷:如何讓客戶自願給你個人數據

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