數據分析-如何選擇合適的數據分析公司?

當企業擁有大量的數據時,如何挑選合適的’數據分析’公司便成為了決策的難題。

進入大數據( Big Data) 時代,企業在數碼市場推廣自己的業務時,都會產生大量的數據。客戶使用互聯網、手機APP購物時,客戶登記、輸入、瀏覽、購買、搜尋等等動作全部都會產生大量的數據。這些資料可以是黃金,但如果沒有正確的數據分析 (data analysis) 處理,通通會變成「廢紙」。

到底,如何挑選合適的數據分析公司? 首要條件,是要熟悉業務,第二是懂得選擇數據,問對的問題。或者筆者先向大家分享一些真實案例。

 

數據分析

 

錯誤數據引致錯誤的結果

 

外國曾有一家保險機構想要調查人們的生活習慣如何影響他們對於退休方案的喜好。由於「習慣」、行為有太多種,執行這個調查的管理層便把問題收窄到抽菸/不抽菸。進行了大規模的市場調查後,依然失敗了,他們無法得出抽菸與退休方案的關聯性。

後來管理層與醫療業界、行為心理學家、社會人類學家等等會面,把問題的方式改變了。他們發現,這種非黑即白的問題(抽不抽菸)難以得出答案,於是將問題更改至「你抽菸幾年了?」、「你戒菸幾次了?」、「你最後一次吸菸是什麼時候?」。最後成功得出準確的數據,幫助保險機構推廣更合適的退休方案。

 

數據分析

 

再舉另一個例子,第二次世界大戰期間,一群科學家提出可憑戰機身上的彈孔數據分析來增強戰機和機師的安全。透過將所有完成任務回來的飛機進行彈孔數據收集、位置記錄及統計,一份一份的數據分析、詳細報告就隨即誕生。

科學家和軍方圍著數據討論,各抒己見。有人主張應該鞏固戰機受到攻擊密度最強的位置,也有人提議該從油箱和駕駛員所坐的位置著手改善戰機的設計。大家都在引用著數據來激烈討論。在大家彼此爭論不休的時候,有一個人緩緩的站起來說:「這些數據都沒有參考價值!」

「這些能夠安全飛回來停在停機坪等待維修的戰機,正說明了在它們機身上的彈孔落點都不是致命的,真正致命的彈孔數據已經隨著被打下的飛機沉在大海裡了!」

説這個故事的作者陳傑豪認為,這個故事的教訓是要「問對問題,才能找到答案」。

 

 

數據分析-需要熟悉業務

 

在選擇數據分析公司時,可能會考慮幾個因素,例如對數據處理的技術、後台的功能、分析結果展示等。數據處理的技術,每家數據公司大同小異,但不代表每家都對你的業務、行情、具備專業及前瞻性。其實最重要,是要考慮該數據公司對於業務的熟悉程度。

若果對業務不了解,即使數據分析的技術多先進,都可能對於你的推廣無幫助。在以上保險公司的例子中,管理層最終與行為心理學家、社會人類學家等等會面並參考了他們的意見。這些專家共通點便是了解人類的行為習慣與思想之間的影響,並且擅長找出當中的關聯。他們清楚單純調查抽不抽菸這種非黑即白的問題並不能充份反映受訪者對抽菸的依賴、上癮程度。於是著手改變調查分析的方向,幫助保險公司獲得有用的數據。

企業選擇數據分析服務時, 需要的不是數據的精準,因為這不單純是數學統計的問題,更是市場推廣領域的問題。所以合適的數據分析公司,必須以Marketing角度出發,審視數據的採集、儲存、管理、分析和展現。要代入角色考慮如何處理數據才能貼身地幫助企業改善他們的市場策略,達到增加營銷的效果。

由此可見,進行數據分析時,應該找到熟悉業務的人士。

 

 

選擇正確的數據,問對的問題

 

正確收集和管理數據會對公司的業務模式產生正面影響。

大數據顛覆了過往玩行銷的方向,企業可以預測數據,達至精準行銷(Precision Marketing),不再單憑經驗靠估,就可以精確瞄準客戶的需求。不過,數據分析的重點不是在統計、分別數據,而是懂得問對的問題。然後,再找相符合的資料來分析,為客戶提供可實際可實行的解決方案。

企業在推廣自己的業務時都會產生海量的數據。但當中很多可能是無效、虛假或者毫不相干的數據。除了以上飛機彈孔作例子外,更生活化的有Facebook和Instagram。他們掌握的數據量是天文數字,但同時有很多因素影響他們數據分析的準確性,例如假帳戶。Instagram 上面有不少的虛假帳戶,提供大量假的讚好和追蹤服務。用戶可以向這些虛假帳戶供應商購買FOLLOWERS、貼文等等捧紅自己的產品。這類形虛假帳戶、讚好等產生不準確的數據,除了影響用家使用體驗,亦影響Instagram的廣告生態系統,以及數據分析。

Instagram公佈他們已經設立了採用機器學習技術的辨識AI工具,可以偵測出帳號內的虛假追蹤、讚好和留言,並自動移除。新工具旨在刪除錯誤的數據,確保數據分析的準確性,達至更好的市場策略。

因此,懂得篩選數據才能更有效率地對症下藥,呈現更精準合適的分析報告,協助企業制訂更進步的市場推廣。

 

總的來說,手持大量客戶數據的你,不要白白浪費這些寶貴的資源! 馬上尋找合適的數據分析公司幫你將數據化為黃金吧! 記得要鎖定熟悉MARKETING業務的分析公司,問對的問題,才能事半功倍。

 

 

 

 

其他大數據銷售故事:

 

客戶關係管理系統,有錢派,不如投資CRM

數碼營銷, 先行者星巴克

大數據銷售-比顧客自己更了解顧客(下)

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?

How CRM System helps to be a Giant in Online Retailer?

The future of retail and service industry bound to CRM Big Data. The profit is promising. However, it requires a custom and automatic CRM system to carry out marketing activities.

The Taiwan Non-Store Retailer Association held a “Non-Store Industry” forum.  The former executive Dean Zhang Shanzheng said that the future of the retail industry rely on big data and artificial intelligence. CRM Big data understand the preferences and interests of customers, which is the key to success.

Let me share the experience of Amazon.

CRM system

 

 

One-Click Buying, First Step of Managing Big Data

 

 

One-click buying is the technique of allowing customers to make purchases with the previously saved payment information. It does not require the shopping cart software. Users have no need to input billing information such as address every time. Instead, users can purchase with the predefined credit card and delivery address. This is quite simple and common these days, but the concept was not popular back in 20 centuries.

The technique was introduced in late 20 centuries. Amazon applied for the patent of one-click buying in 1999. Apple purchased the license from Amazon in 2006. The patent was finally expired in 2017.

Amazon.com is guidance in collecting, storing, processing and analyzing personal information from every customer. The One-Click Buying allows Amazon saving a large amount of customer’s data and purchase history. They analyze the data to capture the customers’ profile.

They use predictive CRM system for targeted marketing to increase customer satisfaction and customer loyalty. Big Data is being adopted in the CRM system, which helps Amazon evolve into a leader among online retail stores.

 

 

The Features of CRM System

 

 

Recommendation

 

Amazon developed a CRM system which included a personalized recommendation system. The system analyses purchase history, wish list, reviewed, rated list and search history. The purpose of the system is to recommend other products, which mostly related or interested the customers.

For example, if you add a DVD movie to your online shopping cart, other DVD movies will also be recommended. This feature generates 35% of the company’s sales annually.

 

 

Anticipatory Model

 

Amazon added a new module to their CRM system. Amazon’s anticipatory shipping model use big data for predicting customer’s most interesting products. It predicts the revisit time and when the customers might need the products. Those products delivered to a local distribution center and warehouse, therefore, they would be ready for shipping. It increases Amazon’s profit while decreasing its delivery time.

 

 

Price Optimization Module

 

The module monitors user’s activity on websites, competitors’ pricing, order history, expected profit margin and etc. Prices are set according to the above factors. Prices change every 10 minutes as big data is updated and analyzed. As a result, Amazon offers the best competing discounts on their hero products.

 

 

Remember, One-Click Buying and the CRM Big Data concept introduced in the ’90s. It is 2018 now and if you did not invest in the CRM system, you should better get on with it ASAP!

 

 

Other articles:

 

How Big Data Change Journalism?

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?

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?