社會的飛速發展給許多行業帶來了新的機遇，這些行業越來越趨向依靠大數據的分析做出決策。那么如何利用分析學工具解決 數據發掘 問題，并且促進行業增長呢？我們從以下幾個主要行業進行分析。

保險業

以前的保險公司是依靠人工進行數據采樣的，除此以外，他們還要分析客戶群體并處理運行中出現的各種問題。這一過程不僅費時費錢，也容易出現錯誤。

人工分析依靠的是歷史數據，不可能對實時情況做出反應，這意味著人工分析無法避免類似于詐騙這樣的威脅，因為這類威脅都是事情發生后才能發現問題。

據英國保險業協會估計，每年未被發現的詐騙金額高達19億英鎊（約22億歐元，合163億人民幣），由此導致投保人每人每年要多花費50英鎊保費。根據2015年保險詐騙調查報告顯示，詐騙集中在意外保險（31%）和保險申請（12%）這兩個方面。

現在保險公司可以運用更加先進的分析學工具來避免這些威脅。通過分析學工具，英國的某汽車保險公司幫助每名投保人節約了2英鎊的資金。瑞士的某保險公司把不合規的相關風險降低到1%以下。

保險業運用分析學工具的好處：

• 風險定價更準確；
• 可以更好地比對花費與定價，來發現和維系客戶；
• 減少索賠中的失誤；
• 節約索賠決策時間；
• 通過分析不同的網絡平臺數據以減少詐騙的發生；
• 減少由失誤、不良債權、訴訟和客戶流失導致的成本費用，以獲得更高利潤，提高客戶滿意度。

銀行業

金融機構使用 數據分析 工具的動機其實各不相同，互聯網數據中心（IDC）公布的一份調查結果向我們展示了這其中的區別。

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但是不論他們的動機如何，對銀行業來說分析學工具的優勢是顯而易見的。 “美國銀行家研究”機構（American Banker Research）對170名銀行家進行了調查。其中28%的人認為顧客份額是機構獲得的最大收益，18%的人則認為貸款虧損的減少是最關鍵的收益。

譯者注：顧客份額是一個企業為某一顧客所提供的產品和服務在該顧客同類產品和服務消費總支出中所占的百分比。

很多銀行表示，最大程度地利用網上資源有益于維持客戶忠誠度。下圖展示了一家歐洲銀行依靠分析學工具，使得廣告點擊率提高了27%，銷售額提高了12%。

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醫療業

近年來醫療領域出現了很多新變化，列舉其中幾個：

• 醫療業越來越趨向于價值導向，因為客戶對高質量的服務要求越來越高；
• 外科醫生和護士數量不足，這要求醫院設法提高員工的工作效率；
• 成本發生變化，因為死亡率降低了，慢性病例數量增多；
• 醫學研究獲得了更多的投資，因此新的藥物和療法不斷被發現。

這些變化增加了醫保提供者面臨情況的復雜性。運用客戶導向分析工具，醫保提供者能夠輕易地實現以下功能：

• 發現疾病類型，防止疾病爆發，并快速對醫療緊急事故做出反應；
• 跟蹤預防性治療，比如可以看到數據庫中有多少人接種過流感疫苗；
• 高效地分配有限的員工資源；
• 通過客戶在醫院網站的瀏覽歷史，預測他們的需求和病情；
• 減少浪費，麥肯錫咨詢公司（McKinsey）預計，每年在臨床治療、研發和公共健康上，美國醫療行業能夠節省3000多億美元。

教育行業

教育行業擁有很多數據來源，比如：

• 錄取記錄（通常包含了社會經濟數據、人口數據、歷史表現和健康情況數據等）；
• 實驗室情況，圖書館、咖啡廳和一般消費記錄；
• 出勤率、考試分數和評分等級情況；
• 體育運動記錄。

但是，這些數據很難用于提高教育環境和預測學生需求。

亞利桑那州立大學率先運用分析學，提升了用戶體驗。該網站國際頁面收集的數據顯示，網站訪問量來自世界各地，這促使學校在網頁上提供了不同的語言選項。

電子商務

幾百萬個網站都爭先恐后地向同樣的客戶群體推銷商品，在這種情況下，如果不使用數據分析工具，商家就很難把握面臨的銷售環境和客戶情況。

電子商務企業有很多標準來衡量網絡性能，其中“轉換能力”是衡量性能的最關鍵的指標（KPI）。對于那些轉換能力不高的網站可以進行深度挖掘，發現背后的原因。很多優秀的網站分析工具都可以做到這一點，這里列舉了一部分網站分析工具：

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Wappalyzer整理出來的這份表格顯示，大部分網站都使用網站分析工具，如woocommerce.com 使用KISSmetrics，shutterstock.com使用crazy egg，app.hubstaff.com使用 woopra。

政府

盡管政府在產能和信息通訊技術上占主導地位，他們也在盡職盡責地投資開發報表工具、計算機設備和數據庫，但是在數據收集和定性分析上政府依然面臨著困難。

我們不僅要運用分析學工具發掘數據，也要使用分析學工具提高分析質量以解決問題。我們從數據中發掘的價值越多，就越能利用數據提高市民的生活質量。

以美國政府網站為例，政府部門能夠看到一定時間內，訪問其網站的人數、訪問的內容以及下載的文件。這些數據清楚地顯示了人們所需要的政府服務。

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結論

文中列舉的事例，展示了分析學工具的益處。這說明任何產業的發展契機，都依賴于其數據分析的能力。市場上已經出現了很多性價比很高的分析工具，操作上也很簡便。這就意味著企業不需要復雜的數據收集和儲存基礎設施，就能夠輕松地使用他們的數據。

英文原文

How Analytics tools are shaping the growth story across industries

If there’s one thing that businesses across all industries have in common today, it’s in their increased adoption of data to shape business decisions. Below is a demonstration of how key industries use analytics tools and the benefits these tools have in solving challenges of data capture and use to shape growth.

Insurance

Traditionally, insurers have relied on manual sampling of data to understand their customer base and address challenges to their operations. Not only is this process time-consuming and costly, it is also highly prone to errors.

Manual analysis also relies on historical data, making it impossible to respond to changes that are happening in real-time. This means that threats such as fraud cannot be prevented, as they are only detectable after the fact.

The association of British insurers estimates the amount of annual undetected fraud at roughly ￡1.9bn (€2.2bn), a loss that costs policy holders an approximate cost increase of ￡50 on their yearly premiums. Some of the highest instances of fraud, according to the 2015 insurance fraud survey, are noted in staged accidents (31%) and applications (12%).

Insurers can protect themselves against such threats using better analytical insights. Below are two examples from Insurance Nexus of insurers who have benefited from use of claims analytics:

Annual savings of up to ￡2 in auto claims by a Uk insurer

A Swiss insurance company reduced risks associated with non-compliance to less than 1%

Benefits of analytics in underwriting:

Accuracy in risk pricing.

Identifying and retaining customers through better comparisons of costs and pricing.

Reductions of errors in claims.

Reduced decision making time where claims are concerned.

Reduced cases of fraud, through analysis of different web-based platforms.

Reduced costs associated with errors, bad claims, litigation and customer attrition, leading to more attractive margins and better customer satisfaction

Banking

Financial institutions differ in their motivations for investing in data analysis as shown in the survey results below conducted by IDC .

But whatever their motivations, the benefits of analytics in banking are clear. American Banker Research surveyed 170 bankers on the usage of customer analytics in banking. 28% of them cited share of wallet as the biggest benefit experienced by their institutions. Another 18% cited reduction in loan-related losses as the key benefit.

Banks also recognize the importance of making optimum use of their online resources to retain customer loyalty. As shown in the image below, a European bank experienced 27% increase in click-through rates for their banners and a sales increase of 12%, by relying on their analytics tools.

Healthcare

There are a lot of dynamics surrounding the field of healthcare. To mention, but a few:

Healthcare is becoming more value-based as customers continue to demand quality services.

Physicians and nurses are always in short supply which means that hospitals have to figure out how to be efficient and productive with the staff they have on hand.

Cost dynamics are changing, thanks to reduced death rates and more reported cases of chronic diseases.

More investment in research has led to new medical approaches and cures.

All these issues create a lot of complexity for health care providers. With more utilization of customer-based insights for decision making, healthcare providers will find it easier to:

Detect disease patterns, prevent outbreaks and respond to medical emergencies with speed.

Track implementation of preventive remedies. For instance, they can track how many people in their data base have received flu vaccines.

Efficient allocation of limited hospital staff.

Use customer browsing history on hospital websites to anticipate individual needs or crises.

Reduce wastage. Estimates by McKinsey show that U.S healthcare can reduce waste and save more than $300 billion annually in clinical operations, R&D and public health.

Education

Learning institutions have many data sources such as:

Admission/enrolment records, (which are usually a combination of socio-economic data, demographics, past performance, health issues, etcetera)

Laboratory, library, cafeteria and general purchase records,

Attendance, test scores and grade tracking,

Sports records.

However, this information is hardly used for improving the learning environment and to anticipate student needs.

Arizona state University is a good example of use of analytics by a learning institution to improve user experience.

Insights gathered from the website’s international page showed that most of the traffic to the website came from all over the world, a factor that prompted the university to offer the pages in different languages.

Ecommerce

Standing out among the millions of websites that are competing to sell to the same audience is near impossible without the use of data to help a business understand its environment and audience.

Though ecommerce businesses use many metrics to measure website performance, ‘conversion’ is the key KPI used to show the rate of success. A website that is experiencing low conversions can dig deeper to understand the reasons behind this performance. There are some amazing web analytics tools out there that you could choose from, here’s a list I’ve compiled about Web Analytics Tools which can prove to be handy.

Lists compiled by wappalyzer show that most key websites use web analytics tools. for instance, woocommerce.com uses KISSmetrics, shutterstock.com uses crazy egg and app.hubstaff.com uses woopra.

Government

Governments hold a central role in the ramping up and use of ICT and though they embrace this role fully by investing in reporting tools, computer equipment and data warehouses, there’s still a challenge when it comes to moving from mere data collection and processing to qualitative data analysis.

The use of tools to not only mine data but to improve analysis helps to address these challenges as the more value is extracted from data, the more it can be used to better the lives of citizens.

For instance, in the example below from the US government site, it’s possible for government departments to see how many people visit the website over a period of time, which pages they visit and the documents they download. This gives a clear indication of the services that people need most.

Conclusion

The body of evidence that shows benefits in increased investment in data tools suggests that opportunities for growth in any sector lie in data insights. The market has readily available analysis tools which are budget friendly and don’t require intensive training to operate, meaning that companies don’t need to roll out sophisticated data capture and warehousing infrastructure to start making use of their data.

注：本文摘自數據觀入駐自媒體—燈塔大數據，轉載請注明來源，微信搜索“數據觀”獲取更多大數據資訊。

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責任編輯：陳卓陽