社交媒体时代下的客户分析

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"《Customer Analytics in the Age of Social Media》是TDWI在2012年第三季度发布的一份研究报告，由David Stodder撰写。该报告深入探讨了社交媒体时代下的客户分析实践，旨在帮助企业理解如何在社交环境中运用分析技术来提升客户洞察力和营销效果。报告强调了客户分析在当今社会媒体环境中的重要性，以及实施过程中可能面临的挑战和收益。" 报告首先介绍了研究方法和受访者群体的基本情况，确保了研究结果的可靠性和代表性。接着，执行总结部分概述了客户分析如何与社交媒体的前沿趋势相结合，揭示了企业在这一新领域中面临的机遇和挑战。在"Customer Analytics and the Social Media Frontier"章节，报告详细阐述了企业如何进入社交媒体时代。它指出，社交媒体产生的大量数据为深入理解顾客行为和需求提供了前所未有的机会。同时，随着社交媒体的普及，客户的声音变得更加响亮，这要求企业必须快速适应并有效响应。 "Importance of Customer Analytics"章节强调了客户分析对于现代企业的重要性。通过客户分析，企业可以实现更精准的市场定位，提高客户满意度，增强客户忠诚度，并最终提升盈利能力。此外，客户分析还能帮助企业识别潜在风险，提前预防客户流失。报告还讨论了实施客户分析所带来的商业益处以及实施过程中的障碍。在"Benefits and Barriers to Implementation"部分，列举了企业寻求通过客户分析实现的目标，如提高营销投资回报率（ROI），以及在采纳客户分析时遇到的困难，如数据质量和整合问题、技术能力限制等。在"Analytics Tools, Data Sources, and Techniques"章节，报告详细介绍了用于客户分析的各种工具，如商业智能（BI）、在线分析处理（OLAP）和数据发现技术。此外，报告还提到了内存计算在提升分析速度和效率方面的作用，使得实时或近实时的客户洞察成为可能。《Customer Analytics in the Age of Social Media》提供了一个全面的视角，指导企业在社交时代如何利用分析工具和技术来优化客户关系管理，提升业务表现。报告的深度和广度为读者提供了丰富的知识，有助于企业在竞争激烈的市场环境中取得竞争优势。

tdwi.org 7

Customer Analytics and the Social Media Frontier

The Importance of Customer Analytics

Before delving further into specic areas of customer analytics and social media’s impact, we can

consider some context-setting results from TDWI’s research about the general importance of

customer analytics technologies and methods (Figure 1). Not surprisingly, we found that the business

functions or operations for which respondents considered customer analytics most important were

marketing (81%, with 52% indicating “very important”), sales and sales reporting (79%, with 45%

“very important”), and campaign management (74%, with 47% “very important”). Market research

(43% “very important”) and customer service and order management (also 43% “very important”)

were also high among business functions regarded as critical to developers and consumers of

customer analytics.

How important is it for your organization to implement customer analytics technologies and methods to

benet the following business functions or operations?

Marketing

52% 29% 7% 7% 5%

Campaign management

47% 27% 10% 9% 7%

Sales/sales reporting

45% 34% 8% 8% 5%

Market research

43% 36% 9% 7% 5%

Customer service/order management

43% 31% 10% 11% 5%

Executive management

40% 32% 14% 8% 6%

Advertising

39% 26% 12% 18% 5%

Fraud/risk management

39% 24% 16% 13% 8%

Finance

38% 29% 16% 11% 6%

Product development

33% 32% 14% 14% 7%

Call/contact center

33% 29% 12% 18% 8%

Operations management/research

32% 36% 15% 11% 6%

Web storefront/online presence

32% 30% 14% 16% 8%

New media/social media department

31% 31% 17% 13% 8%

Regulatory compliance/data

governance

29% 33% 15% 15% 8%

Public relations

26% 32% 20% 14% 8%

Distribution, fulllment, or logistics

25% 27% 16% 23% 9%

Supply chain

20% 21% 22% 26% 11%

Event management

14% 35% 23% 18% 10%

Procurement

13% 23% 28% 24% 12%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Very important Somewhat important Somewhat unimportant

Not important Don’t know

Figure 1. Based on one answer per business function from 452 respondents.

The business functions

or operations for which

respondents considered

customer analytics

most important were

marketing, sales and

sales reporting, and

campaign management.

8 TDWI RESEARCH

Customer AnAlytiCs in the Age of soCiAl mediA

e marketing function, which in most organizations is empowered with the responsibility for

identifying, attracting, satisfying, and keeping customers, is clearly the main stage for customer

analytics. Marketing functions are becoming increasingly quantitative; they are replacing “gut feel”

with data-driven decision making. Data drives the pursuit of eciency and the achievement of

measurable results. Marketing functions are key supporters of “data science,” which is the use of

scientic methods on data to develop hypotheses and models and apply iterative, test-and-learn

strategies to marketing campaigns and related initiatives.

e research shows that sales functions can be important beneciaries of customer analytics. Sales

reports typically focus on providing visibility into the pipeline. Managers can use data insights to

improve sales forecasting of potential revenues based on deeper knowledge of priority opportunities,

most valued customer segments, and more. e oce of nance can also benet from more

sophisticated analytics in sales reports. C-level and nance executives typically consume sales

reports; 67% of respondents said that customer analytics was important for the nance function

(with 38% indicating “very important”). (See Figure 1, previous page.)

Customer service and order management can use customer analytics to get a more subtle and

substantial view of what actions most impact customer experiences and satisfaction. Contact centers

can use customer analytics to help tune performance metrics closer to real time, so that each day’s

agents are guided, if not incentivized, to interact with customers in benecial ways. In addition,

analytics can help service and order management functions move away from one-size-ts-all

approaches to customers and instead tune and tailor interactions more personally based on

knowledge of particular types or segments, such as regions or nationalities. Finally, through

integrated views of customer data and analytics, service and order management functions are able to

work in better synchronicity with the organization’s marketing, sales, and other business functions.

Customer Analytics Budgets and IT Control

TDWI Research found that IT and data management (59%) are the most common owners of the

budget for customer analytics technologies and services (see Figure 2; respondents could select

multiple answers). is reects the central role played by BI and data warehousing systems, which

are often managed by IT. (We will examine research about BI and data warehousing for customer

analytics more extensively later in this report.) In interviews, TDWI did discover a growing budget

role played by marketing and advertising functions. Nearly two out of ve (38%) respondents

said that this function has responsibility for the customer analytics budget in their organizations.

Executive management (39%) is also a signicant player in budgetary decisions.

In your organization, which of the following functions is responsible for the customer analytics

technologies and services budget? (Please select all that apply.)

IT and data management

59%

Executive management

39%

Marketing/advertising functions

38%

Sales functions

20%

Cross-functional team responsibility

18%

Customer/eld service functions

16%

Other LOB or operations management

12%

Call/customer center

10%

New media/social media functions

Figure 2. Based on 992 responses from 448 respondents; a little more than two responses per respondent, on average.

Marketing functions

are key supporters of

“data science,” which

is the use of scientific

methods on data to

develop hypotheses

and models.

Analytics can help

service and order

management functions

move away from one-

size-fits-all approaches.

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