멀티채널 분석 Metrics

인터넷 마케팅 채널이 확대되면서 다양한 채널을 통하여 유입되는 고객데이터를 분석하는데 어려움을 겪고 있다. 고객 유입채널의 다양화에 따른 "멀티채널"분석에 따른 사항들이 이슈가 되면서 데이터 분석에 관한 다양한 방법들이 제시되고있다.

특히 데이터분석 지표의 기준이 되는 KPI설계는 비즈니스 모델 및 고객 유입프로세스, 고객성향에 따라 구성되어야 한다.  

Effective KPIs should include the following:

• Definition—summarize relationships among meaningfully compared data. Also, clearly define which KPIs are provided to the end user, adding a glossary or annotation, if necessary
  
• Expectation—establish targets for improvement. Set expectations by providing context of change over time
  
• Presentation—highlight changes (literally) for easy identification. Each KPI should show a percent change and drive
• Action—Direct additional study and ID areas of the Web site that need work

After important data is gathered and organized, Web site owners should adjust their Web site content and marketing campaigns accordingly. "Also focus on customer life cycle management," said Mason.

Jason Burby, Director of Web Analytics/Business Intelligence at ZAAZ, looks at three types of core data about user behavior:

• Attitudinal data (what do my customers think)
• Behavioral data (what are my customers doing)
• Competitive data (how do we compare with others in our industry)

"Create scorecards to measure organization, Web site, site section, Web team/agency, and individual performance related to business goals," said Burby. "Share this scorecard throughout the organization. People should be held accountable—bonuses and sales can be based on KPIs."

관련기사:Multichannel Metrics: Managing the Sea of Data