In the article “Every Business is a Digital Business”, the Accenture Technology Vision 2013 identifies seven technology trends that are shaping business in the near future. Three of the trends Accenture identified are related to the accessibility and quantity of customer data, which are essential for analytics managers like you to understand and utilize. First, “Relationship at scale”. Rather than “faceless digital transactions or a cookie file”, customers are real people with real differences. This brings to you as a marketer the new responsibility to utilize available date, redesign your relationship with your customers and improve their experiences. The second technology trend progresses with "Data Velocity". It is “the pace at which data can be gathered, sorted and analyzed in order to produce insights that managers can act on quickly.” Needless to say, matching the speed of decisions to that of actions comes to be the key for marketers to win their market. Third, “Design for Analytics”. Accenture argues that despite several relevant functions from the currently available software, the next generation of software will be “designed for analytics” in the first place, giving you the option to outsource real-time analytics while performing customer segmentation analysis internally.
Evaluate your data's worthiness
With possibilities derived from huge data quantity, two important questions should be raised. Does your company have valuable data? What is the right business model to extract value from worthy data? In the article “What’s your data worth?” , Accenture Interactive Research and Finding provides us useful metrics to understand data. First of all, the data your organization has should have the following characters to be consider valuable: reflecting consumer behavior, customer identification, transaction frequency and being accessible. After ascertaining the value of your data, the next step is to monetize the data through the process of data value chain. In this process, you need to refine the raw data into processed data, to interpret the processed data into insights, to profile the insightful segments into presentations and to use the presentations to adjust actual transaction.
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