Understanding your market: 7 elements of customer and social data

Customer-Data

Jeremiah Owyang and his colleagues at Altimeter Group continue to push the boundries of the social internet by helping us to better understand people’s behaviours and how brands might tap into this.

He’s very generously published a summary of the research on how to harness new data types from online experiences. The research included ‘tried and true’ data as the top tier: demographics and product. Then, Jeremiah segmented the data that digital marketers are now very keen to understand in the middle tier: psychographic, behavioural and referral data. At the bottom tier is the experimental new types of data that is rarely harnessed, location-based and intention data. Here’s how it looks:

Demographic data enables an efficient way to create context about consumers, yet broad survey-based research may not yield specific nuances and needs about specific individual taste as today’s consumers are given more choices and have more discrete needs.

Product data is commonly used in ecommerce websites to match similar products with each other to cross-sell and up-sell products. Often combined with demographic data this data type, mixed with referral and behavioural data yields greater accuracy.

Psychographic data is derived from consumers who are voluntarily self-expressing their woes, pains, and aspirations on websites and provide increased opportunity to market products and services based on lifestyle and pain points.

Behavioral data is available in existing customer records like CRM or ecommerce systems or also in the ‘digital breadcrumbs’ that users leave in social networks using a variety of web techniques from cookies, FB connect, and other social sign on technologies.

Referral data includes when customers emit their recommendations for products through ratings and reviews, as well as imply sentiment though gestures like the ‘like’ button in social networks.

Location data emerges when consumers emit signals where they are using mobile devices. This data helps to triangulate context around location and time for brands to reach them.

Intention data is the most inaccurate. This volatile data type holds great opportunity to predict what consumers will do in the future.

To find out more watch this one-hour webinar by Jeremiah Owyang of the Altimer Group.

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Sherrilynne Starkie is a consultant at PDMS. For almost 18 years, Sherrilynne has been advising blue-chip organisations on both sides of the pond, covering Britain, Canada and the United States. For three years, Sherrilynne was the Tech Talk columnist for the Isle of Man newspapers. She serves on the steering committee for Isle of Man Women in Business, is on the Executive Council for the Isle of Man Junior Chamber of Commerce. In the past she was on the management committee for the Isle of Man British Computer Society and the marketing committee of Junior Achievement.