Is a Picture Truly Worth a Thousand Words?

Antique typewriter and vintage photo cameraWe all know, and for the most part believe, that attitudinal data is crucial to the process of understanding our customers (and prospects) and speaking to them in a language they can understand. Behavioral data is important to the picture, otherwise “Big Data” would be pointless, but there are almost always attitudes driving those behaviors. On December 9th Susan Baier, President of Audience Audit, spoke on behalf of Tableau regarding the best ways to incorporate attitudinal data into marketing strategy.

Susan presented first two of the most common methods for segmentation – demographic (what people look like) and behavioral (what people do). Demographics are well known and may also include similar variables such as geographic measures. These are easily found and appended to data sets. Behavioral measures include items such as how frequently they purchase, when was their last purchase, how much time do they spend on your web page, did they respond to the most recent email, how they engage you in social media, etc.

Attitudinal information comes in and answers the question of why a consumer or prospect is doing something (e.g. buying less frequently, spending more per purchase, why they chose you versus a competitor, etc.)  Behavioral data gets to what the person is doing, but not why they are taking those actions whereas demographics can easily obscure the picture.

The case study presented was for Tufts University and spoke to why alumni stay connected with the university. The marketing goal was to better understand this connection and to develop ways to deepen it. Over 1200 alumni responded to the survey. From which four segments arose from the attitudinal differences. Segment size ranged from 23% for the Fans and Advisors segments; 24% for Volunteers and 30% for Networkers. Key differences in attitudes can be seen in the table below.

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The presenter utilized Tableau’s visualization features to present her story as opposed to creating a PowerPoint deck. The chart below is an example of how the Fans segment feels about future donations to the university relative to members of other segments.

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The challenge of using attitudinal data is there is typically no direct key that can be used to flag consumers or prospects in a database. Often, as in the case with Tufts, marketers determined they wanted to create an event that appealed to a certain segment. The event was designed to appeal to the Advisors segment. Messaging and event content were based on the motivations captured in the segmentation study. If events or other marketing activities can be created and delivered then we can begin to flag participants on the basis of their actions (e.g. did they respond or attend?) This process helps merge the attitudes with the behaviors.

As a key takeaway, attitudinal data is one component to understanding the market. It can be used to help develop and refine audience strategy (acquisition vs. retention), targeted messaging, create relevant and focused content, as well as inform other actions such as website development and customer service.

Greg Timpany directs the research efforts for Global Knowledge in Cary, North Carolina, and runs Anova Market Research. You can follow him on Twitter @DataDudeGreg.

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