PATTERN 5: CROWD BEHAVIOURAL INSIGHTS Description

This pattern creates, delivers and captures value for a crowd that is created by behavioural insights of the same crowd by using advanced technologies that support the data process regarding this crowd data.

106 Case studies  Facebook;  TomTom Traffic;  Waze. Context

 Every individual has and create own insights. The crowd can drive the value creation process for the crowd when these insights are combined and shared (automatically);  Thereupon, the crowd gets better products/services or insights in situations.

Problem

 Service providers want to improve the value that they create for the crowd of customers but they do not know how this is possible;

 Thereby, undesirable products/services or situations may arise which harms customer satisfaction and customer retention.

Example

Traffic congestions arise mainly when there are too many people who want to drive on the same road at the same time. Traffic congestions are seen as a problem and have impact on the value that is created for individuals, who want to spend their spare time in different ways, and business, who lose money when cars are stuck in traffic. The problem is that individuals do not have insights in the behaviour of others. TomTom Traffic and Waze show that crowd behavioural insights create value when the same crowd have real-time insight in these complex (and perishable) situations (traffic congestions) that are caused by the crowd.

Solution

 (Behavioural) insights need to be shared. Therefore, (advanced technologies that generate) (behavioural) insights are required. Technologies (mainly apps and/or devices) should generate and analyse user data (just as the previous patterns);

 Aggregation and processing data is important in this data process, because aggregated data of the crowd will be analysed to gather useful insights. Therefore, aggregation is depicted in line with the other activities;

Classification

 Data source: Behaviour;  Target of value: Crowd.

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 Service providers share real-time insights with the crowd. Thereby, value is real-time delivered to the crowd that provides the behavioural insights and drives the value (closed loop);

 The network effects stimulate the crowd to provide data and increase the real-time created value.

Figure 46: Crowd behavioural insights

Example

Users of Waze provide real-time insights regarding traffic conditions using technologies (the Waze app). The Waze app and related technologies generate and analyse real-time insights (traffic information) from the crowd. By analysing input from these crowd behavioural insights, Waze know traffic conditions regarding congestions or accidents. Thereafter, these real-time insights are shared through the Waze app.

Consequences

Results

Main results (value) are shown in the value proposition of Figure 46.

 Individuals and service providers gain insights (and value) regarding certain products and situations that is based on crowd input;

 Products/services/situations may be improved. This increases the user-experience. As a result, customer satisfaction and customer retention improves.

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Trade-offs

 This business model pattern entails the same trade-offs as the previous patterns regarding investment costs, development, implementation, maintenance and further development of the technologies. Besides, the privacy of individuals and data entails another trade-off;

 Service providers should investigate the benefits and possibilities to generate and analyse crowd behavioural insights. It is also important to think about the technological possibilities and the willingness of individuals to support the solution.

Known uses

 Facebook deviates from the TomTom Traffic and Waze case, since their technologies focus more on real-time acquistion, distribution and visualisation of content (insights) that is shared by the Facebook community;

 Facebook aggregates data to analyse crowd insights. Based on these insights, marketers can do targeted reach. Therefore, other social media platforms such as Twitter and Foursquare are known uses;

 PatientsLikeMe is a patient research network. Individuals connect with and support others who have the same disease or condition and track and share their experiences. Thereby, crowd insights will result in value for individuals. In addition, the organisation sells these insights to other organisations, such as pharmaceutic companies. Thereupon, these organisations may improve their products/services. As noted earlier, the real-time element is not that important in this example;

 Quirky is a place for ‘social product development.’ An individual submits an idea. Other individuals (the crowd) vote on all of the submitted ideas and can contribute to the development of the product (product name, design and concepts);

 Adam is a free app that analyses and provide real-time traffic information for commuter traffic around Amsterdam. Information and behaviour is analysed continuously. For example, when too many follow a certain advice, the advice is adjusted to this new situation;

 The gamification element of the Quby Smart Thermostat: crowd behavioural insights may drive the value creation process, because individuals can compare their behaviour regarding energy usage with other users. The crowd is not a key resource for Quby, since the gamification elements is an extra feature and not the core of the product (provide insights in and control over energy use);

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 E-commerce organisations such as Bol.com. These organisations generate and analyse crowd behavioural insights to adjust offerings to individuals to improve value for individuals and their organisation. As noted earlier, there are a lot of online shops who do this.

Variants

This pattern contains two variants, because, based on the crowd behavioural insights, behaviour of the crowd of TomTom Traffic and Waze users is stimulated to drive better routes. Therefore, crowd behavioural stimulation could be a variant, but this is not applicable in the Facebook case where aggregated crowd behavioural insights are used in the value proposition to offer targeted reach.

6.10. PATTERN 6: REAL-TIME MATCHING