VRM Research opportunities

From Project VRM
Revision as of 16:06, 9 December 2009 by Khopper (talk | contribs) (Moving meeting notes to a new page)
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Project Overview

Objectives

Our primary goal is to test one or more basic VRM principles (e.g. benefits of vendor openness, willingness of users to pay for perceived value in the absence of existing payment mechanisms provided by the seller). Results of research efforts will guide the expression of VRM principles, and, presumably, drive their adoption.

Additional benefits include bringing together passionate participants around a research project, demonstrating and furthering Berkman research methodologies an dsoftware -- and forcing some clarity and learning around testable characteristics of VRM.

Testable Principles

Generally speaking, VRM's vision is equip individuals with tools that make them independent leaders and not just captive followers in their relationships with vendors and other parties on the supply side of markets. VRM is successful when customers see direct benefits from taking control of their relationships, and vendors see alternatives to customer lock-in for gaining loyalty and generating profit.

This vision makes several assumptions. Primarily, that a free customer is more valuable than a captive one. Testing this hypothesis (or more accurately, specific versions and aspects of this hypothesis) should be our primary goal. This hypothesis begs at least two important questions:

What characterizes a free customer?

  • Able to choose how to relate to a vendor
    • Customer relies on tools and data under their control to relate to and manage vendors
    • Choose what information to share and when
    • Choose how this information can be used (i.e. under what terms), for example:
      • Customer-generated data must be portable
      • Customer-supplied data must be retractable
      • Customer-supplied data can't be used for targeted advertising / marketing messages
      • etc.
    • Customer receives a copy of data that is provided or generated as part of doing business, e.g. transaction data
    • Full disclosure on how customer supplied-data is being used (privacy policy)
    • Options for terminating relationship at will and without penalty

What are the potential benefits to a vendor for freeing a customer?

  • Decreased cost/hassle of gathering, storing, and managing customer data where the customer is relying on their own tools
  • Increased attention / visibility to vendor for being open, i.e. being the open alternative in the market
  • Increased participation from customers wanting to engage with open businesses
    • Both initial willingness and ongoing enagement
  • Increased sharing / customer WOM around open products / services
  • Increased volume and quality of customer-supplied data
  • Decreased guesswork by the vendor if the customer is telling them exactly what the want when they want it - or at least more/better information about themselves
  • Increased customer trust / loyalty / goodwill (longer term?)
  • Increased external innovation and value being generated around vendor services / data
    • e.g. if a vendor opens their transaction data, a 3rd-party service might help customers better manage their electronic receipts,
  • Development of an ecosystem of value around vendor services, creating the open version of customer lock-in
    • e.g. Good services based on open transaction data encourage continued use of open transaction data provider

Open Questions

  • Similarity to "free culture" arguments, e.g. what are the benefits to CC Licensing. Prior research already done here?
  • What aspects of the benefits above are perceptual vs. technical? How might we measure and test these?

Specific Research Proposals

Present users with different web-based scenarios that test specific aspects of the hypothesis that a free customer is worth more than a captive one. Use mechanical Turk and internally developed web and measurement software tools for completing web-based, personal data-gathering scenarios - Doc Searls and Keith Hopper with help from Aaron Shaw, Jason Callina, Joe Andrieu, and Tim Hwang.

Scenario 1

  • A proposed web-based scenario begins by asking users to provide or produce meaningful personal data (e.g. music preferences, audio listening history, etc.). Each scenario represents three differing degrees of personal control over the experience and the data. At the end of each process, the user is presented with various options for sharing the data, using the data (for example, to deploy against a music recommendation API) and various commercial activities (e.g. music downloads).
  • The specific hypotheses to be tested will be whether an individual is more willing to complete the data gathering effort and subsequently to engage with the system and with vendors if they have more personal control / autonomy over the data and experience
  • Upon completion of a scenario, users will be receive a small amount of money (or free music download) in exchange for their effort.

Scenario 2

  • Assign users to either the role of Vendor or Customer and pair them up. Customers gather music listening preferences and habits about themselves through either a user-driven, open tool and process or through a vendor-driven, choice-free process.
  • The results of these processes are shared with their vendor partners who are asked to make a music download recommendation to their customer based on the information shared. The vendor receives a larger reward if the customer selects their recommended download over a (smaller) cash prize.
  • This scenario goes beyond demonstrating increased sharing to test the idea that openness has the potential to generate less guesswork and increased sales for the vendor

Scenario 3

  • Require AMT participants to use Eyebrowse software to collect browser history data.
  • Create two scenarios - one that puts the user in charge of sharing what/how/to whom and another where the data is uploaded to a commercial vendor as part of the HIT.
  • Measure willingness of participants to complete the task and subsequently to upload their data for the two scenarios

Project Status

  • Meeting with geeks on 10/29 produced some rough research directions and commitment from Berkman staffers to helping execute
  • Additional meetings (11/2, 11/3) with Keith Hopper and Jason Callina and Keith Hopper and Tim Hwang to discuss possible scenarios and where to seek additional advice/support
  • There are clear benefits to producing research not only for the VRM community but also for the business community. Both Zeo and Personal Black Box (interestingly, both startup orgs) have expressed a strong interest in research that helps clarify and "prove" the benefits of vendors opening up control to the user.
  • Specific research proposal is shaping up involving the use of Amazon Mechanical Turk and based on code and data acquisition mechanisms already constructed and tested by Berkman staff for other research projects (cooperation project). See Specific Research Proposals.

Sources/Background

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