With its $30,000 award from the INNovation Fund, the Midwest Center for Investigative Reporting set out to develop a database application bringing together information from several sources about agricultural companies and testing the “freemium” model for generating revenue by offering accessible data sets and related content.
Responses provided by Pamela Dempsey have been edited and condensed.
What was your organization trying to achieve?
Our goals with this project were to build a database application, The Risk Miner, that meshes information from several sources about big agribusiness companies and to test the freemium model for generating revenue by offering accessible data sets and related content.
What role did the INNovation Fund dollars play in the project?
The $35,000 grant via the INNovation fund paid for backend development, a portion of salaries dedicated to this project as well as front-end user development.
What were the key successes of the project?
Audience and Revenue Outcomes
RiskMiner is an 18-month project and we anticipate measurable results and revenue outcomes within six months of its release.
We anticipate initial release in April 2017 with measurable outcomes by October 2017. Further, we are finalizing a potential collaborator who will help with marketing, distribution and user testing.
Once built and released, we anticipate increasing our site traffic by 10 percent, increasing our newsletter traffic by 40 percent and securing 150 paid subscriptions. We expect our tool to add value to the discussion on big agribusiness.
Our user-end framework has been developed through a contractor, Pixo Tech, a tech company that spent months pre-grant guiding us through. We are in the process of merging our back-end database with the front-end framework.
RiskMiner is a tool that is meant to not only generate revenue and build a freemium model for other nonprofit newsrooms, but to also ferret out story tips that would feed into our goals of investigative and enterprise journalism of Big Ag.
As we have continued to research and develop this tool, we have uncovered story ledes. For example, one foreign Big Ag company – Bayer – posted a November 2016 interview with its head CEO from a German-based newspaper that descriptively discussed then President-elect Trump and the company’s pending merger with Monsanto as part of its required reporting to the U.S. Securities and Exchange Commission.
We plan to use this published interview in an upcoming story about this merger.
This epitomizes the goal of RiskMiner — uncovering and connecting valuable information in ways that may not be obvious to highlight risks that impact America’s food and fuel policies.
What were the critical success factors (ex: market types, internal capacity) that made this work?
We anticipate the following factors to make RiskMiner a success.
Sustainability: We are building the project to streamline any behind-the-scenes heavy lifting while continuing to offer content of value. Further, we are counting on paid subscribers to help offset the cost.
Audience: We anticipate that RiskMiner will net at least 150 subscribers in the first six months of its release. Its success will also depend on continued audience growth – a mix of free and paid accounts.
Content: RiskMiner is initially focused on Big Ag as that is the niche we cover. Success will include new and fresh content as we continue to develop this project.
Model: RiskMiner is meant to be adaptable and aims to be a revenue and content model for other newsrooms. We are developing our backend to allow other nonprofits to use it for their own needs. For example, a regional INN member might use RiskMiner’s framework to better cover their local government through city or county documents, election filings and correspondence.
What were the lessons learned?
While our grant proposal was for a solid 18 months of research, development and initial release, the project itself took at least a year of conceptualizing and discussion prior to our request for funds.
We worked with the Urbana, Illinois, tech company Pixo Tech who guided us through this process – even before signing on to develop a user interface.
This process was extremely important to take our idea from concept to tangible, and valuable to bring a diverse set of skills to the conversation.
Further, we learned to avoid the kitchen-sink approach. Not all datasets were adaptable or necessary for this project. While interesting, some datasets on Big Ag fell outside of the goals and focus of the project.
Finally, we had to clearly define what our initial release would look like. While we have plans to include visualizations and customizations based on topic-modeling for paid subscribers, we also wanted to release a solid tool that would gain and grow a dedicated audience. This meant we had to decide where to best spend our time for the first iteration. We anticipate that these decisions will avoid bugs in the tool while at the same time push us further to our end goal.
Do you plan to do this project again?
Yes. We see this as a continuing and growing project and eagerly anticipate its release so we can measure tangible results.
Would you recommend this revenue- or audience-building approach to other news organizations?
Yes, but with the understanding that it cannot be developed without long-term planning throughout and with a very specific focus.
What insight would you offer anyone using or thinking of trying a similar approach?
Decide what your end game looks like – what do you want to accomplish and what success looks like from the starting line.
Identify two to three datasets or data sources ahead of time – and don’t try the kitchen-sink approach.
Dive deep, not wide –. develop one or two strong features initially, versus developing five or six superficially.
Describe the market/community that you serve.
Our audience is a mix of researchers, advocates, trade and government sources and a growing general audience.
What was your organization’s revenue mix (i.e. sources and % )prior to the project? Did the revenue mix change as a result of the project?
Our revenue is primarily grant-funded (92 percent), earned revenue (7 percent) with some individual donations (1 percent). As a result of this project, we anticipate a mix of grant funding (85 percent), earned income (10 percent), and individual donations (5 percent).