Farm Journal is the leading media outlet for the agricultural and livestock industry, with over 140 years of proprietary data. However, without a client facing product their process for providing customers with their rich data sets was lagged.
The team was tasked with creating Farm Journal’s first ever data querying platform for internal and consumer use to help position them as the market leader in the industry.
Salvador Chavez, Fernando Diaz & Vanessa Fahy
Discovery & Analysis:
18 User Interviews, Comparative Analysis, Co-Creation Workshop, Experience Brief
Ideation and Synthesis:
Workflow Modeling, Info. Architecture, Wireframes, Query Builder Concepts (x 2)
Unique Screen Designs, Style Guide, Component Library
7 min read
Without a client facing product, Farm Journal's process for providing customers with rich data sets was done offline through sheets & tables only available to a handful of internal staff. Even a simple query had to be pulled by an in house data scientist, sent to a broker, then passed to their client, resulting in a 1-2 week average timeline.
Farm Journal wanted to create a client facing data segmentation & purchasing platform that would give their customers the ability to combine any of their 2.3 million demographic, brand & behavioral data points to create very specific & tailored lists.
Enable sales & accounts teams to be strategic partners to their clients by giving direct access to data
Reduce the timeframe for a simple data query to a matter of seconds
Create an MVP that sets the foundational functionality upon which programmatic buying and data appending will be built in 2020
Provide simple & intuitive ways for both clients and internal staff to parse the data in the multitude of unique ways needed by different users
Create an MVP experience for 3 prioritized epics- account creation & login, data querying & saving, and payment & activation
Create a platform that showcases the power of FJ’s data to clients, and allows them to explore the different, unexpected ways to query the data on their own
We kicked off the project with a series of 18 internal and customer interviews to better understand the needs & demands of the platform’s users.
We presented these findings to a group of 20 stakeholders during a 2 day co-creation workshop in Chicago.
We wrapped up the session with an MVP prioritization activity with the product owner to identify key features & functionality.
User Flow & Experience Map
Scope of Experience
We identified key areas that needed to be resolved. For e.g deciding on a revenue model, payment facilitation, and back end data structuring options. Over the course of the engagement we worked collaboratively with the client to tackle these hurdles providing guidance & ideas around the Customer Experience strategy as a whole.
As we gained a solid understanding of the ecosystem of the product we created an IA that centered around the key tasks and flows of the users.
Query Builder Logic
The data querying tool was the crux of the experience and the part that was most important to the success of the MVP launch. We designed a querying tool that allowed users flexibility over the magnitude of potential ways to splice Farm Journal’s data.
From Data Dinosaur to Digital Disruptor
We progressed into wireframes for the query builder to support the robust ways in which users could combine data points. We created a system for switching views between the query builder, syntax summary & report breakdown, as well as saving or activating a query.
The querying tool needed to be robust & functional for MVP launch and we based the foundations of our designs on traditional querying interaction models. However, given the business goals to disrupt the market and provide a place for users to explore the power of the data, we also explored a more intuitive solution that would solve some of the core usability challenges of the tool.
To communicate the potential of this tool to truly disrupt the market in future phases of work, we briefly explored a concept that allowed a user to jump in and explore the data more freely. The tool worked like a sandbox, allowing users to start multiple tasks at once instead of completing a long linear process to ‘complete’ one attribute at a time. Here, the user could browse and select multiple attribute types to add to their query, and drag to group and combine them in a way that mimicked human exploration vs formulaic execution, before adding specific attribute qualities.
We explored the impact of using more natural language to further remove the barrier to understanding more complex formulaic combinations; e.g ‘show me results that have all of these attributes’ vs ‘record must match all criteria’.
The client was excited about the potential of the disruptive query builder. However, to meet development and launch deadlines for MVP we completed the more traditional approach whilst finding more low impact ways to solve some of the UX challenges.
To encourage the exploration of and to demonstrate the abilities of the data available we created a ‘template’ concept that allows users to start a query from scratch or to start from a template of commonly combined attributes where they can get an easily adjustable query in 1-5 clicks.
MVP Launch & Continuation
The MVP functionality spanning onboarding, query building, reports & payment was developed and launched in November 2019 for a small set of initial users with great success & uptake. A phase 2 design & development program for adding data appending and campaign tracking functionality is currently under way.