Jin Lin

Associate Director at Conversant

Jin Lin graduated from Northwestern University’s Medill IMC program in 2009. Currently, he is the Associate Director at Conversant, providing digital analytics solutions for clients to improve marketing efficiency. Before Conversant, Lin served as the analytics lead at Groupon and helped to build Groupon’s CRM program.

Changing How We See Data

Data visualization is an increasingly critical part of analytics in the field of marketing. As the most visible part of analytics, data visualization naturally receives the highest awareness level in organizations. It enables business stakeholders to identify trends and patterns from Big Data that often get lost in the clutter. Since my time at Medill IMC eight years ago, I’ve been working in the field of marketing analytics and I’ve seen data visualization evolve steadily. Let’s look closer at some of the trends emerging in the ever-changing realm of data visualization

Data novices and Excel rookies rejoice: visualization tools are getting more user-friendly. Employers want their data teams to be able to perform ad hoc analysis by themselves, so the tools have become much easier to use. Coding is not required in most cases so inexperienced data analysts can jump right in. Most users still use Excel as their primary method for data visualization because it’s charting tool can be used at the same time as you manipulate your raw data. Additionally, although individual users are encouraged to perform data visualization, more and more companies are starting to assign data visualization to a dedicated team to handle common problems and ensure a consistent style. Typically, these newly emerging data visualization teams are designated as the “business intelligence team.”

Some dashboards will be frequently requested by different groups within the organization, so it is more efficient if one centralized team can process those requests. The data visualization team is commonly responsible for auditing dashboards published on public spaces and then purging redundant or unused dashboards regularly. When the size of organizations becomes larger, it is hard to show new employees where the established reports can be found. Thus, a centralized team can serve as an educator to new hires to avoid excessive training by individual teams. While some dashboards will contain sensitive information and should not be shared with everyone, a centralized team can manage dashboard permissions more efficiently.

Another trend I’ve noticed is that more data analysts are placing aggregated tables in databases. Companies want to know how metrics are grouped by a multitude of dimensions. Some data visualization tools can set up connections to databases directly so users can build data views easily and efficiently at any time. However, direct queries on raw data, especially at large scale, can cause a huge delay in performance. To solve this problem, database administrators have begun creating intermediate tables or final outputs stored within databases as buffers. These new tactics and trends are not without a financial commitment, however, and companies are increasingly more willing to invest in data visualization. The typical license fee for software is around $1,000, but many companies are jumping at the opportunity to make the investment. As a result, employees can get access to the tools without pesky licensing hurdles or resorting to outdated software. Organizations then want to offer ample training opportunities for their newly purchased tools. Typically, companies will put together training materials from various sources in a centralized location so employees can have easy access when needed. I’ve also witnessed companies begin to invite experts from vendors to give an onsite training on a regular basis to share data visualization best practices.

When shifting our view to academia, schools are also hosting more and more classes on data visualization. While these types of classes are usually intended for students from analytics-related programs, students from all concentrations are seeking out data visualization education. Whereas, previously, these topics were usually blended with an introduction of an analytics tool, we’re now seeing much more specialized workshops and classes. For example, Northwestern offers a data visualization course to any interested undergraduate or graduate students wishing to expand their horizons.

Whether it’s in the classroom or at the office, data visualization tools are evolving. Both the highly specialized tools themselves and the education required to use them are being proliferated and streamlined so anyone can pick it up quickly. For a truly well-rounded IMC experience, these tools are of the most importance and they’re only starting to gain momentum.

Written by Jin Lin, Associate Director at Conversant
Edited by Thomas Nissen, Medill IMC Class Of 2017

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