UX/UI, Branding, Leadership

Claravine


PROJECT : CLARAVINE 2.0
claravine_logo
The Challenge

The increasing dispersion of marketing tools and teams generating tracking often leads to digital experience data that is inconsistent and highly inaccurate. This lack of effective tracking can lead to misspent advertising and limited visibility into the actual drivers of campaign performance.

The need was for a tool that standardized the taxonomy, creation of a governed process, and be able to validate for campaign readiness.

CLIENT
Claravine

ROLE
LEAD / UX DESIGNER

CATEGORY
UX/ UI, DESIGN, BRANDING

SKILLS
SKETCH, INVISION, LUCIDCHARTS

Process at a Glance

DISCOVERY
Discover and research to define user scenarios and workflows

WIREFRAME
Use Cases, Work flow(s), Site Map, Wireframing, Major Interactions

PROTOTYPE
Visual design, Style Guide, Screen Mockup’s, Interactions

VALIDATE
Get quick and often feedback from stakeholders and team members

TEST
Meet and test actual users and observe user interactions and record results

SUMMARIZE
Validate and learn from users behaviors. Analyze user feedback and results from testing. Iterate as needed

The Solution

The software that Claravine had already built (Tracking First) worked, but had problems that began to show as the customer base grew.  Because of this, it opened up the discussions for the need of UX.

I was brought on the team to establish a UX process (they had not ever had a UX designer or a designer outside of a 3rd party agency).  The UX process included everything from introducing design thinking, creating a design system, establishing the tools for designing and testing, and getting UX a seat at the table.

After establishing and defining a UX process I then got to work on solving the issues.

I started by reaching out to key customers and collecting exhaustive feedback on how they were using the tool.  I wanted to know how they work, what their pain points were both with their jobs and the tool itself.  Next, I created user flows and journey maps that represented the data I had collected so far.

I met daily with BA’s, product owners, dev’s and other stakeholders to determine needs, technical constraints, and to review progress.  From these meetings I created wireframes and iterated based on test results and stakeholder input.

group discussion

Core Issue: Human Error

After identifying a few core problems, the biggest issue we found was that there was a huge problem with consistency in how campaigns and tracking were created. We were able to identify that a large proportion of digital media spend – 40-60% – was tracked ineffectively because of a simple thing such as human error.  We knew we needed to remove as much as that as possible by automating huge parts of the process.

manual process
Manual Process

We identified some common roadblocks to effective media analytics. We also outlined which elements of the campaign process most often lead to tracking errors, and suggest key steps to avoid those mistakes through automation.

Those details get exported into a trafficking sheet based in Excel. Teams or agencies populate the data fields for each ad variation within this sheet. Populating traffic sheets is a painstaking process, and human error at key points can compound data quality issues at the end of the campaign.

Some issues we identified were:

    • Mistakes during data entry create inconsistent tracking codes and landing page URLs
    • Inconsistent codes and URLs don’t capture necessary metadata
    • The volume of lines for each ad iterations complicates data quality checks
    • Loss of valuable meta-data disrupts campaigns views downstream

Depending on the size of a campaign, a traffic sheet may include hundreds or thousands of lines for each ad iteration, multiplying the challenge of manual checks and validation.

Automated Process

The major weakness of a typical media campaign process is, ultimately, the margin for error allowed by the large volume of manual data entry across teams and platforms. In order to eliminate those errors and ensure the veracity of media data, the source of the data has to be governed.

After populating a trafficking sheet, a governance platform can:

    • Ingests, validate, standardize metadata
    • Confirm that tags, codes, and pages are ready
    • Append missing data
    • Bulk export metadata to demand-side platforms (DSPs) with the required structure
    • Centrally manage changes to and consistency of taxonomies

Addressing the manual elements of the media campaign process with automation expedites the launch of digital experiences and ensures granular, correct data for analysis.

automated process

Claravine is a fantastic solution that accelerates the process of getting sound campaign tracking reports up and running. The intuitive and user-friendly interface quickly reduces errors and enhances the workflow around multi-campaign tracking. We recommend it to all our clients!

Brad Millett
Blast Analytics and Marketing

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FINAL DESIGN

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