Data Quality is Essential to Pharmaceutical Marketing Success

Through my work with several financial services organization and pharmaceutical companies, one of the biggest issues I have noticed is with their data quality. These organizations typically have numerous data points such as web analytics, CRM solutions, email marketing platforms, sales information, etc. The challenge is that most of the business units don’t collaborate to integrate their data or to identify the best possible solution to integrate data. If you can’t agree to collaborate, it makes it even more challenging to manage data quality issues. At the same time, organizations have a tendency to use multiple data sources for the same information. Which source is providing the real picture?

Our team encountered data quality issues with a pharmaceutical client while developing monthly marketing metrics reports. We estimated that the data quality issues were costing them over $250,000 per year (if not more). The outdated web analytics solution wasn’t being maintained, so they had skewed SEO traffic, inaccurate referral sources, and limited functionality to integrate with their CRM solution, email marketing, or paid search campaigns.

Basically, they were blindly marketing to healthcare professionals and patients without any knowledge of what their target audiences were engaging with from a marketing perspective. Product managers were being held accountable for something that they had no visibility into, whether it increased new acquisitions or not.

Total Costs to the Organization:

• Outdated Web Analytics Solutions: $250,000 per year (minimum)
• Human Resources for Web Analytics Solution: $100,000 per year
• Estimated Marketing Budget Total: $3,000,000 per year

Poor Data Quality + Poor Data Integration = Poor Decision-Making!

Data Quality isn’t just an issue for Fortune 500 companies. It is also an issue for smaller businesses where decisions can make or break them. Regardless of the size of the business, we still need to take into account the business requirements, technical requirements, reporting, and the impact that the data will have on the organization’s ability to create efficiencies and save time and money. There are significant costs associated with a lack of data and poor data quality.