Businesses need high data quality to properly strategize their efforts and win the attention of customers.
Easier said than done.
This is a struggle that even large, multinational corporations have: utilizing resources to produce accurate data without excessive inefficiency.
Inaccurate data is inefficient.
But employees spending too much time manually validating that data is also inefficient.
Buying technology and not leveraging it to its fullest extent is inefficient as well.
If you want to run your business at its optimal level then you must eliminate inefficiencies. You need to get rid of bad data, without having to do it manually.
Manual Validation Sucks Up Your Resources
Nearly one third of analysts spend more than 40 percent of their time vetting and validating their analytics data before it can be used for strategic decision-making (Build Trusted Data With Data Quality, Forrester Research, February 2015).
In digital marketing teams, analysts spend a lot of time validating, manipulating, massaging and cleansing data. To some extent this is necessary because analysts want to make data legible, understandable and presentable.
Still though, 40 percent of their time?
That is a significant allocation of time towards making data clean enough to analyze.
What if it were possible to reduce that 40 percent to 10 percent, giving these analysts another 30 percent of their time to dedicate towards strategic thinking?
Keeping data accurate is essential for the efficiency of your business, particularly your MarTech stack. Accurate attribution and conversion data can help you determine whether or not campaigns are worth the allocated resources.
Do You Know Your ROI?
Unfortunately there seems to be a pattern of inaccurate data, making it hard for digital marketers to determine whether or not they wisely invested their resources:
Research suggests 51 percent of digital marketers are not able to sufficiently identify the ROI from their web and mobile marketing technology stack (2016 B2B Budget Plans Show That It’s Time For A Digital Wakeup Call, Forrester Research, February 2016).
Not being able to identify the ROI of your marketing technology is dangerous. If you don’t have data, then what do you use as criteria for allocating marketing resources?
Marketers without data to guide strategy make investment decisions based on intuition, previous experience with a certain technology or simply human emotion. But when you can’t trust your data to quantify the return of an investment, then you have no way of knowing if it was a wise use of resources.
You need to know that your data is accurate.
Poor data quality issues result in an annual financial impact estimated to be over $14.2 million dollars per year. (What Does Bad Data Cost? IT Business Edge, February 2015)
The overall digital intelligence of your company relies on the validity of your data.
Inefficient decision-making occurs when data is inaccurate.
Business strategies that find basis in hunches cannot stand up against strategies fueled by data-driven insights.
Having the necessary information to know how a customer is going to respond is essential to creating a customer-centric business.
Automate for High Data Quality
“By using a data quality assurance solution to automatically QA their tagging and MarTech implementations, I have seen clients turn what used to be a 16 hour vetting process into something that takes only minutes—resulting in as much as an 87.5% increase in employee efficiency.” —Mackenzie Knapp, Data Analytics Consultant
Using web audits and automated validation tools such as ObservePoint’s WebAssurance™, your company can monitor thousands of pages and isolate specific URLs where incorrect tagging has occurred.
This will save you resources, give you trustworthy data concerning your ROI and help you make meaningful decisions off of actionable data.
About the AuthorLinkedIn More Content by Doug Jensen