As more companies look to leverage data for insights, the implementation and investment in data quality solutions is going up. This is not surprising: business intelligence is only as good as the data that is used to generate analytics.
This investment is happening across all departments and industry sectors and marketers are certainly included. Ninety-two percent of marketers are investing in data quality solutions today. The bulk of them spend more than $500,000 annually on data quality technology. That level of investment means that 98 percent of marketers now have a data quality solution in place, higher than the average respondent rate.
The call for ROI on data quality solutions
Organizations are often required to do more with the same budgets and resources, or even less. That means that every dollar marketers spend is often scrutinized, which can make investing in new technology difficult.
The good news is that most marketers do find value in data quality solutions. Eighty percent of marketers say they see a return on investment from their data quality tools. However, there is a difference between perceived value and calculated value.
The perceived value alludes to a positive perception of data quality tools, but that can fade as staffing changes or organizations restructure. The only way to truly demonstrate return on investment over time is by calculating it with hard figures.
Today, 62 percent of marketers annually calculate the return on investment from data quality solutions. While that is a great percentage, it still leaves a number of companies who only perceive a return on investment, rather than know it as a hard fact.
While we marketers often work to demonstrate an ROI for a given campaign or attribute sales to a given channel or series of connections, we sometimes forget about measuring the return our technology provides. It can be considered a standard part of doing business.
However, determining the ROI for technology, especially ROI on data quality solutions, is essential. This is for two reasons:
- Budget allocated to given data quality solutions may be cut if value is not demonstrated.
- Poor solutions that do not benefit the organization could continue to receive investment rather than opening up budget to search for new technology.
To ensure data quality tools meet business requirements and continue to receive investment, ROI metrics need to be calculated to prove with hard figures that data quality is benefiting the marketing department and the business. It is important that the value of these tools is not just perceived but proven to the business.
Be sure to take metrics early and often when implementing a new solution and socialize those metrics, both positive and negative, with key stakeholders.
For more tricks and additional insight, download this white paper on the ROI from data quality solutions.