The use of analytics is no longer limited to big companies with deep pockets. It’s now widespread, with 59% of enterprises using analytics in some capacity. And companies are capitalizing on this technology in several ways. For example, at our agency, we typically scrub big data for advertising insights for our clients. And many of the companies we’ve worked with revolve their entire market strategy around the insights pulled from new data.
According to a survey from Deloitte, 49% of respondents say that analytics helps them make better decisions, 16% say that it better enables key strategic initiatives, and 10% say it helps them improve relationships with both customers and business partners. But in order to take full advantage, you need to know how to get the most value from your data.
Data Quality Standards
There is certainly not a lack of data available. However, the quality of that data still leaves much to be desired. A study from the Harvard Business Review discovered that data quality is far worse than most companies realize, saying that a mere 3% of the data quality scores in the study were rated as “acceptable.”
This is problematic because low-quality data adversely impacts many areas of business performance. In particular, it can translate into incomplete customer or prospect data, wasted marketing and communications efforts, increased spending and, overall, worse decision-making. Therefore, improving data quality should be a top priority for all businesses.
There are a few ways to go about this but, in my opinion, as an agency owner, one of the best approaches is web data integration (WDI). WDI is a process that aggregates and normalizes data and presents visuals and other reporting that makes analysis easily digestible. WDI relies on a similar premise as web scraping but is far more comprehensive. It also has the ability to make data “intuitive” — something that’s essential for capitalizing on the massive volume of data that’s out there.
It allows you to take a large volume of data from a myriad of sources and break it down in a way that makes client analysis much easier to do. For us, if we’re looking to clean up data quality, this process helps us present data back to clients in a cleaner fashion.
Before formally choosing to implement WDI, businesses should first determine what specific goals they have for data sets and then decide whether an in-house solution or a managed service through a third-party provider is the better option.
Another way companies are fully leveraging data is through machine learning, where computer systems learn, improve and evolve as they take in new data.
Assessing Data Quality
So, how can you tell if you’re dealing with low-quality data? In a Harvard Business Review article, data experts Tadhg Nagle, Thomas C. Redman and David Sammon recommend the following key steps:
• Gather a list of the last 100 data records you used or created.
• Then, focus on 10-15 key data elements that are most integral to your business operations.
• Have management and their teams go through each data record and identify any noticeable errors. Examine the results. (In my opinion, an easy way to go about this is to create a spreadsheet with two columns — one for perfect records and another for records with errors.)
Once you look through the results, the quality level of your data should become obvious. If more than two-thirds of your records have errors, that’s usually a sign that data quality is hurting your performance and needs improvement.
Here are a few other data management tips:
• Move all of your data to a centralized database to create a standardized data architecture.
• Ensure your employees are up to date on all aspects of data best practices, including data entry, management, compliance and safety.
• Create data management hierarchies if you have multiple teams to keep it all organized and reduce the odds of a breach occurring.
• Designate certain team members to handle core data management.
Choosing The Right Tools
Data is one of the most valuable assets a business can have and potentially has a tremendous impact on its long-term success. That’s why it’s vital to utilize the right tools and technologies to fully leverage all available data and make it as accurate as possible.
Here are some specific things we look for when assessing tools/technologies for accurate data analysis:
• Data normalization for simple organization
• Shareable dashboards for streamlined communication between team members
• Fully mobile
• Third-party integration
When searching for tools, it’s wise to request a demo of any platform you’re considering to get a hands-on feel of how it works, what the dashboard is like, how intuitive it is and so on. Do you naturally like the look and feel of the product right off the bat? Or do you find the experience to be friction-filled? First impressions are everything, so you want to ensure the product feels right to you.
Analytics has come a long way in a relatively short period of time. It can aid in multiple aspects of operations and be a real game-changer for many businesses. But to get maximum results, companies need to know how to properly utilize this technology, improve the quality of their data, and effectively manage it. Those who are able to do so will have a considerable advantage over the competition, and be poised to succeed in 2019 and beyond.
Feature Image Credit: Getty