Modern businesses have realized the need to take a data-driven approach to marketing in order to better understand customers, refine their strategies and drive business growth. Data-driven companies generally experience greater profitability, increased revenue and optimized business processes. However, inaccuracy is a common issue that makes it challenging for marketers to get the most out of their valuable data.
A recent Insights for Professionals report based on a survey of 209 marketing professionals across a range of industries from the United States and the United Kingdom, highlighted that data accuracy is a significant problem for organizations. Around 73% of respondents said they were concerned about the accuracy of the data being used in their company, and only 4% were confident in their data’s correctness.
As data environments continue to evolve and increase in complexity, organizations must take steps to improve data accuracy as soon as possible to avoid falling behind.
The importance of data accuracy
With accurate reporting being the second most reported challenge, it’s important for organizations to consider how marketing ops can facilitate better use and application of data, and how actionable data can be shared effectively. When data is accurate, relevant and useful, businesses will realize the following benefits:
Better decision-making
Good quality data is a crucial component for sound business decision-making. With the right information, senior leaders can steer their teams in the right direction, meet customer demands and lower risk in outcomes.
Increased productivity
Bad data is a productivity killer. In fact, sales and marketing teams lose over 500 hours across the year due to bad data – and this equates to roughly $32,000 per sales rep. Collaboration between sales and marketing is more important than ever, and quality data sits at the heart of any successful partnership. If you get your data in order and share it with the right people, you can maximize productivity and output instead of wasting time finding and fixing data errors.
Reduced costs
Not only does improving data accuracy prevent wasted hours over fixing discrepancies, but doing so will help you make significant savings. Aside from eating into your time and making your teams less productive, data errors can negatively impact your brand in a much bigger way, as bad quality data damages your credibility and can remove the trust between you and your customers.
Higher ROI
It’s simple – good data leads to better marketing. Data accuracy is the key to delivering effective campaigns that hit the mark with your audience. With the right information, you can reduce time and cost, while also achieving better results, boosting ROI and nurturing the bottom line.
Critical data accuracy mistakes to avoid
Below are some common pitfalls to avoid in order to improve data accuracy within your organization.
1. Incomplete data
When identifying what affects data accuracy, 42% of marketers reported that incomplete or outdated data sets are the biggest issues they face. Not having enough data can lead to inaccuracies as analyses may be conducted based on assumptions or extrapolations.
Records that lack key fields will lead to incomplete data that doesn’t reflect your customers correctly and can prevent you from targeting marketing and sales initiatives effectively. Ensure your reports are comprehensive, regularly updated and have a consistent tracking approach throughout. This will help you ensure outdated information isn’t piling up and avoid disjointed data that doesn’t accurately reflect your customers.
2. Data entry errors
The second factor impacting accuracy the most is data entry mistakes, with 28% of those surveyed agreeing that it’s a significant concern. This highlights the growing importance of automation and the removal of manual data entry tasks in ensuring correctness.
Humans make mistakes and it’s something that simply can’t be avoided when it comes to data entry.
Data entry is likely one of the many tasks that employees have to manage, and although sometimes errors are due to lazy practices, most often they are unintentional and just happen.
With manual data entry, it’s important to ensure you have a validation process in place to ensure that inaccurate information isn’t submitted in the first place. Managing this issue at the source, before it escalates, will save time and hassle down the road.
One way to minimize the risk of human error is to ensure forms are well designed and structured. For example, instead of prompting someone to type in a value they could select from a list of options instead. This can eliminate any misspellings that might occur if values are typed in manually. Also, avoid using fields that are confusing for the user and can influence them to enter wrong information. For instance, if database definitions are unconventional, the form should guide them through the process of entering values into the field.
3. Bot traffic in Google Analytics is affecting the accuracy of your data
Research by Barracuda suggests that 64% of all internet traffic comes from bots. Google Analytics picks this up, which affects the accuracy of your data by filling your sales pipeline with prospective customers that aren’t human. This leads to bad data sabotaging your future campaigns and strategies.
For those surveyed by IFP, nearly two-thirds of companies with 250 to 499 employees agreed that bot traffic in Google Analytics affects the correctness of their data. However, this survey group was also the least concerned about data accuracy overall, which is likely due to the fact that there are numerous resources available online about how to exclude artificial traffic.
4. Outdated and inefficient systems
Another big challenge for marketing professionals is integrating legacy systems with
new technology, and this is significantly more problematic for larger firms that have been dependent on outdated and inefficient systems for longer.
Nearly a third of marketers consider their data and analytics infrastructure to be inadequate – and just 20% would consider it to be excellent.
Failing to keep systems and forms updated with new possibilities and filter settings can result in data not being entered correctly. If an organization is dependent on an inefficient legacy system that doesn’t follow the latest tracking best practices, it can slow down data collection and lead to errors.
Once you understand the causes of incorrect data, it’s easier to fix the issue and prevent it from happening in the future. Most of these problems are easily solved by using systems and tools to automate tasks and implementing correct standardization procedures to minimize inaccuracies.
If the biggest issue in data is human error, simply automating and standardizing the data collection process can make a huge difference. Next would be to ensure that all your systems, tools and architecture are regularly updated.
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