What issues are marketers encountering with their data and how are they addressing them?
Interestingly, when we asked the same pool of people to rate their data and analytics infrastructure, almost a third (32%) claimed it was ‘fair’ or ‘poor’, illustrating the differing progress our respondents have made in their journey to data analytics maturity.
When asked to pinpoint the biggest challenges in data maturity and what affects the accuracy of their data the most, respondents chose the following responses:
1. Incomplete or outdated data
The majority of our participants (42%) reported that they’re struggling with incomplete or outdated data. This could lead to faulty decision making if left unsolved and could potentially lose your company millions of dollars of revenue. Moreover, outdated data could hinder your ability to adapt to both changing customer preferences and fluctuating market trends. If your data is incomplete, you risk having to delete it all and collect it again from the beginning to avoid inaccuracies.
2. Data entry mistakes
The second most reported issue with over 27% of votes is data entry mistakes. What’s important to note here is that as long as humans enter data manually, there will be mistakes. However, there are ways you can mitigate and reduce these errors.
For example, streamlining and automating your data entry processes will help you avoid mistakes and will render your data more accurate. What’s more, teaching your employees about the importance of data and providing them with a stable working environment are also ways to avoid data entry errors in your business.
3. Bot traffic in Google Analytics
Bot traffic can seriously impact the accuracy of your data, and it’s crucial that you spot it and filter it out early on. In fact, 23% of our participants claimed that bot traffic in GA affects their data accuracy. Unfortunately, you can’t guarantee that your website won’t accumulate bot traffic. Nevertheless, by automating your bot detection processes and always reviewing your analytics, you can monitor your GA bot traffic and remove it before it impacts your decision making.
4. Using the wrong report
Finally, only 7% of our respondents pointed out that using the wrong report impacts the accuracy of their data. Although this wasn’t a major issue for most marketing professionals, it is still one you need to pay attention to and solve before it impacts your ROI.
The importance of data accuracy
1. 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.
2. Increased productivity
Bad data is a productivity killer. In fact, sales and marketing teams lose over hundreds of hours across the year due to bad data. Collaboration between sales and marketing is more important than ever, and quality data sits at the heart of any successful partnership.
Listen to the podcast: Episode 27: How to Align Your Sales and Marketing Efforts | With Greg Gifford
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.
3. Reduced costs
Not only does improving data accuracy prevent wasted hours over fixing discrepancies, but doing so will also 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.
4. 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.
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