AI seemingly has its thumbs in every pie these days, and data collection is one instance where its use can be particularly dangerous. Accurate data is essential for personalised marketing, and if there are inaccuracies – referred to as ‘dirty data’ – the consequences can ripple throughout the entire business.
The business can quickly lose credibility, customers will lose trust in their services, and, of course, money will go down the drain. To keep this from happening, we’ve put together a guide on how to avoid dirty data.
Thorough Checks
Dirty data includes a wide spectrum of issues, ranging from minor typos or misplaced entries in a database, all the way to outdated or wholly falsified information. Imagine the trouble you’d get into leaving dirty data unchecked, then also consider that businesses may spend 30% of their working hours simply trying to understand unclear data.
The last thing you want is to lose money or credibility, let alone simultaneously. Reinforcing strict data entry practices can help fix some of these issues, but cannot fully resolve them.
Frequent Audits
By constantly reviewing the data you’ve accrued, you can lower the risk of inaccuracies sprouting up. Automated data validation tools, or the help of an adept data collection company, such as https://shepper.com/, can all ensure proper procedure with the data you collect.
AI
Yes, we warned of using AI in our intro, but AI does not need to be discarded entirely because lazy workers didn’t check the data that an AI collected for them. There are AI tools that are capable of automating data validation, while others can filter out falsified or incorrect entries from databases. But always remember to check on the AI, instead of just leaving it to do your job.
Clean Data
Maintaining high-quality data is vital to a business’s success, helping to maximise efficiency and boost the trust of customers. AI also needn’t be feared – just used more prudently. By adhering to rigorous data management and collection practices and ensuring truthful information, companies can evade the dirty data circulated by malpractice.
