Six reasons to normalize customer data
Posted: Mon Dec 23, 2024 9:33 am
Now, the big question: Why? Why should I spend all that time and effort normalizing my data? It may seem unnecessary if you aren't noticing any serious problems with non-normalized fields.
The answer is simple. Most of the negative effects of poor data go unnoticed. Sure, it can be embarrassing to see yourself addressing a potential customer as “JAMES” in an automated marketing email. But it’s not the end of the world.
But not all of the hidden effects of poor-quality data that never get talked about or reach management are visible. But these effects can hurt companies that rely on big data over time.
When you have low-quality data, marketing teams are afraid to inject thailand country code more data-driven personalization into marketing campaigns. Even small mistakes, such as incorrect capitalization of names, can impact your brand’s reputation in the long run.
Sales teams are also affected. Lack of data and poor quality data means they lack the critical context they need to speak directly to the biggest concerns of customers and prospects. This leads directly to declining sales and poor-quality analysis.
Additionally, poor quality data negatively impacts lead scoring , hindering salespeople’s ability to effectively segment and categorize leads so they can engage with them effectively.
Here are five of the top reasons why every business should normalize their customer data in some way.
The answer is simple. Most of the negative effects of poor data go unnoticed. Sure, it can be embarrassing to see yourself addressing a potential customer as “JAMES” in an automated marketing email. But it’s not the end of the world.
But not all of the hidden effects of poor-quality data that never get talked about or reach management are visible. But these effects can hurt companies that rely on big data over time.
When you have low-quality data, marketing teams are afraid to inject thailand country code more data-driven personalization into marketing campaigns. Even small mistakes, such as incorrect capitalization of names, can impact your brand’s reputation in the long run.
Sales teams are also affected. Lack of data and poor quality data means they lack the critical context they need to speak directly to the biggest concerns of customers and prospects. This leads directly to declining sales and poor-quality analysis.
Additionally, poor quality data negatively impacts lead scoring , hindering salespeople’s ability to effectively segment and categorize leads so they can engage with them effectively.
Here are five of the top reasons why every business should normalize their customer data in some way.