Everyone has probably heard the story of The Three Little Pigs. While two pigs built houses from straw and twigs, the third pig built his house of brick and cement. It doesn’t take a structural engineer to figure out which house was strongest and could withstand the huffing and puffing of the Big Bad Wolf.
Building a startup is a lot like building a house. Use strong data and you’ll have a strong foundation for your company. Conversely, competitive external forces combined with weak, inaccurate data puts your company at risk and can upend the groundwork in place. Data quality is important for all organizations but even more so for startups.
Everyone Needs Data Quality
There are a number of issues that can arise from using incorrect or incomplete data. This might seem trivial at the onset but can snowball if left untended. For example, when sending a newsletter, it’s essential to have the correct email addresses. Ignore this imperative and a lot of emails may not reach the intended customer. Opportunities are missed, time and money are wasted, and additional resources must be expended to reach these people.
So, let’s take a look at the top reasons organizations need data quality solutions:
- Connect to People and Potential
For a startup to grow, it must be able to reach existing and prospective customers. For this, a strong customer base is a necessity. It will form the cornerstone of your growth pattern. You can reach out to people in a number of ways – through emails, phone calls or even direct mail. Without the right contact details, how do you expect to connect with these people? Every person for whom you do not have the correct data represents a missed connection, and a lost opportunity to generate revenue and growth.
- Build Better Customer Experiences
Would you be pleased if you ordered something online and did not receive it on time because the company had the wrong address? Of course not. Having to reship a product increases vendor costs and is likely to negatively impact customer relationships as well. Maintaining the accuracy of your data supports and helps build better customer experiences.
Retaining customers is crucial. Hence, you cannot afford to lose them over improper data handling. In a world of online reviews, an irate customer leaving a bad review of your product and the experience could keep other potential customers away too.
- Minimize Data Collection
It’s also important to keep customer data secure. Since the introduction of GDPR regulations, companies can face severe fines and even jail time if customer data is compromised.
The less data you collect, the easier it is to secure and manage. This can be accomplished only if the data collected is accurate and sufficient for conducting business. For example, in many instances having the right email addresses is appropriate and phone numbers may not be necessary. Minimizing data collection also streamlines the customer experience and reduces cart abandonment.
- Optimize Costs
Working with inaccurate data is a costly affair. Consider that having the wrong address affects shipping expenses. Without data quality tools, incorrect email addresses require manual handling, for example sorting to dedupe or correct. Tracking and correcting inaccuracies also takes time away from other more important tasks. These may be considered mundane tasks that appear to incur negligible cost, but on an annual basis these losses of time and resources add up.
Another way to view these costs is to consider the price tag associated with lost opportunities. What if the person you were trying to email was a potential customer?
- Build A Good Reputation
Who do you trust more – a brand from which you receive an email when they say they will send one, or the brand from whom you hear nothing? Bounced emails are not only bad for your marketing department but can also affect your reputation. Similarly, if you have to contact a customer every time they place an order to reconfirm their shipping address, the customer will lose patience and trust.
The Bottom Line
Maintaining quality data isn’t something only big brands need worry about; it is every organization’s responsibility. Focus on each level of data handling – its collection, segregation, validation, and enhancement – and build in data quality as an operational standard. Startups are all about capitalizing on potential and opportunity, so it is just good business to protect and foster accurate customer data as a valuable asset from day one.