Determine Your Data Quality With These Tips
Bad data can make it increasingly challenging for brands to accurately target customers. It can lead to inaccurate information about them and make it hard to know who will be the most receptive to your promotions and sales pitch. Therefore, organizations should pay close attention to how to improve data quality and what they should do about it if its not up-to-par.
Let’s explore first some of the major forms of bad data to better see how to pick out this unhelpful information.
- Inaccurate or missing data
- Non-relevant data
- Non-reliable data
- Vanity data
Inaccurate or missing data. Inaccurate or missing data might be a particular problem for your sales team. For example, you might see two entries for a single prospect, missing contact information for a lead, or inaccurate information regarding the company of the lead.
Sometimes data comes from mistakes in data entry, but it also can come from inaccurate data posted online, or data that ages.
To solve these problems, you will want to tackle the problem from a few different directions.
- Help everyone in the organization see the problems that can come from bad data. Make sure everyone has training on the business’s best practices regarding data entry.
- Make sure the sources from where you gather data about leads are accurate and trustworthy.
- Dedicate time to data scrubbing. Allot time for people to regularly sort through their existing data and update it as needed, delete duplicates, or otherwise scrub out inaccurate or unhelpful information.
Non-relevant data. As you collect data, you also need to make sure that the information you gather is relevant. You might have plenty of data on prospects that accurately describes your lead, but if that information will not help you understand their pain points and solve them, it does not offer you any value.
Examine the data you have for relevance. Delete irrelevant data and do not waste more resources collecting this information. Focus on the data points that better help you serve your customers.
Non-reliable data. Data also sometimes comes from sources that you should not regard as reliable. Sometimes people post inaccurate data online. Othertimes, the results of market research or surveys arrive from organizations with a clear bias. The information from these types of sources cannot be trusted to guide business decisions.
To root out this type of outlier data, be sure to verify the sources as you collect data and check to be sure that they will provide solid information.
Vanity data. Vanity data describes information that might help an organization look good, but the information itself does not help with marketing, sales, or customer engagement.
To avoid wasting time and resources collecting vanity data, make sure that you carefully plot out KPIs that reflect your marketing strategy. Know what your campaigns want to target and use that information to help you choose KPIs that will guide your organization and offer immediate value.
Bad data can derail marketing and sales efforts by making it hard for brands to accurately target potential customers and leads. Consider the tips for each of these types of bad data to ensure that you maintain clean, effective data banks that will help you target and bring in new customers.