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Data quality in B2B sales [and why you need your data to be qualitative]

by Karan Sharma
last updated on May 27, 2024 11:50:08 AM

Data quality in B2B sales

Data quality can make or break your B2B sales efforts. High-quality data increases the efficiency of your sales process, enhances personalization, and improves conversion rates. Let’s delve into the best practices for maintaining clean data in B2B sales.

First, it’s important to recognize the common pitfalls associated with data quality.

Duplicate records can lead to multiple touchpoints with the same contact, causing confusion and inefficiencies.

Inaccurate data, like outdated or incorrect contact details, can result in outreach that falls on deaf ears.

And incomplete data block your ability to fully understand and engage with your prospects.

So how do you ensure your data stays clean and accurate?

Start by regularly auditing your database to check for inaccuracies and duplicates, which can be streamlined using advanced data verification tools (Hint: check out hubsell's data solutions).

Let's start by listing the most common problems caused by inaccurate, outdated and incomplete data.

 

Risks and problems caused by bad data

Bad data quality can significantly impact your B2B sales efforts. Here is list of the most common issues caused by bad quality data.

  1. Poor data leads to wasted time. Sales reps spend valuable hours chasing inaccurate or outdated leads, lowering overall efficiency.
  2. Inaccurate email addresses increase bounce rates. This can harm your sender reputation and push your emails into spam folders, reducing open rates.
  3. Misleading metrics from bad data can skew your key performance indicators, leading to inaccurate sales forecasts and misguided decisions.
  4. Customer dissatisfaction is another risk. Mismatched offers or poorly targeted marketing campaigns frustrate potential customers and can erode trust.
  5. Ultimately, bad data increases operational costs. The inefficiencies and extra resources needed to clean and correct data can add up, affecting your bottom line.

When you want to update your data or fix your data problems you will want to use a data source. And you'd want that source to be relevant and fresh.

Good sources of fresh data

To maintain high data quality, it’s crucial to use reliable sources that provide up-to-date and accurate information. Here are some of the best sources you should consider when updating.

 

LinkedIn

It is a rich source and in may ways a unique source of professional data with up-to-date job titles, company roles, and career histories. Users frequently update their profiles, offering fresh and current data. But a lot of better than the vanilla version of LinkedIn, is their sales product, Sales Navigator which allows for in-depth filtering. I have written another posts which addresses how to use Sales Navigator to get the best out of it:  Masterclass: 9 tips to level up your Sales Navigator game

 

Company website

Company websites often provide direct and reliable information about key personnel, company news, and updates. Monitor press releases for the latest announcements on new hires, partnerships, or product launches.

 

Industry publications and news sites

Industry-specific publications and news sites are excellent sources for the latest trends, acquisitions, and executive movements, especially if your target market is consisting of large multi-nationals. They publish regularly updated content which should track with Google Alerts so that you have the most recent data on market developments.

 

Other social media platforms

I say other because LinkedIn is also a social media platform but it is unlike the others, however platforms like Twitter/X, Facebook can be used to gain information about your target personas.

 

Maintaining data quality

There are two things you will need to have main good data quality.

 

Start off with good data

Easier said than done since most data vendors out there are databases which themselves suffer from bad data quality. Good news is that not all data vendors are database resellers, there are solutions (like hubsell which generate new data and update existing data for their customers).

By starting off with good data, you lower the amount of work you need to do to remain productive.

Next off.

 

Periodically update your data

Consistent practices are key to keeping your data in top shape. Schedule monthly or quarterly audits of your data. Set up automations to generate lists of all contacts and accounts that have not been updated since a chosen period and then have those contacts and accounts updated and completed.

An alternative to doing it in-house is to use solutions that provide near real-time updates, these are solutions that periodically (say weekly or bi-weekly) check social media to see if the contact or the account has undergone any changes. When a change is detected, these are then updated in your CRM.

Another key point to remember is that in order to more easily keep your data fresh, make sure that you find and add the social media profile URLs in your CRM as part of your data.

Now that you know how to start off with good data and keep it good, let's talk about one of the ways outdated data shows its ugly face. Email bounces.

Email bounces are the bane of email deliverability and your email outreach performance. Let me explain how email validation is done.

 

Validate email addresses

For starters understand that there are two types of email server settings when it comes to email validation.

 

Catch-All servers

Catch-all (aka accept-all) servers accept all email messages sent to a domain whether the specific address is valid or not. Traditional data providers struggle with validating these, making it hard to know if the email address actually exists.

A catch-all server essentially ignores any email validation requests, which then requires more granular methods to validate the email address on catch-all servers.

Hint: hubsell specializes in validating email addresses on catch-all servers, so if you are suffering from high bounce rates (e.g. above 5%) then get in touch with us and we can help.

 

SMTP-pingable

SMTP-pingable (not official nomenclature) servers are servers where when you ping them for email validation they return with a confirmation or rejection of an email address, where the former indicates that the email is valid and the latter that the email is invalid.

There is also a third option, which is typically called "validation delayed" or "unknown" or something undetermined like that. This option occurs for a various of reasons but trying the same email with multiple email verification tools can help solve the problem.

Most data providers rely solely on SMTP pinging to validate emails. This doesn’t cover all scenarios, especially with catch-all servers. To better understand, why you need to make sure that you are also validating on catch-all servers, you need to know that catch-all/accept-all server make up approximately half of all servers for business email addresses (so no free-mailers like gmail/yahoo etc).

That's why a dual validation process combining SMTP pinging and additional checks is more comprehensive. It not only ensures higher accuracy but also reduces bounce rates, making your email deliverability more reliable.

hubsell can help with both cases.

Conclusion

Maintaining high-quality data is paramount for successful B2B sales. Implement these best practices today and watch your sales performance soar.

Start by regularly auditing and cleansing your data. Use real-time updates to ensure data accuracy. Integrate with your CRM for seamless data management. Enrich your data for deeper insights.

By following these strategies and leveraging superior data solutions, you can mitigate the risks associated with bad data and capitalize on fresh, accurate information to drive your sales efforts forward.

By following these strategies, you’ll be well-equipped to dominate your B2B sales efforts.