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How poor quality data can impact your sales team

When you’re absolutely starving and just looking for something to eat, anything will do.

You’ll grab a sandwich here, get a Coke there, you may even pop into McDonald’s and grab a burger and fries - even though you promised yourself you were going to eat better!

But it doesn’t matter, you’re hungry and well, it’s convenient. After all, you’re just on a mission to fill yourself up and keep going about your day.

Well, this is kind of how poor quality data comes about.

In B2B sales, IT and salespeople look to pull data from the most convenient places, rather than collecting complete and relevant data, propagating “dirty data”.

So, what’s the big deal with dirty data, and why does it matter? Keep scrolling 👇 for our insights.

Why is quality data important? 💾

Data is becoming a core component of business, and a business in itself. Quality data is one of the most important contributors to the success of a company, from prospecting to lead generation.

Essentially, data is actionable knowledge, gathered from a variety of sources. Sales leaders use it to power their sales strategy. It empowers them to make decisions that will positively impact the success of a company, improve its practices, and increase revenue.

This data sits in your CRM system and is a vital asset for your sales team.

With prospect and customer data doubling every 12 to 18 months, having poor quality B2B data is sure to hinder your outbound sales process and waste a lot of time.

It will cause operational inefficiencies, unnecessary costs, and impact your customer satisfaction, all of which will cost you dearly.

How poor quality data impacts on your sales team’s performance 📉

Much like sending a construction worker to a site without his tools, sending your SaaS sales team out without the correct data is really not going to help them get the job done.

The consequences of using dirty data in B2B sales are far-reaching. It impacts employee productivity and your company’s reputation. It has a crippling effect on revenue and business growth.

According to Integrate, an average of 40% of B2B generated leads are invalid, incomplete, or duplicates.

We think that’s an epic stat. And that’s not all.

Here are some other ways that working with dirty data affects a sales team.

It wastes time ⌛

In B2B sales, and throughout your entire organisation, your salespeople are the most reliant on your CRM data.

According to recent studies,  94% of businesses suspect that the data they have on their customers is inaccurate. It’s been identified that chasing bad data wastes over 27.3% of a B2B salesperson’s time.

It contains malformed content 🚧

Malformed data is B2B data that is unusable or corrupt - like phone numbers with too many digits.

Malformed content in a contact field prevents salespeople from following up with leads. It also prevents searches from being populated with quality leads.

It results in undelivered mail 🚫

Email addresses are often incorrect due to human error like missing a letter, or the account is latent, temporarily unavailable, or a spam trap.

Your sales team is heavily reliant on digital communication to engage leads, start the sales cycle, and close deals.

If their emails are not being delivered, it wastes your team’s effort, impacts sales forecasts, and hinders the campaign’s success.

This all leads to missed opportunities 🤝

In the above examples, key engagement points are missing, meaning salespeople won’t be able to communicate with leads effectively. That leads to reduced demand and an inability to nurture leads.

How to address data quality issues 🛠️

So, how do you, as a sales leader, make sure your data’s not inaccurate, incomplete, or inconsistent (i.e. dirty)? 🤔

Firstly, it’s important to understand that poor quality B2B data needs to be addressed at all levels where dirty data creeps in - technology, governance, and at a people level.

Here are five ways to address these issues 👇

  1. Make data quality part of your onboarding and training processes. Inform your current sales team, and new recruits, of the importance of quality data and stress this to them - the data must be both compliant and useful.
  2. Give ownership of your data to your sales team. Emphasise that gathering quality data is not the responsibility of your IT team. The onus is on your sales team to generate good contact data.
  3. Audit your data frequently. Identify gaps and eliminate dirty data where you can. Rotate who audits the data so that fresh eyes are looking every time.
  4. Add data quality to your team meeting agendas. Get the auditors to report on their findings in your weekly meetings.
  5. Look to automation. Partnering with a trusted company, like Cognism, gives you access to quality data and cuts down the work for your team.

Cognism’s data 🚀

At Cognism, we pride ourselves on the quality of our B2B data.

We’ve assembled a world-class team of AI experts and data scientists who developed Revenue AI, our patented technology.

It deploys a unique combination of computational, statistical, and machine learning methods, to deliver the best possible B2B data to our clients.

Here’s how our data found decision-makers for our clients:

Ice Blue Sky

Their biggest challenge was filling the funnel for their customers.

“We found there weren’t enough quality leads going into the top of the funnel. MQLs were being generated from events and content downloads, but these tended not to be the senior decision-makers the client was after.”

-  Charlotte Graham-Cumming, Managing Director, Ice Blue Sky

Cognism generated detailed lists with many decision-makers, influencers for bulk emails, and highly targeted lists for ABM campaigns.

The result?

“We’ve generated many new, better quality leads thanks to Cognism and consequently, we’ve seen a lot more interactions with campaigns. Our MQL to SQL conversion rate for one particular client is now 75%, and 50% for conversion from sales qualified lead to forecasted opportunity. The quality of the contacts supports the campaigns we are running very well, and these are great conversion numbers.”


Projects36’s main challenge was around data quality. They needed to make sure that they were working with the best-quality data on the market, to execute ABM programmes at enterprise-level.

“We were looking to identify extremely senior prospects in the financial sector, which historically has always been a challenge.”

- Joe Birkedale, Founder and CEO, Project36

Project36 used Cognism’s data to help their clients find senior decision-makers across a range of industries for the ABM programmes that Project36 runs for them.

These targets are very senior and are often high net-worth individuals, so they’re not always easy to identify. Then, Project36 deployed Cognism’s automated email function to engage with those senior-level prospects.

The result?

“We’ve seen contact engagement rates of 70%, 700-800 webinar registrations, over 500 webinar attendees, and 98% engagement rates during webinar broadcasts. Cognism’s data helped us to attract some great thought leaders to commit to our content, which meant that it was impactful and well-attended.”

Joe added:

“Our customers know that the data we use is best-in-class and totally compliant with the GDPR. At Project36, our mantra is to make data-driven business decisions - so it makes sense for us to be partnered with the best B2B data company in Europe.”

Need better data? 👩‍💻

If the dangers of poor quality data have been impressed upon you and you’re wondering “where to go from here?”, we’ve got your covered.

Cognism’s globally compliant data is constantly evolving and trusted by over 700 companies worldwide.. We’ll provide you with real-time, accurate data that you can trust.

Try our data, book your demo today 👇Request your demo now

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