Hopefully, the importance of quality in your B2B data has been demonstrated. But for those still on the fence and think it’s not such a big deal, here are a few ideas to see what the true cost of not using high-quality B2B data could be for your business.
- How lower email deliverability can affect sales revenue
Briefly mentioned earlier, outdated contact information can result in having lower email deliverability. Even though many of us focus on other more exciting metrics like open rates, reply rates and click-through rates, if the prospect isn’t even getting your email, all these other metrics will be directly impacted.
Let’s explore how this affects overall revenue.
The example earlier saw 100 prospects be sent an email but 15 were to a wrong or invalid email address. With an email deliverability rate of 85%, this immediately decreases the data’s overall potential by 15%.
To compare this against a benchmark figure, at hubsell, we guarantee our customers with data accuracy of at least 95%, but we’ll stick with 95% for example purposes.
Email open rate
Using an average email open rate of 60%, the number of emails opened would be the following:
100*0.85*0.60=51 opened emails, as opposed to;
100*0.95*0.60=57 opened emails
A reduction from 57 to 51 people results in having to send over 11% more emails just to get back up to 57 opened emails.
Email reply rate
Now, suppose we have an average positive email reply rate of 5% of those who opened an email, the number of email replies received would be the following:
100*0.85*0.60*0.05=2.55 positive replies, as opposed to;
100*0.95*0.60*0.05=2.85 positive replies
Although this may seem small, this example could very easily represent the email volume of a single sales rep in just a single day.
In one month:
2000*0.85*0.6*0.05=51 positive replies, as opposed to;
2000*0.95*0.6*0.05=57 positive replies
As we can see, 6 potential deals per sales rep per month is lost when we compare email deliverability between 85% and 95%.
Lost annual revenue
To demonstrate the impact on annual sales revenue, we shall assume the average close rate is 20%. Let’s look at how much potential revenue is lost using two different company examples from losing 6 potential deals per month:
Company A with an average deal size of £10,000:
6*12*0.2*10,000=£144,000 is lost per sales rep per annum
Company B with an average deal size of £100,000:
6*12*0.2*100,000=£1,440,000 is lost per sales rep per annum
Multiplying this lost revenue by the number of sales reps gives an even greater and truer look at the scale of the potential loss. As we can see, a mere 10% difference in email deliverability has disastrous effects on annual sales revenue.
- How a lack of personalisation can affect sales revenue
Personalisation plays a big factor in a successful marketing campaign. It shows the recipient that you thoughtfully targeted them and believe you can offer a solution that will help solve a potential pain point.
Your prospects are receiving numerous emails and messages every day. To stand out, you cannot afford to simply send generic content that could have been sent to anyone. Your prospects likely do not have the time to read everything they get sent and often decide whether to open an email or message purely based on the subject line and preview of the text.
The content of your message must be written specifically for each prospect which can be achieved by using your B2B data. Each job title has a different pain point, each industry faces different challenges, and every prospect has different levels of experience. Using your own personal knowledge along with these insights, you can gain a competitive edge by crafting a message that speaks to each prospect on an individual basis.
Some small personal touches to add would be to name their company in the subject line or compliment them within the first line so it appears in the preview. These alone can help to increase your email open and reply rates by a few percentage points each.
Increased email open and reply rate
Expanding on our earlier example, let’s compare how a modest 10% increase in open and reply rates will help generate more sales opportunities.
Low-quality data example:
2000*0.85*0.60*0.05=51 email replies per sales rep per month
High-quality data and personalised:
2000*0.95*0.66*0.055=68.97 email replies per sales rep per month.
As we can see, the difference has increased nearly 3-fold from 6 to 17.97 potential deals per sales rep per month being lost when email open and reply rate improves by just 10%.
Lost annual revenue
To further demonstrate the impact on annual sales revenue – still assuming the same 20% close rate – let’s look at how much potential revenue is lost using the same two company examples from losing 17.97 potential deals per month:
Company A with an average deal size of £10,000:
17.97*12*0.2*10,000=£431,280 is lost per sales rep per annum

Company B with an average deal size of £100,000:
17.97*12*0.2*100,000=£4,312,800 is lost per sales rep per annum

As we can see, the numbers get frighteningly bigger by improving email open and reply rate by just a few percentage points. Although this is just an example, very similar real-life scenarios can resemble this and we can quickly see how making small improvements at each step can exponentially improve the overall result.
- Mistargeting segments can lead to wasted effort and cost
There are many ways to segment your B2B data. The most common ways would be by using a mix of industry, company size and job title.
However, you can segment much more granularly by using other forms of B2B data such as firmographics, demographics, technographics, etc.
The level of granularity will depend on the data points you have for each contact and account. By not being able to clearly profile your data into segments, you will not be able to create a quality message that resonates with your target market.
While having more data points enables you to target your prospects with greater accuracy and focus, fewer data points will keep your message generalised and appear to be a one-to-many type message as opposed to it being one-to-one and tailored for each individual.
Having full visibility of your data, you will be able to understand why a certain campaign is performing well or what segment is resonating well for you. Focusing on the best performing segments and campaigns enables you to scale your winning approach to further optimise and generate more sales.
- Higher customer acquisition cost
Another cost of using low-quality B2B data is that you end up incurring a high customer acquisition cost. This could be due to time wasted on marketing to irrelevant prospects, paying for contacts with wrong or invalid data making them void, increasing sales cycle length due to mistargeting decision-makers, or paying more for data hygiene services.
From an email marketing perspective, contacts that have wrong or non-existing email addresses become unusable. The result is that any costs, whether it be time or money, spent on acquiring that contact and any marketing effort has gone to waste.
As we can see, if purchasing data, invalid email addresses alone can increase the cost per contact. Suppose you pay £200 for 100 contacts. If 10 contacts result in a delivery failure, the real cost becomes £2.22 p/c – an 11% increase in cost with added frustration and time lost.
If your B2B data does not have enough information, you may not be able to segment your data properly or be able to craft a tailored message. This may result in fewer conversions or a longer sales cycle if you misidentified a contact as a decision-maker.
Procuring data from an unreliable source or working from a questionable B2B database will not give you the confidence to execute a successful marketing campaign. There are some data hygiene processes that can ensure your data is clean and up-to-date such as cleansing, enriching and validating your B2B data. However, these services will cost time and money which further adds to the costs of sourcing data.