Introduction

Best outbound practices are constantly evolving. However, cold email seems to be always part of the game, whether it’s as a standalone or as a part of a multichannel sequence. On average in B2B, the ROI of a multi-channel campaign is 24% higher than a single-channel campaign (Supersend, 2024). 

However, your sequence is only as good as its deliverability. In a lead generation process, losing most of your contacts because you don’t have their emails or, worse, sending emails to the wrong addresses is a real pain.

In this article, we will test different providers to ensure you get the best email coverage and quality. We will also cover how you can optimize your email discovery process by combining your email finders with the waterfall enrichment method.

Quantifying Success: Coverage and Quality

To find up to 90% of email addresses, we focused on the following email providers: Datagma, Dropcontact, Hunter, Prospeo, Findymail, and Icypeas.

Coverage

The first aspect tested in this email discovery process was the coverage. By coverage, we mean the number of contacts where the provider was able to find an email divided by the number of leads at the start.

%coverage = (number of emails found / number of leads at the start) x 100

The data to test the coverage comes from LinkedIn Sales Navigator searches. In total there were 850 leads, split into batches of 200 to 250 leads according to their company size and location:

• French companies with 51 to 200 employees, among whom 5 to 20 are in the Business Development department
• French companies with > 200 employees, among whom > 20 are in the Business Development department
• Companies based in the US with 51 to 200 employees, among whom 5 to 20 are in the Business Development department
• Companies based in the US with > 200 employees, among whom > 20 are in the Business Development department

In terms of buyer persona within these companies, we mainly focused on Sales, Marketing, Growth, and Operations roles.

The process is straightforward: run the input file with all of our contacts within the different tools. In our case, we use the specific Captain Data workflows to find emails with Datagma, Dropcontact, Hunter.io, Prospeo, Findymail, and Icypeas.

If you’re reproducing this analysis to your own ideal customer profile and buyer persona, make sure that you input columns corresponding to the leads’ criteria to simplify the result interpretation. For example, we used the columns original_group as meta in our workflow to be able to know where the lead was coming from. Without this information, it would have been a lot harder to differentiate contacts between Europe and America.

To get the results from your analysis you simply have to download the output file and compute the sum of emails found divided by the original number of contacts you had in your input file.

For example, if we had 850 contacts at the start and Dropcontact was able to find 650 emails, we would have:

%_coverage_Dropcontact = (650 / 850) x 100 = 0.765 * 100 ≃ 77%

To count the emails more easily, you can use the COUNTA formula that counts the number of variables in a set range:
=counta(O_Dropcontact!D2:D1000)

Below are the results from our coverage analysis, we will show you how to attest to the quality of these emails and how you can use that to maximize your results in a second!

Quality

The second part of this analysis is focused on the quality of these emails, meaning whether or not they correspond to the right person. The risk of a poor-quality email is for it to bounce as soon as it is sent, which then hurts your domain reputation. If you send poor-quality emails at scale, there is even a risk of blocking your email.

Quality is thus established as the number of valid emails divided by the number of emails found. 

%quality = (number of valid emails / number of emails found) x 100

However, how can we measure whether an email is valid or not?

The first approach is to look at the data providers themselves give you. Indeed, in the different output files you can find some type of email scoring already. In our analysis:

• Most providers give an email status: valid, catch-all, catch-all@pro, accept-all, unknown, invalid...
• Icypeas shows a deliverability score, that is usually 99% or 90%
• Datagma outputs emails that they consider valid in the email column as well as another output column that is “Most Probable Email” where they store what other providers would consider as catch-all

Below is the breakdown per provider of the number of emails found in the previous coverage analysis versus the number of emails they consider as valid/not risky.

What is critical to note here is that despite Datagma, Findymail, and Icypeas scoring poorly on coverage, the emails that they do have seem to be more qualitative, still according to their statuses.

Another proactive approach to optimize deliverability is to add a validation tool to your email discovery process, such as Neverbounce, Bouncer, or Zerobounce. These tools will take the email that was found by the providers and output an additional email status. Common statuses are: valid, deliverable, invalid, unknown, risky, catch-all…

For this research, we decided to use Bouncer as an email validation tool on the same batch of contacts used previously.

It’s interesting to note that we have approximately the same percentages of good emails when the provider tags it as valid and with an email validation tool for Prospeo and Icypeas. However, Hunter.io and Dropcontact tend to tag more emails as risky within their tools than what we identified with Bouncer. The opposite happens for Datagma and Findymail. Overall, the less risky emails seem to be found in Findymail, Datagma, and Icypeas.

The third approach we will dive into to verify the quality of emails found by the providers is to work on a batch of emails that we already sent. 

For this research, we are using another dataset of 1085 leads whose companies are split equally between Europe and North America. The company size of these companies is between 11 to 500 employees, mostly in the tech and consulting industry. The profiles of these leads are still in Sales, Marketing, Growth, and Operations positions.

However, it is important to note that the leads in these campaigns were mostly discovered by Dropcontact, which is biased. We will update this article with the data from our first batch in a few months but, in the meantime, these results are to be interpreted with caution.

In this batch, most providers have close scores in terms of coverage and quality. Datagma is the only one that stands out by having considerably fewer emails found but, when found, of a pretty good quality.

Best Practices for Implementing Waterfall Enrichment

In the analysis we just did, we enriched a set of leads with multiple email finders. 

Imagine how long it would have taken us to go inside each of these 6 tools, import the input file, make sure the columns match, go back after 30 minutes to see which jobs are over and which ones still need time, and download the results… not ideal. 

In our case, we used Captain Data’s workflows for the different integrations:

• Find email Hunter
• Find Email Prospeo
• Find Email Findymail
• Datagma Find email
• Find Verified Email Dropcontact
• Find email Icypeas

The good news is that it takes 10 seconds to create a new job, import the file, and launch within Captain Data.

However, it’s still not ideal. It takes time and, as you can see, different providers have different scores for different emails.

That’s why Captain Data created the email waterfall back in 2021: to be able to optimize your email discovery process. From moving between the different tools or APIs, Captain Data was one of the first to introduce this concept of combining several email finders to optimize coverage. 

Captain Data’s email waterfall looks like this:

You have several email finder options available: Prospeo, Dropcontact, Hunter, Datagma, Findymail, Kaspr, Lusha, Apollo, Zoominfo, SocieteInfo as well as Captain Data credits!

How the waterfall works is that it will run through each tool in the order you select and stop as soon as it finds a valid email address for the lead.

Furthermore, since we enhanced in our research the importance of quality, you also have a validation step that you can choose to use or not to confirm whether the email found is valid between each provider. To do so, Captain Data is integrated with Bouncer, Neverbounce and Zerobounce.

But how do you know who to put first? As you maybe noticed in the screenshot above, we have recommended orders based on your leads’ location: France, Europe, the United States, and Asia.

Based on this article’s coverage and quality results, here is the order we would recommend for:

France

• Dropcontact
• Hunter 
• Prospeo
• Findymail
• Icypeas 
• Datagma

Europe

• Hunter
• Dropcontact
• Prospeo  
• Findymail
• Icypeas 
• Datagma

United States

• Hunter
• Dropcontact
• Prospeo 
• Findymail
• Icypeas 
• Datagma

Keep in mind that these recommendations are based on the results we found in our leads samples, it is a pretty good start, but it might be different if your target is different. 

We recommend you to test the different providers on your own ideal customer profile and buyer persona to see what would work best for you. 

Next up, we will go over how you can use the waterfall enrichment method with Captain data to craft your own email discovery process! 

The Waterfall Enrichment Method with Captain Data

Detailed breakdown of the waterfall enrichment process tailored by Captain Data:

• Stage 1: Identifying the target audience through Sales Navigator for specific regions (e.g., France and the US).
• Stage 2: Utilizing Captain Data’s workflows to automate the discovery of email addresses across multiple email finders.
• Stage 3: Computing coverage and valid email percentages against total leads, emphasizing the importance of data quality.
• Stage 4: Applying email verification steps to ensure the highest quality of collected emails.

Identifying your target audience

The first step in this process is to determine the scope of this test. To do that, here are a few questions that we recommend you take a minute to answer:

• What is my ideal customer profile? Think about the company size, specific industries etc.
• Who is my buyer persona? Think about their position in the company, whether how long they have been in the company matters, if there’s anything specific keyword that interests you.
• Which geography am I interested in? Is it based on the lead? The company?
• Which email finders will I be comparing?

Based on the answers from above, you can build a list of companies and/or leads that will be the start of your workflow.

Utilizing Captain Data’s workflows to automate the discovery of email addresses across multiple email finders.

In this example we’re starting from LinkedIn Sales Navigator searches but keep in mind that you can also find leads with email by starting from their domain, full name, company name, Google Maps company page and so much more!

If you’re starting from a LinkedIn Sales Navigator Leads search, you can use the Find leads with email from Sales Navigator Search workflow. This will directly extract and enrich the leads.

If you’re starting from a LinkedIn Sales Navigator Account search, you can use the workflow Find Leads with email from Sales Navigator Company Search. In this workflow you will be able to get specific account filters and information, search for the right contacts within this company and find their emails, all-in-one.

The goal here is to have several lists that will cover your overall ideal customer profile and buyer person. To perform a relevant test, we highly recommend to test more than 500 contacts and segment at least by location.

Achieving the best data quality

As we said before in pt. 3, you can use the standalone workflows to be able to compute the coverage and quality scores of each email. 

In our research we established them as:

• %coverage = (number of emails found / number of leads at the start) x 100
  
  
• %quality = (number of valid emails / number of emails found) x 100

Once you’ve established the scores of each provider on each list, you can sort them from the highest coverage to the lowest. We recommend to add a double verification step for the providers who score less than 90% in terms of quality to ensure the emails you have are deliverable.

Finally, since you established the best email discovery process for your audience, you can set up the email cascade accordingly in your Captain Data workflows.

Why Captain Data is more advanced than its alternatives

Captain Data’s custom workflows enable you to add the email waterfall step in pretty much any workflow where this is information about the lead and the company.

Email finders usually need ​​the lead’s first name, last name, full name, company name, website or domain and sometimes country information to give you the best coverage.

Captain Data is integrated with many tools to optimize your email discovery process, each step of the way!

In terms of lead sources you’ll be able to get data from LinkedIn, Sales Navigator, SocieteInfo, Zoominfo, Google, Google Maps, Tripadvisor, Yellow pages, Glassdoor, Seek, Product Hunt, Wappalyzer…

Then you can find your contact’s email with Prospeo, Dropcontact, Hunter, Datagma, Findymail, Kaspr, Lusha, Apollo, Zoominfo, SocieteInfo, Icypeas and Captain Data. Just add an email validation step with Bouncer, Neverbounce and Zerobounce. Use Captain Data’s bundled credits to avoid having to buy subscriptions with each provider!

Each provider has different email status to say whether an email is valid or risky, but Captain Data normalizes the statuses automatically so you don’t have to handle these specific cases.

Once your leads are enriched, you can push them directly to your CRM, whether it’s Hubspot or Salesforce… or a Google Sheets.

You can also add a step at the end of your workflows to push the leads with email to your outreach tools. We’re integrated with Lemlist, Reply, La Growth Machine… or Make if you can’t find what you need.

The best part of it all is that everything flows seamlessly between each step. You can even schedule workflows to get new results from week to week without lifting the finger! 

Real-world Success Stories

Most of our customers use the email waterfall, whether it’s for a lead generation use case or to enrich emails from their CRM.

Today we’ll focus on the Anode Agency who generates 10+ qualified meetings per week by using Captain Data’s automated Find leads with email from Sales Navigator search & Hubspot.

Their process is streamlined for maximum efficiency: from micro-segments on LinkedIn Sales Navigator, they get enriched companies and leads with emails who are pushed in Hubspot and then directly to Lemlist campaigns. They have a ROI of x10 for Captain Data. 

Timothée Franc, the guy who implemented the process for Anode, says 

“You get the full value of Captain Data by building workflows that let you go far beyond LinkedIn, and when you automate those searches. Anode is now set up to automatically have their outreach launched on a weekly basis, with rolling windows looking for people who have just changed jobs. We have a bunch of dynamic filters set up, and the process gives reliable results that can be fine-tuned as time goes on.”

Conclusion

In this playbook we showed you how you can reach more than 90% of emails found. We researched our own audience to give you recommendations of providers based on geography. However, we also mentioned that in order to have something that is 100% relevant for you, it’s best to perform this analysis on your own ideal customer profile and buyer persona! Once you know the best combination for you can set that up in your Captain Data workflows to be able to optimize your email discovery process!

Captain Data's advanced features, including customizable workflows and seamless integration with various tools, empower users to streamline their lead generation strategy and achieve significant ROI (x10 for Anode).