Lead generation businesses provide the service of building lead databases. Typically, their clients specify their description of an ideal customer by asking to look for a certain company size, with a certain revenue level, from a certain location, and so on. 

For quite some time, I’ve been working with such a startup myself, and I noticed how often the databases contain irrelevant contact information or names of long-retired decision-makers from target companies. So I found some hacks that could help any leadgen company distinguish itself from similar startups and ensure better lead quality. 

In this article, I’ll tell you about two things:

• What common obstacles are shared between most leadgen businesses, and 
• What your team can potentially do to make your startup stand out. 

So yes, I am currently building a leadgen startup. During our market research, we discovered many tools that can generate a lead list. As a rule, these are tech services and platforms able to find leads by specified filters: geography, industry, etc. However, we found significant problems in how these services processed leads.

Since it was likely that both our clients and competitors also used these tools for lead generation, we assumed that they must be experiencing these problems as well. We saw significant quality drops of lead lists that these tools generated, and since it was something our customers already had, we needed to be better. 

In other words, if we want to build more precise databases, our task is to find a workaround and solve the following three challenges.

The first problem was with inconsistency of information. Some tools we were using showed irrelevant contact details, such as emails of people who no longer work in the target company. We also noticed errors with determining the location of the lead.

For example, there was one time when a company turned to us for our services. It segmented its customers (Shopify stores) by industry, location, revenue, and traffic, so it wanted to get a contact list of decision makers in selected industries, in a certain country, and with the right number of visitors.

After researching the market, we found a tool called BuiltWith, and it seemed to be able to solve our task. We bought a trial version and downloaded the first 100 leads. These were supposed to be American stores from Shopify, but upon manual rechecking it turned out that these stores were not located in the United States and came from elsewhere.

Now, the next parameter. Indeed, BuiltWith showed revenue, but it wasn’t clear how the program calculated it. Without knowing the sources of information and methods of calculation, we could not guarantee the correctness of the data.

As for traffic, BuiltWith only showed if a target company had more or less than a million users visiting its webpage. This wasn’t what we were looking for in our segmentation, so we concluded we could not only use this tool. We needed something else for our technology stack, but it turned out that some other tools we tried (SimilarWeb, Semrush, etc.) had similar problems.

That’s how we defined our first challenge: it was unclear how to generate lead lists that only contained correct data. Overall, it’s quite common for data analysis: you always need to know what sources to address, which ones you can trust, and how much you can trust them.

The second problem is strongly connected with the previous one. Companies and analytical agencies post a lot of information in the public domain. For example, we can google the latest corporate news and see a company’s recent hires. Nevertheless, we don’t know how accurate this information is or how often the company updates these sources.

Thus, the quality of our lead generation directly depends on whether a target company has updated its data or whether a person has specified on Linkedin that they recently left their position.
But it’s not just about targeted companies. This coin has two sides, and here’s the other one: even if businesses update their data regularly, you don’t always know how often aggregators and services (such as Rocketreach, Leadfuze, etc.) sync up their database. There might be a scenario where the source has updated its webpage, but Rocketreach has not managed to do it yet.

So the first question here is how often a company or employee updates their data. The second question is how often the services update their databases. Unfortunately, we came to the conclusion that in the current environment, all we can do is to verify data manually after we sourced it from the platforms we trust the most. But if this source does not update its data timely, then there is nothing we can do.

Businesses that operate in the leadgen market should take these two things into account. These are the rules the market plays by, and we all have to abide — until, of course, we find a way to disrupt it. 

Our third and final problem is that all lead generation platforms take data from the same few sources: LinkedIn, HR databases, and so on. Their number is limited, so they are well known to all industry players. The scary thing is that these companies can deny access to their data at any time. When it happens, the industry will lose a significant share of its capacity.

For example, if LinkedIn shuts the valve off, we will no longer be able to verify our lead lists, and the search results of leadgen platforms will become much narrower. Thus, the situation is highly uncertain because you simply can’t predict when the great shutdown will occur.

Even if we are using the best sources and services, they might still have errors. So it seems that targeting tools like Semrush and SimilarWeb will always contain a share of inaccurate information. And the higher the number of leads in the generated list, the greater this share is.

At the moment, we believe there are no better alternatives than a human specialist who will thoroughly cross-check the generated lead list. But of course, it’s expensive, time-consuming, and does not guarantee a perfect result. Developing a solution that can automate this process would help to a certain degree, but then again, you will have to be manually checking how well this checker works. To sum it up: not cute.

Over time, your company will collect sufficient knowledge about the accuracy of different sources or their application in different cases. Knowing when it makes sense to turn to particular websites, systems, or databases, you can take different pieces of data from different sources and, in so doing, assemble your lead selection.

For example, we once generated a lead list for a studio. To do this, we took company data in one place, traffic data in another place, and decision maker data in a third place.

You can also run a few cycles of database generation using different tools and then compare them, looking for mismatches. This way, your customer will know the margin of error that these services allow.
Nevertheless, there is nothing that can solve the problems of outdated information and unstable, scarce data sources. This might possibly be the biggest challenge for the industry. 

There are three main problems with lead generation tools used to build lead lists.

1. Services provide inaccurate data.
2. Companies do not update their info.
3. Access to company data can be denied anytime.

Although the second and third one are currently impossible to solve, the first one can be addressed in the following ways:

1. Databases are checked manually.
2. Databases are pieced together from different sources.
3. You let your customers know about possible margin of error.

That’s exactly how our startup finds leads of better quality. Using various tools, the team tries to form the most accurate picture and avoid providing incorrect info. Then an employee goes over the results to verify leads and ensure that they are up to the customer’s request. We call it providing “more qualified leads.”

As a final word, I would like to say this. If you need B2B leads in the IT sphere, we can advise you on our lead generation model. In order for our potential clients to try our services, we generate a demo list of 100 leads for free. Having analyzed various approaches, tools, and methods, we will surely provide you with better leads than our competitors.