More leads means more sales, right? Not necessarily. If there are enough low-quality leads in your pipeline, your sales team can easily waste hours chasing people who were never going to make a purchase. For this reason, knowing how to generate high-quality leads is an essential skill.
There is no universal strategy for efficient lead generation. But one principle that seems to apply almost everywhere is that you need high-quality data to identify high-quality leads.
In this post, we’re going to explain why — and show you how to use data, within your own lead generation campaigns, to capture more great leads.
In simple terms, a high-quality lead can be defined as anyone who is very well suited to your offer. This means they are likely to make a purchase down the road.
Where do you draw the line between low-quality and high-quality leads? There is no standard, so every business needs to create their own benchmark here. However, there are frameworks you can use for ranking the quality of your leads.
To know whether an individual or business is likely to become a future customer, you first need to do some research. The more you can learn about each contact, the better informed you will be when deciding whether they are a marketing qualified lead (MQL).
Of course, your decision-making is guided by information you collect. And not all data is worth taking into consideration.
For example: community-managed sites may offer interesting insights, but not all of them will be accurate. In contrast, data collected through your own site, or supplied by a reliable sales intelligence company, is more likely to reveal the most promising buyers.
With this point in mind, it’s worth considering how you can get better data into the hands of your reps.
There are many different ways to introduce data into your lead generation strategy. That said, there are three key steps that any business can implement in this area in order to see better sales outcomes.
Let’s take a look at each of them now.
Before you start going after new leads, it’s important to pinpoint the characteristics of your dream client — their age and job title, the size of the company they work for, and so on. Using this data, you can create your very own ideal customer profile (ICP).
The purpose of building an ICP is so that you have a solid yardstick for sizing up new leads.
Say your ICP is aged 25–35 years old, and works in middle management at a hospitality business with over 100 staff. To track down high-quality leads, your sales team simply needs to find people who match this buyer persona.
The process of creating any ICP should involve a lot of data. While you may be able to make sweeping generalizations about the kind of people who often become customers, your assumptions might be wrong.
For this reason, it’s important to gather as much intelligence as possible about previous customers. Some key data points to look at include:
- Job title
- Company size
- Company revenue
- Work history
- Professional connections
In addition to all this personal information, it’s a good idea to consider the needs and wants of potential customers. What are their current pain points? What kind of solutions are they looking for?
The answers to these questions can not only guide your marketing strategy, but they can also shape your lead nurturing.
With your ideal customer profiles in place, your marketing team can begin work on content marketing for a specific target audience, and your sales team can start identifying likely buyers. But it’s worth bearing in mind that these efforts may be hampered if your data isn’t up to scratch.
More specifically, your teams need data that is both highly accurate, and deep enough for drawing meaningful conclusions.
If you were to verify all the data in your CRM by hand, you might be surprised by the number of mistakes. Human error will play a part, but a more common issue is data coming from unreliable sources. Over time, some records also become out of date.
There are several ways to address this problem. First, it’s a good idea to run some basic automated checks. Tools like NeverBounce allow you to verify every email address in your database, and remove the dead wood.
You could also search for duplicates, and identify any incomplete records. Where your records are complete, consider trying to establish where the data came from. The last thing you want is to be utilizing contact details that have been gathered illegally, for example.
Assigning someone to the role of data verification is a good way to ensure that your CRM only contains useful information.
Going forward, consider how you can improve the overall quality of the data you have stored. A good place to start is with a reputable data provider. These companies provide B2B marketers and sales reps with verified information, taken either from the web or ethical sources.
Any information you get from your provider can be cross-referenced with other sources, such as website metrics and social media profiles. Adding extra tracking features to your site can also help to paint a more accurate picture of potential customers.
To figure out which leads are high quality and which are time wasters, you need a lead scoring system.
This is a formula that uses data to predict the likelihood that any given lead will eventually make a purchase. You should end up with a single score, allowing you to place new leads in order of priority.
A quick Google search will reveal a dozen different formulas for lead scoring. However, the most effective systems are usually based on three key pillars.
The amount of times a person has interacted with your brand is a good indicator of their interest in doing business.
Examples of noteworthy engagement includes:
- Signing up for a webinar
- Clicking CTAs on your landing pages
- Opening your marketing emails
- Engaging with your social media posts
- Visiting your SEO content
When a lead completes one of these actions, their score should increase. The amount of points you assign to each form of interaction should be dictated by data. For example, if signing up for a webinar is a strong buying signal, make it worth a lot of points.
Obviously, engagement means nothing if a lead doesn’t have the resources or authority to make a purchase. For this reason, qualification should be an important part of your lead scoring system.
Your formula should give the biggest scores to people who have a genuine chance of buying in the near future.
This is an important distinction, because the majority of leads who may eventually become your customers are not actually ready to pull the trigger. As such, you shouldn’t be trying to force them down your sales funnel.
Higher-quality leads also tend to have a very strong product fit. This connection usually results in better retention rates, and more value over the course of your business relationship. As such, you should work this into your scoring system.
As you devise your lead scoring system, the other factor to bear in mind is data quality.
As we discovered earlier, the quality of your data can have a real impact on your decision-making. The same applies when it comes to lead qualification and scoring.
The key metrics to focus on here are age, completeness, and relevancy.
Age tells you how fresh your data is. Data from recent activity should pump up the score of associated leads; your salespeople need to be alerted so they can strike when the iron is hot.
Completeness shows you whether you can see the full picture for any given lead. You might have a couple of good indicators, but there is no point chasing people who haven’t passed other key tests.
Relevancy plays a very important role in your scoring system. You may have an 80% complete data profile for any given lead, but the other 20% might be the part that really matters for your campaign. This metric deserves significant weighting, but you need to choose the parameters very carefully.
If you can implement the strategies above, your chance of generating high-quality leads and converting those individuals into paying customers is sure to increase.
However, there is a more important takeaway here: better data leads to better conversion rates.
The correlation isn’t obvious at first. But as we have discovered, good data can inform your outreach, shape your inbound marketing efforts, and help you prioritize the best leads. It’s actually an essential ingredient of digital marketing as a whole, and of effective lead generation.
So, how do you find better data? A good place to start is with Datanyze.
In seconds, our user-friendly Chrome Extension can reveal contact details for anyone with a LinkedIn profile or company profile page.
This means you can quickly collect accurate data on decision-makers and business owners — vital for email marketing, cold calling, and other tactics. There are over 120 million professionals in our database, and all the data comes from sources that comply with GDPR and CCPA.
Datanyze also provides key company data, and every new contact is automatically added to your online account. It’s a pretty smooth workflow.
Sign up today for a free 90-day trial to find out how easy it can be to collect high-quality data!