How to get more leads: sources, offers and lead quality

If you're working out how to get more leads, judge sources and offers by the qualified leads and sales they bring. Raw lead count is the wrong yardstick. Tag every lead with its source and offer, and write the qualification rule before you compare anything. Then compare channels by cost per qualified lead over the same observation window, and move budget on that number.

A lead is a person who leaves contact details and could enter a quote or sales process. Lead volume and lead quality are separate numbers. A channel can double sign-ups and leave qualified leads flat. When most of the new leads never buy, more leads only add work and cost.

Form fields and landing page design are outside the scope of this post.

The first unit to count is the unique person who leaves contact details. If one person fills in two forms, that's one lead. Otherwise you end up counting forms instead of people.

The second count is the qualified lead: a lead that sales, or a rule, marks as meeting a criterion written in advance. The third is the converted lead, a person who pays within a fixed period after the lead was created.

Tools count the same three stages under different names. HubSpot's lifecycle stages article puts someone who only signs up for your blog or newsletter in the default "Subscriber" stage. A "Lead" is someone who converted on your website or interacted with you in another way "beyond a subscription sign up" (HubSpot's words). The same page separates a marketing qualified lead (MQL) from a sales qualified lead (SQL).

The SQL is the one sales has qualified as a potential customer, and "qualified lead" in this post sits close to it. If you count newsletter sign-ups as leads, write that into your definition. Every row you compare has to use the same one.

Google's tools draw the same lines. Google Analytics' recommended events include generate_lead for a form submission.

A lead "marked as fitting the criteria to become a qualified lead" triggers qualify_lead. A lead that "became a converted lead (a customer)" triggers close_convert_lead. Google Ads has two goal types, qualified leads and converted leads, and both work from your offline conversion data.

None of the three stands in for another. Lead count shows how many records a channel brings. The qualification rate shows how many of them are useful to sales. The conversion rate shows how the process after the offer is working.

Whether a lead counts as qualified should depend on one written rule set before the comparison starts. The rule depends on your business. It might be your service area, a budget range, company size, decision authority or when the need will arise. If the rule changes mid-period, the gap between channels carries the rule change too.

Who applies the rule is part of the definition. If sales marks leads, they should also pick a reason when they reject one.

Google Analytics recommends disqualify_lead for this. It fires when a lead "is marked as disqualified to become a lead for one of several reasons", in the page's words. Rejection reasons tell you which channel a low qualification rate comes from, and why.

Every lead record needs these fields:

• Source and campaign: UTM (Urchin Tracking Module) parameters carry the source from ad and email links into the record. You can build the links with the UTM builder.
• Offer: demo request, price quote, downloadable guide, free trial or webinar registration.
• Created date: the day the observation window starts.
• Qualification decision, its date and the rejection reason.
• Sale and its date.

HubSpot's lifecycle page also defines a "Date entered [stage]" property for each stage. It stores when the record entered that stage. From these dates you can work out the days from lead to qualification, and from qualification to sale. You'll need that gap when you pick an observation window.

The source is the channel a person came through. The offer is what they got in return for their contact details. Search ads, paid social, organic search and content, customer referrals, events and partners are sources. Demo requests, price quotes, downloadable guides, free trials and webinar registrations are offers.

More leads come from three directions. You can reach more people through an existing source, show the same visitors an offer more of them accept or open a new source. Each one affects quality differently.

An offer that asks for less commitment may also bring people who aren't ready to buy. That's a possibility to check in your own data, not a rule.

Google Ads' guide to high-quality leads suggests adding lead form assets to Search, Performance Max, Video and Display campaigns. With that asset, a person submits their details inside the ad itself. That's another source and offer combination. Keep the source and the offer together as one row in your reports, since one ad channel can show two qualification rates with two offers.

Sales capacity and the current qualification rate decide which one comes first. You can track capacity with two numbers. One is the time from lead creation to first contact. The other is the number of open leads nobody has called by the end of the week.

If sales can reply to new leads the same day and still has spare capacity, try to raise volume. Watch that the qualification rate doesn't drop while you do. If the team reaches qualified leads late because it spends its time screening poor-fit ones, raise quality first. New leads would only lengthen the queue in front of the qualified ones.

When qualified leads don't turn into sales, the problem may not be lead generation at all. A slow reply to a quote, an unclear price or missing follow-up messages produce the same picture. Following up with leads who are interested but not ready yet is covered step by step in the lead nurture journey.

A hypothetical business runs three source and offer combinations in the same 90-day period. Every lead is a unique person. Spend is the media and production cost paid for each channel in the period: $30,000 each for A and B, and $12,000 for C.

Qualification comes from sales, against one criterion written before the period. A sale is a payment within 60 days of the lead's creation, and every lead in the period has completed those 60 days.

Switching the ranking from cost per lead to cost per qualified lead moves B from first place to last. B brings the cheapest leads but becomes the most expensive channel per qualified lead.

The rule "move budget to the channel with the cheapest leads" picks B here. Yet only 6% of B's leads qualify, against 40% of A's, and B is the most expensive of the three per qualified lead. Someone who looks at cost per qualified lead picks C, and someone who looks at cost per sale picks A. So each of the three measures puts a different channel first.

These sales counts are small, so the cost-per-sale ranking is open to chance. Suppose two more of C's 40 qualified leads had bought within the window. C's cost per sale would then match A's at $2,000.

B's qualification rate is the assumption that drives the decision. At a 10% rate, B would reach 60 qualified leads and match A's cost of $500.

At 15%, B's cost per qualified lead would fall to $333. That's still above C's $300.

The gap in the table isn't a gain. The example doesn't assume extra budget would bring leads at the same rates. Nobody measured what moving B's budget to A would return. The performance marketing metrics post explains how to judge added spend by its marginal return instead of the average.

A channel's leads need time to turn into sales, and a new channel hasn't had that time. Say you compare a content channel that started last month with search ads that have run for three months. The content channel's sales will look low, because many of its leads are still open.

Group leads by the week or month they were created and give every group the same observation window. Pick the window from your own data. Look at the spread of days between lead and payment in past sales, and choose a window that covers most of them.

A lead that's still open on the day you measure isn't lost. Keep it apart as "not resolved yet" and count it again once its group completes the window.

Spend and leads should come from the same period too. Dividing one month's ad spend by the next month's leads mixes two different periods. If your business is seasonal, compare channels over the same calendar period.

An ad platform that only sees form submissions can't know whether a lead was later qualified. Google Ads' page on qualified and converted leads defines the qualified lead goal by what it tracks. It "helps track Google generated leads that have also been further qualified offline (outside of Google Ads)", for example in customer relationship management (CRM) software. The same page describes a lead funnel report with volumes from interactions to leads, qualified leads and converted leads.

Google Ads' guide to high-quality leads raises a few points about the goal you bid toward. It advises against picking goals from more than one stage of your lead journey. It asks you to make sure the action produced at least 15 conversions in the last 30 days at the account level. Ideally, the action should happen within 7 days of the ad interaction.

One inference follows from that guidance. Take a business where sales close weeks after the lead and only a few close each month. Bidding on sales there may not meet those points.

Qualification happens before the sale and usually more often, so it may suit bidding better. Your own account's conversion counts and delays tell you which one fits.

The same guide also suggests ReCAPTCHA, double opt-in or server-side validation to make sure leads are real. Fake sign-ups inflate lead count and pull the qualification rate down. Note the day you add a verification step in your records.

A randomized test is the most direct way to see whether a new offer raises lead count or qualified lead count. Assign visitors at random to two groups when they can first see the offer. The control group keeps seeing the current offer and the test group sees the new one.

Compare the groups by the unit you assigned: qualified leads per assigned visitor, not per person who accepted the offer. Apply the same qualification rule and the same follow-up window to both groups.

Write the decision rule before the test starts. Say which difference counts as a win, and which guardrail stops the test at what limit.

A drop in the main conversion (a purchase or a trial) is one candidate for a guardrail. A backlog that sales can't follow up is another. If the result is unclear, report it as unclear rather than as no effect.

The site's A/B test library has two test plans for this question. One asks whether a gated download brings better leads. The other asks what a request demo link beside start free changes. Both use qualified opportunities per assigned visitor as the primary measure.

Marketing emails you send to leads in the US fall under the CAN-SPAM Act. The Federal Trade Commission's compliance guide for business says the law "doesn't apply just to bulk email." It "makes no exception for business-to-business email" either. This summary is not legal advice.

The Act's own text, 15 U.S.C. 7704, requires commercial email to give a valid physical postal address and a notice of how to opt out. It also requires the email to say it's an advertisement, unless the recipient gave prior affirmative consent. Once someone opts out, you can't keep sending them commercial email more than 10 business days after the request. This is not legal advice.

If you collect leads in the EU and rely on consent, the General Data Protection Regulation (GDPR) sets what valid consent looks like. Under Recital 32, "Silence, pre-ticked boxes or inactivity should not therefore constitute consent", so a box ticked by default doesn't count. This is not legal advice.

Article 7 asks the controller to be able to demonstrate consent. Article 7(3) adds that withdrawing consent must take no more effort than giving it. Read this as a summary, not as legal advice.

Under Article 7(4), whether a service is conditional on consent to processing it doesn't need weighs heavily when judging if consent is freely given. One reading for lead offers is that tying a downloadable guide to marketing consent may raise that question. Ask for an email to deliver the guide, and collect marketing consent with a separate, unticked box. That reading goes beyond the text and isn't legal advice, so check your own form with your legal team.

To find out from your own data which source and offer to choose, work in this order:

1. Write the definitions of lead, qualified lead and converted lead on one page and agree them with sales.
2. Tag recent leads with their source and offer, and keep leads with an unknown source in a separate row.
3. Pick an observation window from the days between lead and payment, and compare only groups that have completed it.
4. Put cost per lead, cost per qualified lead and cost per sale side by side for each source and offer. Write the sales count next to them.
5. Pick one change for the row with the highest cost per qualified lead and test it against a control group.

To compare cost per sale with a customer acquisition cost (CAC) that includes all acquisition spend, use the CAC calculator.