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Lead generation optimization

Turn more of your traffic into qualified leads.

We help lead generation teams find where prospects are dropping out, why they are hesitating, and what changes can improve both conversion volume and lead quality.

repeatGROWTH combines funnel analytics, usability research, messaging analysis, form optimization, and experimentation to improve the path from first visit to qualified lead.

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More leads matters. Better leads matter more.

The lead generation funnel

We optimize the full path from interest to qualified lead.

Lead generation rarely breaks in one place. We look across the funnel to understand where intent is being lost, where friction is being created, and whether the experience is attracting the right prospects in the first place.

  1. Landing pages

    Message match, value proposition, trust, hierarchy, calls to action, and whether the page gives prospects enough reason to continue.

  2. Forms

    Field count, sequencing, question clarity, progressive disclosure, validation, friction, and the tradeoff between volume and qualification.

  3. Multi-step funnels

    Step order, commitment, progress, transitions, optional questions, and where prospects abandon before completion.

  4. Offers and calls to action

    How the next step is framed, whether expectations are clear, and whether the action fits the prospect's level of intent.

  5. Lead quality

    We look beyond form completion to qualification rate, revenue per lead, sales acceptance, and other available quality signals.

What makes a lead program work

More form fills only help when the leads are worth having.

Lead generation gets harder when teams optimize only for completion rate and lose sight of who is converting and what happens after the lead is captured.

Volume and quality get optimized together

We watch qualification alongside completion, so easier forms do not quietly lower the value of every lead.

Instead of optimizing for volume alone

Hard questions come at the right moment

High-intent questions arrive once the prospect has enough confidence and context to answer them.

Instead of asking too much too early

The whole path tells 1 story

Ad, landing page, form and follow-up make the same promise at the moments that matter most.

Instead of messaging that drifts apart

Measurement follows the lead downstream

We push measurement as far past the thank-you page as your data allows.

Instead of stopping at the form fill

How we work

We find where intent is being lost and test better paths forward.

  1. Step 1 of 6

    Map the funnel

    We review traffic sources, landing pages, forms, steps, completion rates, and available downstream lead-quality data.

  2. Step 2 of 6

    Understand the prospect

    We combine analytics with usability testing, session behavior, surveys, and messaging review to understand why prospects hesitate or abandon.

  3. Step 3 of 6

    Prioritize the opportunity

    We identify the parts of the funnel where the combination of traffic, friction, and business value makes testing worthwhile.

  4. Step 4 of 6

    Design, build, and run the experiment

    We create the variation, build the test code, QA the experience, and launch the experiment ourselves.

  5. Step 5 of 6

    Measure more than conversion rate

    We evaluate the primary conversion metric alongside the downstream quality measures available to the business.

  6. Step 6 of 6

    Hand off what worked

    When a variation wins, we provide the tested code, findings, and implementation guidance so your team can put the better experience into production.

Our approach

Funnel data tells us where. Prospects help us understand why.

Analytics can show us where prospects abandon, which traffic sources underperform, and where completion rates change.

What it cannot tell us is whether someone did not trust the offer, misunderstood the question, felt the form was too invasive, or was not ready for the commitment being asked of them.

That is why we combine quantitative data with direct observation of how real people experience the funnel.

Quantitative Tells us where to look.
Qualitative Helps us understand why.
Experimentation Tells us which solution performs better.

Beyond the form fill

The best lead-gen metric is the one closest to revenue.

Not every business can connect every lead to revenue, but we push measurement as far downstream as the data allows.

Conversion rate

How many qualified visitors complete the desired action.

Cost per lead

Whether the experience is making paid traffic more efficient.

Qualification rate

How many captured leads meet the criteria that matter to the business.

Revenue per visitor or lead

When available, we look at the value being created, not just the number of submissions.

Side effects

The measures that could improve on paper while making the business worse in practice.

Practical outputs

Better funnels come from better evidence.

Depending on the engagement, the work may include:

Funnel analysis

A clear view of where prospects enter, advance, abandon, and convert.

Usability findings

Mobile and desktop recordings showing where prospects hesitate, get confused, or lose confidence.

Form and flow recommendations

Specific opportunities to improve field strategy, sequencing, step order, and commitment.

Messaging recommendations

Ways to improve clarity, trust, message match, and the perceived value of taking the next step.

Experiment roadmap

A prioritized set of tests based on impact, traffic, testability, and downstream business value.

Who this is for

Built for lead generation businesses where small funnel improvements create meaningful value.

Common models Insurance, legal, financial services, home services, marketplaces, B2B, and comparison sites.
Works especially well when The funnel has multiple steps, qualification questions, paid acquisition, or big differences in lead quality.
Best fit

Companies with meaningful traffic, measurable lead flow, and enough downstream value that improving conversion or quality materially affects revenue.

If the value of a lead varies, we want to understand that before optimizing the funnel around the wrong outcome.

Pricing

Scope depends on the funnel, traffic, and the depth of measurement available.

Lead generation programs are scoped around the number of funnels, experiment volume, research needs, and the downstream metrics we can connect back to the experience.

We do not price from a generic package. We start with the data, identify where the opportunities are, and build the engagement around what is actually worth testing.

Longer programs let the learning from each experiment improve the next one.

Start with the funnel

Let us show you where your lead funnel is losing value.

We review your analytics, walk the funnel, conduct mobile and desktop usability tests, and examine the pages, forms, and steps that matter most.

Then we show you where prospects are dropping out, what may be causing the friction, and which opportunities we would prioritize testing first. When downstream lead-quality data is available, we include it so we are not optimizing for volume at the expense of value.

You keep the evaluation deck and usability recordings whether we work together or not.

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Questions

What lead generation teams ask before starting.

Do you optimize for lead volume or lead quality?

Both, when the data allows it. A higher conversion rate is useful only if the resulting leads are still valuable to the business.

Can you optimize multi-step forms?

Yes. Multi-step forms are often one of the strongest opportunities because step order, question strategy, commitment, and progress all influence completion.

Do you work with paid traffic funnels?

Yes. Paid acquisition often makes this work especially valuable, because even a modest improvement in funnel performance can materially change cost per lead and return on ad spend.

Will you remove form fields to increase conversion?

Not automatically. Fewer fields can improve completion, but they can also reduce qualification. We look at the business purpose of each question before recommending a change.

What metrics do you use?

Depending on the data available, we may evaluate conversion rate, cost per lead, qualification rate, revenue per lead, revenue per visitor, and downstream sales performance.

Do you build the tests?

Yes. We design and build the experiment, QA it, launch it, and measure the result. When a variation wins, we hand the tested code and findings to your team for production.

How much traffic do we need?

It depends on funnel volume, conversion rate, and the size of the effect we are trying to measure. We evaluate testability before recommending an experimentation program.

Find where your lead funnel is losing volume, quality, or both.

We will review the data, test the experience with real users, and show you where we would focus first.

Request an evaluation

Funnel analysis. Mobile and desktop usability testing. Prioritized recommendations. You keep the findings.