How to eliminate low-quality leads and improve conversion rates

I. Post-Click content and experience

Many campaigns generate a large volume of leads, yet the actual conversion rate remains surprisingly low. This issue does not stem solely from inaccurate targeting, but more critically from inconsistencies in messaging and the post-click experience delivered to users.

Common causes of low-quality or “junk” leads include:

• Clickbait-style ad messaging that creates misleading expectations, prompting users to click out of curiosity rather than genuine interest.

• Lack of alignment between ads and landing pages , where the post-click content makes users feel “tricked,” leading them to submit inaccurate information or abandon the page entirely.

Recommended improvements:

• Strong alignment between Performance and Content teams: Ensure ad messaging accurately reflects the intended target audience. Avoid overly broad messaging that dilutes qualification criteria. Content itself acts as an active filter for lead quality. Core messages (offers, key benefits, value propositions) should be consistently repeated and clearly emphasized on the landing page to support conversion optimization.

• Avoid excessive “clickbait” tactics or clickbait: The more transparent and honest the messaging, the stronger the user trust. While clickbait may temporarily boost clicks, it often undermines lead quality and long-term conversion rates.

• Optimize landing page UX/UI: The interface should be clean, intuitive, and easy to navigate. Forms should be prominently placed, with clear flow and minimal distractions. Avoid clutter that causes users to drop off mid-journey or submit inaccurate information.

• Build a multi-layered campaign structure: Combine awareness, consideration, and remarketing stages—running in parallel when appropriate—to filter users based on real engagement behavior, rather than relying solely on clicks or raw lead volume.

II. Lead filtering mechanisms within the funnel

Broad targeting can help reduce CPM or CPC, but it also increases the risk of attracting users with low intent or those outside the serviceable area. A simple registration form may generate a high volume of leads, yet it can also become a gateway for fake leads, incorrect information, or unqualified prospects. Conversely, overly complex forms with too many required fields can raise the cost per qualified lead and discourage completion. The key is finding the right balance between user experience and effective lead qualification. Below are several optimization tactics to reduce low-quality leads at the top of the funnel:

• Optimize registration forms: Instead of keeping forms overly minimal, add a few classification fields that remain user-friendly—such as current location, estimated budget, expected purchase timeline . These fields help identify genuine prospects without making the process feel burdensome.

• Use qualifying questions: For example: “When are you planning to purchase a car?” This simple question helps score lead quality early on while enabling flexible segmentation for later sales enablement.

• Add light, user-friendly verification steps: Reduce bot spam with simple confirmation elements such as checkboxes. Avoid overusing reCAPTCHA, especially on mobile devices, as it often harms user experience. Email or OTP verification can be considered later in the nurturing stage rather than at the initial form.

• Leverage engagement behavior instead of explicit intent confirmation: Instead of presenting a form immediately, use CTA buttons like “Learn More” or “Estimate Cost” to pre-filter users with real interest. This approach should be applied contextually to avoid disrupting the user journey when intent is already high.

III. Behavioral data

One of the biggest challenges in evaluating lead quality is the lack of post-click behavioral data. As user tracking becomes increasingly restricted, marketers can no longer rely solely on third-party data. Instead, they must proactively build internal measurement systems to understand lead sources, on-site behavior, and true conversion value. Key actions include:

• Integrate CRM with behavioral analytics systems: Synchronizing CRM with analytics tools allows teams to track leads after submission—identifying which sources drive high-quality leads, post-call status, response rates, and closing potential.

• Apply consistent UTM tagging across campaigns and ads: Consistent UTM setup across channels, ad groups, and content enables granular performance tracking at every touchpoint and helps identify the true drivers of conversion.

IV. Alignment criteria between marketing and sales

A common scenario across many organizations is Sales stating, “Marketing keeps sending uninterested leads,” while Marketing believes budgets and targeting have been optimized correctly. This misalignment often stems from a lack of communication, shared criteria, and end-to-end data visibility. Rather than assigning blame, businesses should establish a transparent and collaborative framework for evaluating lead quality. A recommended approach includes:

• Agree on a shared definition of a “Qualified Lead”: Both teams must clearly align on what constitutes a qualified lead. For example: valid phone number + reachable + confirmed interest in the product/service = Qualified Lead.

• Re-evaluate targeting strategies if Sales feedback consistently mismatches expectations: Frequent feedback such as “outside our service area” or “the customer is unfamiliar with the product” indicates potential issues in audience selection.

=> Tighten criteria around age, behavior, geographic location, profession, and interests.
=> Exclude audiences that have been exposed repeatedly without meaningful engagement.

• Review ad messaging to avoid misinterpretation: If users respond with comments such as “I thought this was a free gift registration,”, “I didn’t realize this was a paid service,”, or “I didn’t know this was a consultation form,” the ad message is likely misleading.
  => Reassess headlines, descriptions, visuals, and CTAs.
  => Clarify messaging to reflect real value propositions and ensure full alignment with landing page content.

• Segment leads by campaign and channel for optimization: Tag or group leads by source—such as Product A ads, Zalo OA, remarketing campaigns—to evaluate performance at a granular level.

• Use a shared CRM system for unified measurement and lifecycle tracking: A centralized CRM allows both teams to view lead status in real time—contacted, unreachable, follow-up required, converted—supporting remarketing and ongoing optimization. Importantly, lead quality should be evaluated using downstream metrics, not CPL alone. Key indicators include:

  • Successful connection rate

  • Sales response time

  • Conversion rate from MQL (Marketing Qualified Lead) to SQL (Sales Qualified Lead), reflecting the true business impact of each campaign.

• Establish a fast feedback loop from Sales on lead outcomes: Sales teams should update lead status after each call—user response, reasons for disinterest, or positive signals. Marketing can then refine targeting, messaging, and channel allocation based on real conversion insights.

The diagram above illustrates a sample Lead Qualification Process. Input sources may include multiple lead types:

• Unqualified: Leads that do not meet minimum criteria or lack sufficient information.

• MQLs (Marketing Qualified Leads): Leads qualified based on marketing-defined criteria.

• SQLs (Sales Qualified Leads): Leads ready for direct sales engagement.

• PQLs (Product Qualified Leads): Leads that have experienced or shown strong interest in the product.

• CQLs (Conversion Qualified Leads): Leads demonstrating high conversion intent.

All leads pass through a Lead Qualification Framework, where they are evaluated and segmented into two groups: Qualified Leads—ready for the sales pipeline—and Disqualified Leads, which are either removed or entered into nurturing workflows for future opportunities. This approach enables businesses to reduce wasted spend while focusing resources on leads with genuine conversion potential.

Conclusion

As user behavior tracking becomes increasingly constrained by privacy regulations and cookie-blocking technologies, marketers must adopt new approaches to maintain precision in lead qualification. Rather than relying solely on historical data, brands should shift toward contextual and real-time strategies—leveraging first-party data and personalizing messaging based on the content users are actively consuming. This context-driven approach focuses on true intent at the moment of interaction. Ultimately, lead quality is not determined by traffic or targeting alone, but by a coordinated system spanning distribution strategy, messaging, landing page optimization, and strong marketing alignment with sales.

Currently, SmartAds is advancing toward a holistic solution to this challenge—combining contextual advertising with robust measurement to help brands reach the right audience at the right moment while tracking post-click behavior more effectively. As a result, businesses can optimize real performance, build high-quality customer segments from the outset, and move beyond volume-driven campaigns toward sustainable conversion optimization.