We keep generating leads that sales ignores. What do we actually fix?
This is not a relationship problem between sales and marketing. It is a structural problem in how you have defined a qualified lead — and it needs to be fixed at the definition level, not the communication level.
Why sales ignores most marketing leads
Sales teams do not ignore leads out of laziness or arrogance. They ignore leads because working unqualified leads has a cost — it takes time away from deals that are actually likely to close. When marketing sends leads that sales has learned not to trust, the rational response is to deprioritise them. The problem is not attitude. It is a misaligned definition of what a qualified lead looks like.
Most marketing teams define their ICP at a high level — industry, company size, geography — but do not build that definition into their lead qualification criteria. Every lead that doesn't match the ICP that sales actually sells to is guaranteed to be ignored. The ICP on the website and the ICP in the field are often different companies.
MQL definitions are usually built by marketing without sales input, and they tend to reward engagement behaviour rather than buying intent. A prospect who reads three blog posts and downloads a whitepaper is not the same as a prospect with budget, authority, and an active problem. Conflating these two creates volume that looks good in reports and performs badly in pipeline.
Once sales has ignored marketing leads for two or three quarters, a trust deficit builds. Even when marketing improves lead quality, sales will continue to deprioritise the leads because the historical signal is bad. Fixing the definition is not enough — you have to actively rebuild the feedback loop and show improving data over time.
In Indian B2B companies, the sales team often has a strong referral and relationship culture. They are used to working warm introductions from founders, advisors, or existing customers. A cold inbound lead — even a well-qualified one — can feel lower priority than a warm intro. Marketing needs to understand this hierarchy and design handoffs accordingly.
The question map: L1 vs L2
L1 questions describe the symptom. L2 questions locate the real cause — and point toward decisions that actually fix it.
Define your ICP with sales, not for sales
Sit with two or three of your best-performing salespeople and reverse-engineer your last 10 to 15 closed-won deals. Build the ICP from actual customers — industry, company size, tech stack, team size, trigger event — not from a strategy document.
In SaaS, the most common mistake is treating any product signup as an MQL. Trial users who signed up out of curiosity are not the same as buyers who signed up because they have a problem to solve. The fix is not scoring higher — it is splitting your funnel: build one nurture track for exploration signups and a separate fast-follow sequence for signups that match your ICP profile by company size, industry, and role.
In IT services, sales teams work from existing relationships and referrals. A whitepaper download from a procurement manager at an enterprise company is not something an enterprise sales rep will chase — they already know that person or they will get introduced. Marketing's role in IT/ITES is to support the relationship, not generate new one-way intent signals. Measure content downloads by whether they appear in CRM accounts already in pipeline, not as standalone leads.
In manufacturing, a lead is not a lead until the buyer has a spec and a timeline. Most marketing activity — tradeshows, catalogs, website visits — generates awareness, not intent. Sales teams know this and filter accordingly. Rather than fighting it, build a two-stage model: marketing owns awareness and first contact; sales owns everything from the first conversation. The handoff point should be explicit and agreed, not assumed.
In pharma B2B, a lead is only viable if the buyer's product and regulatory context matches your solution. A hospital procurement manager is not the same buyer as a CRO vendor. Generic intent signals generated through content marketing almost never carry this context. Build lead forms that capture product area and regulatory market upfront — and accept that this will reduce volume significantly while dramatically improving acceptance rate with sales.
Rebuild your MQL definition around fit, not behaviour
A lead who visits your pricing page twice is engaging with your content. A lead who matches your ICP and has visited your pricing page twice might be in-market. Behaviour alone is not qualification — fit plus behaviour is. Rebuild your MQL criteria so fit thresholds must be met before any behavioural score counts.
Create a formal SLA between sales and marketing
A Service Level Agreement between sales and marketing defines what marketing will deliver and what sales commits to in return. Without one, both sides operate on informal expectations that erode over time. The SLA should specify: what counts as an MQL, how quickly sales will respond, and how sales will log disposition back into CRM.
Build a closed-loop feedback system
The most valuable data in your lead generation program is what happens to leads after you hand them off. If you do not know why leads are being rejected, you cannot improve. Build a simple disposition taxonomy in your CRM: Not ICP, No budget, No timing, Already a customer, Duplicate. Review these monthly.
Run a pipeline audit before changing anything else
Before redesigning your entire lead gen program, audit your last 20 closed-won deals. Where did each one start? What was the original source? How long did it take from first contact to close? This audit almost always reveals that your best deals come from sources you are not prioritising.
Establish a 90-day improvement cycle
Lead quality improvement does not happen in one quarter. Set a 90-day cycle: change one thing in the MQL definition or ICP criteria, measure the impact on MQL-to-SQL rate, adjust. Resist the temptation to change multiple things at once — you will not know what worked.
Real-world examples
How B2B companies across India and globally have navigated this decision.
Intercom's growth team found that their scoring model rewarded engagement behaviour — multiple logins, feature exploration, invite of team members — that correlated with product adoption but not with commercial deal size. Their highest MQL scores were often coming from very small companies where the product was being used heavily but there was no commercial opportunity. They rebuilt their qualification model to require company size and role fit before any behavioural score could lift a lead to MQL status. MQL volume dropped by 40% and SQL conversion rate nearly doubled within two quarters.
A Bengaluru-based HR tech company had been investing heavily in content marketing and LinkedIn lead gen, generating several hundred MQLs per quarter with low sales conversion. A pipeline audit revealed that the majority of their closed deals came from introductions through three implementation partners and referrals from existing customers — channels that had no dedicated marketing investment. They rebuilt their partner marketing program, allocated a portion of their content budget to partner enablement, and saw a material improvement in SQL quality within two quarters. The content program was not eliminated — it was repositioned for awareness rather than lead generation.
A mid-sized Indian IT services company had been running a content and event program for two years, generating consistent inbound leads that their enterprise sales team rarely worked. A candid conversation with the head of sales revealed that enterprise IT services deals never start with an inbound inquiry — they start at a conference, through an analyst relationship, or via a CXO introduction. Marketing pivoted to measuring pipeline contribution from the events it co-sponsored, the analyst briefings it facilitated, and the account-based campaigns it ran for named accounts already in sales pipeline. Lead volume went to zero as a marketing metric; pipeline contribution became the single number both teams agreed to report.
When the logic works — and when it breaks
- The ICP is defined jointly with sales and reviewed every six months
- MQL criteria require fit thresholds before behavioural scores apply
- A formal SLA governs response time and CRM disposition
- Disqualification reasons are tracked and reviewed monthly
- Lead quality is measured by MQL-to-SQL rate, not volume
- A pipeline source audit is done annually to validate budget allocation
- MQL definitions are built by marketing and presented to sales as a fait accompli
- Behavioural engagement alone triggers MQL status without fit criteria
- Lead volume is the primary metric reported to leadership
- Sales teams have no structured way to feed back why they rejected a lead
- The same MQL threshold applies to all segments, deal sizes, and channels
- Marketing changes multiple variables at once and cannot isolate what improved conversion
Your move
Pull your last 15 closed-won deals from CRM and find the original lead source for each one. Then pull your last quarter's MQLs and check what percentage of them match the same profile as those 15 closed deals. The gap between those two numbers is the size of your lead quality problem.
Then schedule a 60-minute working session with two salespeople — not a roundtable, not a QBR, a working session — and ask them one question: describe the last lead from marketing that you actually worked and why. The answer will tell you more than any scoring model audit.
Every month, one hard B2B marketing problem.
First principles thinking. Real India context.