Revenue Diagnostics Revenue Intelligence About
Working inside your marketing and pipeline data

B2B revenue
analytics
for founders

I help founders identify revenue blockers, funnel drop-offs, and which channels and signals lead to closed deals.

https://chat.lamparalab.com
Which channels bring leads, not just traffic?
Where does the pipeline slow down?
What should we fix first?

Who This Is For

Built for B2B teams with traffic
and leads, but no clarity on revenue

Early-stage B2B teams

Traffic is coming,
but nothing is clear

"We get signups, but don't know where they come from" "Users drop, but we don't see where" "Data is there, but not useful"

You get:

  • Which channels actually convert into leads
  • Where users drop in your funnel
  • Which metrics actually matter — and what you can ignore

Growing B2B teams

Pipeline is full, but
revenue doesn't follow

"We have leads, but deals don't close" "We spend on ads, but don't know if it pays off" "Deals sit in the pipeline for months"

You get:

  • Where deals slow down or get stuck
  • Which channels lead to better deals and outcomes
  • What to fix first to move deals forward

How I Help

B2B revenue analytics across
marketing, CRM, and pipeline

I analyze your marketing, CRM, and pipeline data to understand where revenue slows down and what to fix first.

You get

  • CRM data audit — what's tracked, what's missing, and what blocks analysis
  • Pipeline in real dollars — by stage, deal size, and total value
  • Win rate by deal size — which deals you close and which you lose
  • Stage drop-off map — where deals stall between steps
  • ICP from closed deals — industry and geography based on actual wins
  • Untapped contacts — leads in your CRM without deals or follow-up

Depth of analysis depends on what's tracked in your CRM. I show what can be seen, what cannot, and what to fix first.

You get

  • Data quality check — what is tracked correctly, what is broken, and what is missing
  • Channel performance — how different traffic sources relate to leads and conversions
  • Funnel breakdown — where users drop between key steps
  • Device comparison — differences in behavior and conversion between mobile and desktop
  • User paths — how visitors move before converting, based on available data
  • Content impact — which pages are involved in conversions and which are not

Depth of analysis depends on your tracking setup. I show what can be measured, what cannot, and what to fix first.

You get

  • Channel comparison — where traffic comes from and where deals close, shown side by side
  • Funnel view — from traffic to deals, highlighting the largest drop-offs between stages
  • Where the funnel breaks — between marketing and sales stages
  • Lead to deal view — how leads move (or don't) into the pipeline, and what limits visibility
  • Geo view — where traffic converts on the website, and where CRM location data is missing
  • Marketing and pipeline together — seen in one view, not as separate reports

This is not full attribution — the data doesn't allow it. But I show what the numbers do reveal: where marketing and sales align, where they diverge, and where the gap is.

You get

  • Priority channels — where to invest more and where to reduce effort
  • Target segments — which customers to focus on first, based on your data
  • Core messaging — how your product is currently perceived and how to adjust it
  • Funnel priorities — what to fix first to improve conversion
  • Action plan — clear next steps for the coming weeks
  • Key metrics — what to track to see if changes are working

You get

  • Top recurring issues — what customers complain about most
  • CSAT trends — rising or falling, where problems cluster
  • Tickets indicating dissatisfaction (refunds, complaints, repeat contacts)
  • SLA health — response times, backlog, overloaded teams
  • Patterns in support load — when and where volume spikes
  • Prioritized fix list — what to address first based on impact

You get

  • Buyer segments — which companies are most likely to need your product
  • Competitor positioning — strengths, gaps, and overlaps
  • Market signals — what your audience discusses and struggles with
  • Messaging patterns — how the problem is described in the market
  • Positioning opportunities — where you can stand out

Focused snapshot based on available signals, not a full market research project.

How revenue analysis works

Connect your data. Analyze it.
Turn it into revenue decisions

01

Data Connection

Start with what
you already have

I connect to your marketing, CRM, and other data sources with read-only access. Your systems stay untouched — no changes, no risk.

HubSpot Salesforce GA4 Google Ads Zendesk Intercom LinkedIn Ads Search Console
02

Analysis & Direction

Find what's
blocking revenue

I analyze your marketing, CRM, and pipeline data to see where revenue slows down and what drives deals. We review the findings together on a live call, and you get a clear, prioritized report with what to fix first.

Analytics review CRM audit Market signals Live call Written report
03

Ongoing Support

Adjust decisions as
your data changes

I track changes, refine priorities, and adjust decisions as your pipeline and market evolve. Monthly reviews keep analysis relevant and focused on real signals, not assumptions.

Monthly review Updated analysis Priority tracking Ongoing access

No dashboards for the sake of dashboards. Just decisions.

Ana Orestova

About

Ana Orestova

Revenue Analytics Consultant · Founder, LamparaLab

LinkedIn

Hi, I'm Ana. I work with B2B founders to understand what is actually happening in their data — and why revenue doesn't grow the way it should.

With a background in finance and several years in B2B SaaS (mostly FinTech, US market), I focus on connecting marketing, CRM, and pipeline data to find where things break: where leads drop, which channels waste budget, and where signals stop making sense.

How the work is structured
All analysis, interpretation, and calls Done by me · always
Technical setup and data connections Me + data engineer (included)
Work beyond analytics (ads, CRM ops) Trusted specialists on request

FAQ

Common questions

A service. You don't get a new dashboard login or software to maintain. You get a real analyst — me — who looks at your data, interprets it, and gives you specific answers and recommendations. You keep access to your own tools. I work inside them with you.
Most analysts give you numbers. I give you answers to founder questions — framed around revenue decisions. I've built products, run campaigns, and managed the full marketing-to-revenue loop myself. That means I know what a B2B founder actually needs from data, not just what the metrics say in isolation. The AI layer also means I can process and cross-reference far more data than a solo analyst doing it manually.
Two things. First, I’ve worked as a generalist across analytics, positioning, paid, content, website, and CRM. That’s what lets me trace how revenue moves from traffic to pipeline to closed deals — and where it breaks. Second, I use AI agents for what scales: data monitoring, pattern detection, recurring reporting. That lets me work at team scope while staying accountable as one person. Strategy and judgment are always mine.
30 minutes. I'll ask about your current stack, the questions that bother you most, and what you've already tried. You'll leave with a clear sense of what analysis makes sense for your situation and what it would cost. No pitch, no pressure — just an honest read.
Project work has a fixed scope and price we agree upfront. Ongoing monthly support is scoped per engagement. We discuss both options on the first call — once I understand your situation, I can be specific about what makes sense.
If you have traffic, leads, or a pipeline, but can't clearly explain what is driving revenue or where it slows down, this is something we should look at.

Ready to stop guessing
about revenue?

Book a free 30-minute call. We'll talk about your biggest revenue question and decide together which analysis makes sense.

Free 30-min call · No commitment · You own your data

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