Business Review B2B SaaS · Mid-Market

Lattice Cloud
Business Review

Strong product-market fit and an established mid-market motion — performance is constrained by MQL→SQL leakage, slow inbound callback SLAs, and a paid-search engine that's outrun its keyword tier. Three changes recover ~$280K of pipeline in 60 days.

About the Business
Lattice Cloud is a mid-market B2B analytics SaaS serving 280+ customers across financial services, healthcare, and SaaS verticals — selling a self-serve + sales-assisted platform with $24K ACV and an 18% blended win rate. Sales is led by a 9-person AE team with 3 SDRs; marketing is led by a single Head of Demand. The product has strong reviews (G2 Leader, 4.7), real category authority with RevOps and Analytics buyers, and a sales-led motion that converts well at the demo stage — but the pre-demo funnel is leaking.
90 days
Period Reviewed
6
Channels Audited
4
Issues Identified
4
Opportunities Sized
$1.4M
90-Day Pipeline
Section 1 · Executive Snapshot
Where we are. What's broken. What's the upside.
A 90-second read on the current operating state: the pipeline KPI dashboard, the three issues constraining performance, and the three opportunities sized against measurable lift.
CPL (blended)
$312
↑ 18% L90D
Target: $220
MQL → SQL
22%
↓ 6pts YoY
Target: 35%
Win Rate
18%
→ Flat L90D
Target: 28%
Pipeline Coverage
2.8×
↓ 0.4× vs Q-1
Target: 4.5×
ACV
$24K
↑ 8% YoY
Healthy
CAC Payback
18 mo
↑ 4 mo YoY
Target: 12 mo
⚠ Top 3 Issues — Constraining Pipeline Today
1
MQL→SQL leakage at 22% (vs 35% target). Inbound callback SLA averaging 6h 12m, ICP qualification inconsistent, lead routing has 3 dead-end paths. → ~$280K pipeline lost / 90d
2
Paid-search has outrun its tier-1 keywords. CPC up 31% YoY on brand-adjacent terms; tier-2 expansion never happened; SEO has zero topical authority on 18 high-intent terms. → ↑ CPL 18% over 90 days
3
Sales-marketing alignment is informal. No shared SLAs, no closed-loop reporting on lead quality, no agreed ICP scoring. → Win-rate stuck at 18% (target 28%)
↑ Top 3 Opportunities — Sized to Measurable Lift
1
Tighten the inbound funnel: SLA + qualification + routing. 30-min callback SLA, ICP scoring, 3-path routing fix. → MQL→SQL 22% → 32–38% · ↑ pipeline +$220–280K / 90d
2
Paid + SEO content engine on tier-2 intent terms. 18-term content roadmap; LinkedIn ICP-led paid; outbound sequence fed by intent signals. → ↓ CPL 25–35% · ↑ qualified MQL +18–28%
3
Sales-marketing operating system. Shared SLAs, closed-loop reporting, ICP scoring, weekly pipeline review. → ↑ Win Rate 18% → 24–28% · ↓ Sales Cycle 64d → 48d
Section 2 · Current State Diagnosis
Pipeline · Channel Mix · Messaging & Conversion
Three audit lenses on the same engine. The pipeline funnel tells us where deals leak; the channel mix tells us what's funding the leaks; the messaging/conversion section tells us why the leaks compound at the top.
2A

Pipeline Funnel Performance

Two distinct leaks: a MQL→SQL drop (22% vs. 35% benchmark — driven by callback SLA + routing), and a SQL→Opp drop (44% vs. 60% — driven by demo-to-proposal handoff). Combined leak: an estimated $280K of unrealized 90-day pipeline.
L90D · Pipeline
n = 1,340 leads
Inbound Leads
1,340 leads 100%
↓ 62% MQL rate · benchmark 65% — borderline
MQL
831 MQLs 62%
↓ 22% MQL→SQL · benchmark 35% · leak #1
SQL
183 SQLs 14%
↓ 44% SQL→Opp · benchmark 60% · leak #2
Opportunity
81 opps 6%
↓ 18% Opp→Win · benchmark 22% — borderline
Closed-Won
15 wins 1.1%
MQL→SQL
22%
vs benchmark 35%
Avg Callback SLA
6h 12m
target 30 min
Sales Cycle
64 days
target 45
Pipeline Coverage
2.8×
target 4.5×
Segment Mix · 90-Day Pipeline Contribution
Enterprise · 8% of leads
$72K avg ACV · 38% pipeline
Win Rate 22%
Cycle 118 days
CAC Payback 10 mo
Coverage 3.4×
Highest LTV by 3×; sales cycle is long but predictable. The strategic-account expansion lever sits here.
Mid-Market · 47% of leads
$24K avg ACV · 52% pipeline
Win Rate 19%
Cycle 64 days
CAC Payback 18 mo
Coverage 2.6×
Engine of the business; this is where the inbound leakage hits hardest. Fixing MQL→SQL here is the biggest single lever.
SMB · 45% of leads
$8K avg ACV · 10% pipeline
Win Rate 11%
Cycle 32 days
CAC Payback 32 mo
Coverage 3.1×
High volume, low win rate, long payback — candidate for self-serve / PLG motion rather than AE-handled cycle. Filtering opportunity.
2B

Channel Breakdown

Spend Mix · L90D
$186K
Total Spend
Paid Search 38%
Outbound (SDR) 22%
LinkedIn / Paid Social 16%
Events / Webinars 12%
SEO / Content 12%
CPL by Channel · target line $220
$220 target
LinkedIn / Paid
$498
$498
Paid Search
$334
$334
Events
$298
$298
Outbound
$186
$186
SEO
$92
$92
Channel Spend % CPL MQL→SQL Pipeline % Verdict
Paid Search 38% $334 26% 34% Borderline · Saturated
Outbound (SDR) 22% $186 38% 28% Healthy
LinkedIn / Paid Social 16% $498 14% 9% Underperforming
Events / Webinars 12% $298 32% 18% Strong · Underused
SEO / Content 12% $92 34% 11% Latent Asset
⚠
Channel takeaway: Paid search funds 38% of spend at $334 CPL but is saturated on tier-1 terms. Outbound and SEO are the cheapest, highest-converting channels but consume just 34% of spend together. The structural rebalance: feed outbound with intent signals, fund a 18-term SEO content engine, fix LinkedIn ICP targeting before scaling spend further.
2C

Messaging & Conversion — The Critical Gap

Demo Request CVR
2.1%
benchmark 3.4%
Avg Callback SLA
6h 12m
target 30 min
ICP-Fit MQL Rate
58%
target 80%
Demo→Opp
62%
strong — converts after demo
Win Rate
18%
target 28%
Landing Page Conversion Distribution · 90-Day · n = 22 active LPs
Demo-Request CVR % by Tier
3 LPs · 14%
4 · 18%
3 · 14%
5 · 23%
3 · 14%
2 · 9%
2 · 9%
>5% 4–5% 3–4% 2–3% 1.5–2% 1–1.5% <1%
Top Performers (32%)
7 landing pages carry the demand engine. All ICP-specific, all lead with a use-case headline, all have social proof above the fold. The "RevOps Analytics Playbook" lander is the single best — 5.8% CVR.
Average (51%)
11 LPs are coasting. Generic "platform" framing, no segment-specific copy, sub-the-fold social proof. Converting at 2–3% — should be 3.5–4.5% with ICP-specific reframing.
Underperformers (18%)
4 LPs are dragging blended CVR. Outdated copy, broken form fields, no ICP fit. Should have been retired or rebuilt 60+ days ago.
What's Working
ICP-specific use-case landers. The 7 top-tier LPs share a structure — segment-specific headline ("RevOps", "Healthcare Analytics"), use-case framing, social proof above fold. This is the iteration spine.
What's Broken
Callback SLA at 6h+, no qualification scoring, 3 dead-end routing paths. An MQL submitted at 2pm Wednesday gets a sales callback at 8am Thursday. Half the lead intent has decayed. Routing has gaps for "Enterprise + Healthcare" and "Mid-Market + No Stack".
What's Missing
A sales-marketing operating system. No shared SLAs, no closed-loop reporting, no agreed ICP scoring rubric, no weekly pipeline review with both teams in the room. Pipeline is owned by Sales; quality is owned by Marketing; the seam is the leak.
Section 3 · Core Problems
Four problems. Ranked by impact.
Each problem is named, traced to its root cause, and quantified by 90-day pipeline impact. Sorted by severity — Problem 1 is the highest-leverage fix.
Problem 01 · Critical
MQL→SQL leakage at 22%: callback SLA, qualification, routing
↑ Severity
Inbound MQL→SQL conversion is at 22% vs. a 35% benchmark and 38% on outbound. The leak is operational, not strategic — average callback SLA is 6h 12m, ICP qualification is inconsistent across SDRs, and three routing paths dead-end (Enterprise+Healthcare, Mid-Market without stack info, SMB+SaaS).
Cause
No formal SLA; SDR team works business hours only; lead routing logic unchanged in 14 months; ICP scoring lives in heads, not in a system. Marketing hands off; Sales picks up — no closed loop.
Impact (L90D)
~$280K of unrealized pipeline at current MQL volume — the highest-leverage operational fix in the engagement. Compounds the moment SLA tightens.
Problem 02 · High
Paid-search saturation; no tier-2 keyword expansion
High
38% of spend in Paid Search at $334 CPL — up 18% YoY. Tier-1 brand-adjacent terms (~24 of them) are saturated; CPC has risen 31% YoY on those terms. Tier-2 expansion (~18 high-intent terms) hasn't been built. SEO has zero topical authority on the same tier-2 set.
Cause
Paid search has been the easiest channel for the last 3 years and absorbed budget by default. SEO has been "important but not urgent" with no resources committed. The tier-2 keyword set has been mapped twice and never built.
Impact (L90D)
+18% CPL over 90 days on Paid Search alone. Compounds quarterly — every additional CPC click on tier-1 is a click that doesn't fund tier-2 expansion.
Problem 03 · High
Sales-marketing alignment is informal; win rate stuck at 18%
High
Win rate has been flat at 18% for 4 quarters (target 28%). Demo→Opp is healthy at 62%; the leak is between SQL and demo and again between Opp and Closed-Won. Pipeline is owned by Sales; quality is owned by Marketing; the operating cadence between them is one Slack thread per week.
Cause
No shared SLA, no closed-loop reporting on lead quality, no agreed ICP scoring system, no weekly pipeline review with both teams in the room. Definitions of MQL/SQL/Opp drift between teams.
Impact (L90D)
~10pts of unrealized win rate — if win rate moves from 18% → 24%, that's $360K+ of additional 90-day closed-won at current pipeline. The operating cadence fix is structural, not incremental.
Problem 04 · Medium
SMB segment dragging CAC payback; no PLG / self-serve filter
Medium
SMB represents 45% of leads but 10% of pipeline at 11% win rate and 32-month CAC payback. SMB leads consume AE time that should be allocated to mid-market (47% of leads, 52% of pipeline) and enterprise (8% of leads, 38% of pipeline).
Cause
No self-serve / PLG path. Every inbound — regardless of fit — gets the same AE-handled motion. SMB leads can't onboard themselves and don't justify the AE attention.
Impact (L90D)
Compounds Problem 1 — AE time on SMB displaces mid-market follow-up. Estimated ~25% of AE bandwidth recoverable through a self-serve filter.
Section 4 · Competitive Landscape
How competitors are winning. Where Lattice Cloud has leverage.
Five competitors audited across positioning, messaging style, channel strength, and execution velocity. The pattern is consistent: competitors are out-iterating on demand-gen content velocity and ICP segmentation — not out-thinking the product.
Brand Positioning Messaging Style Channel Strength Where they win Where we win
Tableau
Incumbent · Enterprise
 Enterprise BI standard; "trusted by Fortune 500" Authority-led; case-study-heavy; long-form sales enablement Salesforce ecosystem · Events · Direct sales Enterprise procurement default; Salesforce attach motion Mid-market speed-to-value; modern stack-native; G2-led peer review credibility
Looker (Google)
Cloud-Native · Mid+
 BI for the modern data stack; "model once, query anywhere" Technical-first; data-engineering audience; LookML ecosystem play Google Cloud · Partner ecosystem · SEO Modeling depth; technical buyer trust Self-serve simplicity for RevOps/biz buyers; faster time-to-first-dashboard
Mode Analytics
Notebook-Native
 SQL-first analytics for data teams ~25 pieces of long-form content/wk; aggressive SEO; LinkedIn ICP-led paid SEO · LinkedIn ICP-led · Content Topical authority on 40+ analytics terms; data-team mindshare Business-user accessibility; broader cross-functional ICP
Sigma Computing
DTC-Style B2B
 Spreadsheet UX on the cloud warehouse Outbound + LinkedIn-heavy; product-led demos; aggressive pricing transparency Outbound · LinkedIn · Free trial Self-serve onboarding; pricing transparency wins SMB+MM Established vertical depth (FinServ, Healthcare); embedded partner motion
Hex
Newer · DS-Native
 Notebooks + dashboards for data scientists Founder-led content; Twitter/X dominant; community-first; 60+ webinars/year Community · Founder content · Webinars Data-science community mindshare; content velocity; founder reach RevOps / biz-user fit; vertical case studies; sales-led mid-market motion
Observation 1 — Content Velocity Gap
Mode and Hex are publishing 20–30 pieces of long-form content per month; Lattice Cloud is at ~6. The gap isn't writing capacity — it's a structured content engine tied to tier-2 keyword targets and ICP-segment needs.
Observation 2 — ICP Segmentation Depth
Sigma and Mode run 5–8 ICP-specific landing pages per vertical with vertical-tailored sales decks. Lattice has 3 vertical landers and a single "Platform" deck — half the funnel is generic by default.
Observation 3 — SEO Topical Authority Gap
Mode owns ~40 analytics-category terms; Looker owns ~60 modeling-category terms. Lattice owns the brand term and 4 "RevOps + analytics" terms uniquely — but ~18 high-intent tier-2 terms are uncontested.
◆
Strategic position — where Lattice Cloud wins. Lattice has structural advantages in mid-market: vertical depth in FinServ + Healthcare, RevOps/biz-user accessibility that Looker and Mode lack, sales-led mid-market motion that Sigma and Hex haven't built, and a G2 Leader / 4.7 rating with real category authority. The execution gap — not the product — is what's keeping mid-market share from compounding. The competitive read is: out-iterate on content + ICP segmentation, don't out-position on product.
Section 5 · Growth Opportunities
Four opportunities. Each tied to a measurable lift.
Sequenced by leverage and time-to-value. Quick = days 0–30, Mid = days 30–60, Long = days 60–90+. Every opportunity carries a numeric expected-impact range — no qualitative wins.
Opportunity 01 · Days 0–30
Tighten the inbound funnel: SLA + ICP scoring + routing
Quick
Move callback SLA from 6h 12m → 30 min, deploy ICP scoring as a routing input, and fix the three dead-end routing paths. Closes the MQL→SQL leak (22% → 32–38%) and recovers ~$280K of pipeline at current MQL volume.
What we'd do
30-min callback SLA + tracking · ICP scoring rubric in CRM (firmographics + intent signals) · routing logic rebuild · auto-Slack-alert on inbound · weekly SDR efficiency review
Expected Impact
↑ MQL→SQL 22% → 32–38%
↑ Pipeline +$220–280K / 90d
↑ Coverage 2.8× → 3.6×
Timing
SLA + routing live by Day 14; ICP scoring by Day 30. Lift visible in the pipeline within 30 days.
Opportunity 02 · Days 14–60
Sales-marketing operating system + closed-loop reporting
Quick
Stand up the operating cadence between Sales and Marketing — shared SLAs, agreed MQL/SQL/Opp definitions, weekly pipeline review with both teams, closed-loop reporting on lead quality. Closes the win-rate gap from 18% → 24–28%.
What we'd do
Shared SLA document · joint MQL/SQL/Opp definitions · weekly 30-min pipeline review · closed-loop reporting dashboard · monthly Sales+Marketing ICP review · quarterly business review cadence
Expected Impact
↑ Win Rate 18% → 24–28%
↓ Sales Cycle 64d → 48d
↑ ACV +6–12% (better-fit deals)
Timing
First weekly pipeline review by Day 14; closed-loop dashboard live Day 30. Win-rate lift visible from Day 60.
Opportunity 03 · Days 30–75
Tier-2 demand engine — paid + SEO + outbound on intent
Mid
Build the tier-2 keyword engine across Paid Search (18 new term clusters), SEO content (24-piece roadmap on the same terms), and an intent-driven outbound layer (6sense / Bombora signals fed to SDR sequences). Compresses CPL and expands qualified MQL.
What we'd do
Tier-2 keyword expansion in Google Ads · 24-piece SEO content roadmap (pillar + cluster) · intent-data integration → SDR · LinkedIn ICP-led campaigns rebuilt · webinar program (1/mo cadence)
Expected Impact
↓ Blended CPL 25–35%
↑ Qualified MQL +18–28%
↑ SEO Pipeline 11% → 18–24%
Timing
Paid tier-2 live Day 30; SEO content shipping weekly from Day 45; intent layer Day 60. Compounds for 4+ quarters.
Opportunity 04 · Days 45–90
Self-serve PLG filter for SMB + vertical depth for Enterprise
Long
Two-sided segmentation: a self-serve / PLG path for SMB (recovers ~25% of AE bandwidth) and a vertical-deep enterprise motion (FinServ + Healthcare ABM). Reframes resource allocation around the segments where Lattice has structural advantage.
What we'd do
Self-serve onboarding flow + pricing page · SMB filter rule (companies <50 employees → PLG path) · FinServ + Healthcare ABM list (200 accounts each) · vertical sales decks · 1:1 ABM playbook
Expected Impact
↑ AE bandwidth +25%
↑ Enterprise Pipeline +30–50%
↓ SMB CAC Payback 32mo → 14mo
Timing
Self-serve flow shipped Day 60; ABM lists active Day 75. Compounds across full sales cycle (90+ days lift).
Section 6 · Growth System (MH-1 Differentiator)
The differentiator isn't more reporting — it's a system that converts inputs into compounding pipeline.
Most B2B engagements operate as three disconnected functions: demand-gen, sales, and content. The MH-1 system connects them through a structured loop where every output feeds back into the next input — pipeline compounds instead of resetting weekly.
Inputs
Tier-2 keyword + content roadmap
ICP scoring + intent signals
Outbound + paid + LinkedIn ICP plays
First-party data (CRM, product, support)
Competitive scan (weekly)
→
System
AI-driven content + outbound iteration
Closed-loop MQL→SQL→Opp→Won reporting
Sales-marketing weekly operating cadence
Performance triggers + auto-routing
Cross-channel signal sharing
→
Outputs
↓ Blended CPL, compounding
↑ MQL→SQL conversion
↑ Win Rate, ↓ Sales Cycle
↑ Pipeline coverage 2.8× → 4.5×+
Predictable, durable ARR growth
◆
For Lattice Cloud: the system unlock is closing the inbound funnel loop with a 30-min SLA and ICP scoring, then feeding the front of the funnel with tier-2 demand. Every winning content piece spawns 2–3 sequence ideas the following week; every dead-end routing path is patched within 48 hrs. The system runs the calendar — not the other way around.
Section 7 · 30 / 60 / 90 Day Plan
Stabilize · Scale · Compound
Sequenced for compounding leverage. Each phase produces outputs the next phase needs — we don't expand channels until inbound is converting, and we don't compound vertical depth until sales-marketing alignment is durable.
Days 0–30 · Stabilize
Tighten the inbound funnel; restart the operating cadence
Inbound funnel rebuild
30-min callback SLA, ICP scoring, routing fixes.
  • 30-min callback SLA + tracking
  • ICP scoring rubric live in CRM
  • 3 dead-end routing paths patched
Sales-marketing operating cadence
Shared SLAs, weekly pipeline review live.
  • Shared SLA document signed
  • Weekly 30-min pipeline review (both teams)
  • MQL/SQL/Opp definitions agreed
LP audit + top-7 reframe
ICP-specific copy on top traffic landers.
  • Vertical-specific headline on top 7 LPs
  • Social proof above the fold
  • Form-field optimization
Days 30–60 · Scale
Expand demand; close the closed-loop reporting
Tier-2 demand engine launch
Paid + SEO + outbound on tier-2 keywords.
  • 18 tier-2 paid-search clusters live
  • SEO content shipping weekly
  • Intent data → SDR sequences
Closed-loop reporting dashboard
Channel → MQL → SQL → Opp → Won, end-to-end.
  • Closed-loop dashboard in production
  • Channel attribution by stage
  • Weekly review cadence anchored on it
LinkedIn ICP-led rebuild
Paid social CPL $498 → $260.
  • ICP audience rebuild (firmographics + intent)
  • Vertical-specific creatives (FinServ, Healthcare, SaaS)
  • Account-list targeting on ABM accounts
Days 60–90 · Compound
Vertical depth, PLG filter, durable demand
Self-serve / PLG filter
SMB onto self-serve; AE bandwidth back to MM/Ent.
  • Self-serve onboarding flow live
  • SMB filter rule active
  • Pricing page transparent
FinServ + Healthcare ABM
200 accounts each, 1:1 plays running.
  • ABM lists built (400 total accounts)
  • Vertical sales decks shipped
  • 1:1 ABM playbook in execution
Quarterly review + Q-Plan
Built on a stabilized engine.
  • Q+1 plan with Sales + Marketing
  • Pipeline coverage at 4.5×+
  • Operating cadence durable
Section 8 · KPI Guardrails
When we act. Not just what we see.
A reporting system tells you what happened. A guardrail system tells you what to do about it. Each metric below has a healthy threshold, a trigger threshold, a defined action, and an owner — so the team isn't waiting for a weekly meeting to react.
Metric Healthy Trigger Action Owner
Callback SLA < 30 min > 60 min / day Page on-call SDR; review routing rules + load-balancing same day SDR Lead
MQL→SQL Rate > 32% < 26% / week Audit lead source quality; refresh ICP scoring; SDR script review Marketing + SDR Lead
Blended CPL < $220 > $280 / 7 days Pause underperforming campaigns; ship 4 new creatives within 72 hrs; check ICP fit Growth Marketer
Pipeline Coverage > 4.0× < 3.5× / week Activate ABM list outreach; ship outbound burst sequence; review SDR capacity VP Sales + CMO
Win Rate > 22% < 16% / month AE win/loss review on last 20 deals; refresh ICP fit; sales enablement check VP Sales
Sales Cycle < 50 days > 70 days / month Stage-by-stage drag analysis; AE training on stuck stages; pricing/proposal review VP Sales
◆
How guardrails operate. Thresholds are reviewed weekly and adjust to the prior 4-week trailing average — guardrails compound, not pause, the system. Actions trigger automatically; the meeting is to debate exceptions, not to read the report.
Section 9 · What Happens Next
What ships next, and the path forward
The Business Review is one of two trial deliverables. The Day-14 30-60-90 Plan Presentation is the second. Between today and Day 14, here's what ships and how we move into the engagement path forward.
This Week
What ships before the next meeting
Three workstreams already in motion — momentum walks into the next meeting.
  • 30-min callback SLA piloting on FinServ + Healthcare segments
  • ICP scoring rubric drafted; CRM fields ready for activation
  • Top-3 ICP-specific landing pages reframed and shipped
  • First weekly Sales-Marketing pipeline review on the calendar
Day 14 · Meeting 2
30 · 60 · 90 Day Plan Presentation
A channel-by-channel build of the next 90 days. Specific tactics, named owners, named metrics, and the operating cadence you'll see week-to-week.
  • Channel-by-channel quarterly plan (Paid · SEO · Outbound · ABM)
  • Sales-marketing operating cadence + closed-loop dashboard
  • Pipeline coverage targets by phase
  • Resource & team mapping
Beyond Trial · Path Forward
We'll align on the path forward together
Two engagement paths are typical at the end of trial — a continued focused engagement, or an expanded team scope as outcomes compound. The Day-14 meeting is the place we agree on which.
  • Continue — current scope with the inbound rebuild and tier-2 demand engine running
  • Expand the Team — add co-pilot specialists as outcomes compound (ABM, content, RevOps)
  • Operating cadence transitions from weekly trial reviews to a monthly performance dashboard rhythm
100% refund if we don't continue after the trial.