Find which customer segment is expanding fastest

<context>
I want to understand which customer segment is expanding fastest in our base — not by revenue alone, but by the firmographic attributes that define who we sell to. I want to know if our fastest-growing customers share specific traits: industry, size band, function makeup, geography, or signals like funding stage. That tells us where to focus new business.

My customer base:
- Customer list: [PASTE COMPANY NAME, CURRENT ACV, EXPANSION ACV OR "NONE", SEGMENT — one per line]
- Our segments: [HOW YOU DEFINE THEM — e.g. SMB / Mid-market / Enterprise, or by industry]
- What counts as expansion: [UPSELL / NEW SEATS / NEW USE CASE / ALL]
- Timeframe: [LAST 6 MONTHS / LAST YEAR / LAST QUARTER]
</context>

<task>
1. For each customer that expanded in the timeframe, use Lusha to pull current firmographic data:
   - Headcount at time of expansion
   - Industry and sub-industry
   - Geography
   - Headcount in the function we sell into
   - Any signals active around the time of expansion: funding, exec hire, headcount growth

2. Identify firmographic patterns across expanding customers:
   - Which industry or sub-industry has the highest expansion rate?
   - Which size band expands most frequently?
   - Which function headcount range correlates with expansion?
   - Any geographic concentration?
   - Any signals that appear disproportionately in accounts that expanded vs those that didn't?

3. Compare expanding customers against non-expanding customers in the same segment:
   - What firmographic attributes do expanding customers have that non-expanders don't?
   - Is the pattern consistent across segments or specific to one?

4. Return a segment expansion analysis:
   - Top 2-3 firmographic attributes most correlated with expansion
   - The segment or sub-segment expanding fastest (by rate, not just volume)
   - The signal most commonly present in accounts that expanded
   - One ICP refinement recommendation based on the pattern

5. Flag any customer that hasn't expanded but matches the firmographic profile of your fastest-expanding segment.
</task>

<constraints>
- Base the analysis on Lusha-verified firmographic data, not CRM tags or rep notes.
- Correlation is not causation — flag patterns as signals worth testing, not proven rules.
- If fewer than 5 customers expanded in the timeframe, say so — the sample is too small to conclude.
- The ICP refinement recommendation must be specific and actionable, not generic.
</constraints>

The situation: A CS leader at a B2B SaaS company runs the analysis across 18 customers, looking at expansion over the last 6 months. 7 expanded. She wants to know if there’s a pattern she can use to sharpen both new business targeting and expansion prioritization.

Output: Two firmographic attributes dominate expansion. One sub-segment is expanding at 3× the rate of others. Four non-expanders match the profile and are flagged as priority targets.

Segment expansion analysis

18 customers analyzed · 7 expanded · 11 did not expand

Timeframe: Last 6 months. Firmographic data via Lusha.

Top attributes correlated with expansion

1. Sales team headcount between 30–60 reps 6 of 7 expanding customers had a sales team of 30–60 reps at the time of expansion. Only 2 of 11 non-expanders fell in that range. This is the strongest single firmographic predictor in the dataset.

2. Series B or later funding stage 5 of 7 expanding customers had raised a Series B or later. 3 of 11 non-expanders had reached that stage. Funded companies at the 30–60 rep scale appear to be the core expansion profile.

3. New CRO or VP of Sales hired in the 90 days before expansion 4 of 7 expanding customers had an exec hire in the buying function within 90 days of the expansion conversation opening. This signal appears to be a catalyst — the expansion didn’t precede the hire, it followed it.

Fastest-expanding sub-segment

Mid-market SaaS, 150–350 employees, Series B+, sales team 30–60 reps

Expansion rate: 5 out of 6 customers in this sub-segment expanded in the last 6 months — 83%. The next closest segment (enterprise, 500+ employees) expanded at 2 out of 5 — 40%.

The pattern is consistent: this isn’t the highest-ACV segment, but it’s the most reliable expander. A new CRO or VP of Sales joining a company in this band within the last 90 days is the single clearest trigger for an expansion conversation.

ICP refinement recommendation

Add “Series B+, sales team 30–60 reps” as a secondary ICP filter for expansion-focused prospecting. Companies that fit the primary ICP (industry, size, geography) but also match this sub-segment profile should be prioritized in new business targeting — they’re more likely to expand within 12 months of initial close.

Non-expanders matching the expansion profile — flag for CS outreach

Dune Analytics is the highest-priority flag: matches the profile and has a live new exec signal that hasn’t been acted on.

Firmographic data validated via Lusha connector, May 19. Customer data from pasted CRM export.