VII. The Prescription: What Working Looks Like
Support as System Intelligence
What the Survey Measures
View data table
| year | COGS | S&M | G&A |
|---|---|---|---|
| 2018 | 56 | 33 | 11 |
| 2020 | 84 | 9 | 7 |
| 2021 | 82 | 11 | 7 |
| 2022 | 87 | 9 | 4 |
| 2023 | 79 | 15 | 6 |
The inventory is short because the data is. Across five survey years the certified series asks exactly one operating question about Support, where its cost is booked, and in one year it asks a second: how eager respondents are to apply AI to it.
| Support Cost Allocation (average) | COGS | S&M | G&A | Data Year | Source |
|---|---|---|---|---|---|
| Customer Support | 56% | 33% | 11% | 2018 | 2019 Survey, p. 64 |
| Customer Support | 84% | 9% | 7% | 2020 | 2021 Survey, p. 53 |
| Customer Support | 82% | 11% | 7% | 2021 | 2022 Survey, p. 52 |
| Customer Support | 87% | 9% | 4% | 2022 | 2023 Survey, p. 30 |
| Customer Support | 79% | 15% | 6% | 2023 | 2024 Survey, p. 37 |
That is the complete inventory: no ticket volume, no time-to-resolution, no escalation rate, no CSAT, no cost-per-contact, no headcount, no coverage ratio. The 2024 survey does define the boundary, Customer Support is “service + product assistance,” distinct from Customer Success’s “renewals + upsells” (definitions, 2024 Survey, p. 37), which confirms the survey knows the function exists as a distinct discipline. It measures nothing the discipline does. Inference
A Sensor Network Read as a Cost Center
Set Support beside its adjacent function and the survey’s model of the post-sale organization becomes explicit. On 2023 data (2024 Survey, p. 37), Customer Success books 68% of cost to S&M, the commercial line, attached to the selling motion. Customer Support books 79% to COGS, the delivery line, attached to the product’s margin. The COGS share for Support moved from 56% in 2018 to the low-to-high 80s by 2020–2023: by the efficiency era, Support was overwhelmingly classified as a cost of delivering the product, directly compressing the gross margin the survey tracks so carefully. A function classified almost entirely as COGS, in an era of margin discipline, has a target on it by construction. Inference
Consider what the survey’s own headline problems look like from inside a support queue. The churn floor, 14–15% today and unimproved in every measured year, is preceded by accounts that ticket differently before they leave: volume spikes, unresolved escalations, then silence. The downsell wave, 32% of gross retention loss overall in 2024 and 37–39% at the smallest and largest companies (2025 Survey, p. 19), is preceded by shrinking accounts that stop opening tickets for modules they have quietly stopped using. And the product capability gaps documented elsewhere in this report as invisible to the survey arrive in Support first, tagged with a feature name and an error message, months before they surface as a churn statistic. Support holds the leading indicators for the exact lagging metrics this survey has spent seven years documenting, and contributes zero fields to the dataset. Inference
Automating What Was Never Baselined
The one forward-looking signal in the certified series arrives through the 2025 AI data: 55% of respondents rank “Customer Service and Support” among the largest AI opportunity areas, third overall behind New Products/Services (82%) and Back Office/Data Automation (56%), and far ahead of workforce reduction (15%, the lowest-ranked area; 2025 Survey, p. 25). Read against the allocation history, the survey’s implied position is coherent and troubling: Support is a COGS burden, and AI’s promise for it is cost removal.
The distortion compounds across three of the report’s own findings. The churn floor looks unexplainable because its explanatory data was never collected: a floor observed without its precursors will always look structural, whether or not it actually is. Support’s retention contribution is unpriceable, so budget decisions default it to zero, and the COGS classification finishes the logic (cut it and margin improves, with no visible retention cost) the same illusion this report documents for the R&D cut, replayed one function over. And the product-gap signal chain is severed at its origin: the evidence for why customers leave exists, structured, timestamped, and categorized by feature, in every respondent’s ticketing system, and the survey never invited it in. Inference
Three Inputs Only Support Can Produce
Reframed as system intelligence rather than a delivery cost, three inputs fall out of Support’s queue that no other function can produce at the same fidelity.
A product-gap heat map
Ticket volume by feature area and error type is the most accurate available map of where the capability-outcome gap is widest. No roadmap-prioritization process sees this unless Support delivers it deliberately.
A customer-impact heat map
Severity cross-referenced against ARR, segment, and renewal timeline identifies which open issues carry the highest retention risk right now, not which are loudest.
A root-cause database
Tickets categorized by cause accumulate into an evidence base for product-experience misalignment, often flagging a churn signal the health score does not yet show.
The signal loop this report calls for elsewhere in the prescription, Support ticket root-cause data as a required roadmap input, cannot be benchmarked, and its absence cannot even be noticed, in a survey where Support’s only quantified property is its expense classification. Inference
Why This Is Not a Fifth Function
The argument above could read as a case for formalizing Support as a standalone function alongside Product, Marketing, Sales, and Customer Success. That is not the conclusion. The 2018-to-2020 allocation shift shows the classification is a choice, not a fact: in 2018, a third of Support cost sat in S&M; by 2020, 84% sat in COGS. The function did not change, the industry’s accounting posture did, which is itself evidence that Support’s org placement is fluid rather than structural. Formalizing Support as a fifth function is not worth the organizational complexity that argument would require, particularly as the industry consolidates Customer Success and Support under one leader. The value is captured without structural change, by treating Support’s output as a required input rather than by giving it a new seat. Inference
Closing the Loop
Two responsibility assignments capture the value. Customer Success incorporates Support data into health assessment and renewal-risk identification as a required input, using the customer-impact heat map to prioritize which accounts get proactive attention before a renewal, not after a cancellation notice. Product receives systematic Support analysis on a regular cadence as a required roadmap input, using the product-gap heat map and root-cause database as the evidentiary base for the capability-gap log described in Product as a System Member. The outcome record links the two: when Support patterns reveal a recorded outcome is not being reliably achieved, the record is updated, Sales and CS are notified, and the roadmap adjusts. Inference
The loop this page describes is sequenced in The Playbook.
Frequently asked questions
What does the KBCM survey actually measure about Support?
Almost nothing. Across seven survey editions the series asks only where Support's cost is booked, no ticket volume, resolution time, escalation rate, or CSAT. In 2023 data, 79% of Support cost sat in COGS, up from 56% in 2018.
How much SaaS Support cost is booked to COGS?
On 2023 data, 79% of Customer Support cost is booked to COGS, the delivery line, up from 56% in 2018. Customer Success, by contrast, books 68% of its cost to sales and marketing, the commercial line, on the same data year.
How many respondents want to apply AI to Support?
55% of respondents rank Customer Service and Support among their largest AI opportunity areas, third out of seven areas measured, behind new products at 82% and back-office automation at 56%. Workforce reduction ranked lowest at 15%.
Why is automating SaaS Support without baselines risky?
Support holds leading-indicator signals for churn, which has not improved in years and runs 14 to 15% on the current edition, and for the 32% of 2024 revenue loss that comes from downsell. With zero baseline metrics recorded across seven editions, any damage AI automation does to that signal will be invisible.
Last reviewed: July 2026
