Strategy and growth. Chief Revenue Officer
AI for the CRO Office
You don’t lose revenue at the close. You lose it long before.
A lead waits two days for a call. A discount goes out because it always has. A deal sits in commit for a month after the buyer went quiet. None of it shows up until the quarter ends. We map the CRO Office the way your team actually sells, then put agents where revenue leaks.
The short answer
It protects revenue at the points where it usually leaks. Agents recommend price and discount per deal from live market data, flag deals at risk before they slip, follow up every lead within minutes and warn account owners about churn weeks earlier.
Your sellers keep the relationships and the negotiation. The agents take the admin, the chasing and the guesswork, so the number you commit is the number you close.
The mandate
Hit the number. Every quarter. At a price that protects the margin.
What the board measures you on
Revenue against target
By segment, region and product
Forecast accuracy
Commit against what closed
Win rate
By segment and competitor
Price realisation
What you got against list
Net revenue retention
Renewals plus expansion
Sales cycle length
And where deals stall
The canvas of the CRO Office
Most sales AI only helps sellers write emails. The bigger money sits in pricing, forecast and retention, and in the rules you answer for.
Canvas 1
What you run
The revenue engine, every day.
Sales teams and pipeline
Territories, quotas, pipeline reviews and deal reviews.
Pricing and discounting
List prices, discount bands and the deal desk.
Partner and channel revenue
Resellers, distributors, marketplaces and affiliates.
Customer success and renewals
Onboarding, adoption, renewals and expansion.
Revenue operations
CRM, sales tools, reporting and the weekly forecast.
Canvas 2
What you answer for
The things the CEO and the CFO hold you to.
The forecast
The number you commit, and whether it lands.
Deal approvals
Discount approvals, non standard terms and deal desk rules.
Commission plans
Incentives for sellers and partners, paid accurately.
CRM data quality
Whether the pipeline in the CRM is real.
Where value leaks
Each one is small in a single deal. Across a year of deals, it’s often the gap between plan and actual.
01
Price leakage
Discounts go beyond what the deal needs, and prices lag the market.
Pricing agents. Track competitor and market prices, compare similar deals and recommend a price and discount band for each one.
Price realisation
Average discount
02
Pipeline that isn’t real
Stale deals and hopeful close dates inflate the forecast.
Deal signal agents. Read emails, meetings and call notes, compare them with deals that closed before and flag the ones slipping.
Forecast accuracy
Slipped deals
03
Leads that go cold
Marketing hands over a lead and nobody calls for days.
Lead agents. Qualify every lead, route it to the right seller and send the first response within minutes, with context.
Speed to lead
Lead to opportunity rate
04
Seller time lost to admin
Reps spend hours on CRM updates, recaps and internal reports.
Sales assistant agents. Log activity, write recaps, draft follow ups and prepare account briefs before every meeting.
Selling time
Meetings per rep
05
Churn spotted late
Renewal risk shows up weeks before the renewal date.
Health agents. Watch usage, support tickets and sentiment and alert the account owner months ahead, with a suggested next step.
Net revenue retention
Gross churn
06
Partner commission errors
Commissions are worked out by hand from complex agreements.
Contract agents. Read every partner agreement and check each commission line against the deal and the terms.
Commission accuracy
Partner yield
Process lifecycles
We start from the systems you already run. The orange steps are where an agent takes on the work, so your sellers and managers spend their time on customers and calls that matter.
Lead to cash
Every new deal
Lead
Qualified and routed in minutes
Agent
Discovery
Opportunity
Proposal
Drafted from the account brief
Agent
Negotiate
Close
Handover
Full context to success
Agent
Typical systems. Salesforce, HubSpot, Microsoft Dynamics, Gong, Outreach
Quote to contract
Every quote and renewal
Configure
Price
From live market data
Agent
Approve
Within rules the deal desk sets
Agent
Contract
Sign
Typical systems. CPQ, deal desk tools, DocuSign, ERP
Forecast cycle
Weekly
Rep call
Deal check
Evidence from activity
Agent
Manager roll up
Commit
Actual against commit
Where it slipped and why
Agent
Typical systems. CRM, Clari, spreadsheets, BI
Renew and expand
Every customer
Health check
Usage, tickets, sentiment
Agent
Renewal
Upsell
Signals from usage
Agent
Cross sell
Typical systems. Gainsight, CRM, product analytics, billing
Agent intervention point
The CRO control tower
Not a forecast built from what reps typed on Friday. A live view from what is really happening in every deal and account, with a brief on what needs your call.
Illustrative
CRO control tower
Sample data to show the view. Not client results.
Pipeline coverage
3.1x
▼ 0.3x vs target
Win rate
27%
▲ 2 pts
Price realisation
91.5%
▲ 1.8 pts
Average discount
14.2%
▼ 2.1 pts
NRR
108%
▲ 3 pts
Commit at risk
€2.3m
7 deals flagged
This week’s revenue brief
Slipping
Three commit deals have no buyer contact in 18 days
€1.4m in total. Owners and next steps listed. Deal signal agent
Price
Competitor cut list prices 6% in two markets
Recommended response by product ready for the deal desk. Pricing agent
Expand
Eleven accounts past 90% of their licence limit
Upsell briefs drafted for account owners. Health agent
Leads
Median first response down from 26 hours to 9 minutes
Since lead agents went live in Benelux
Average discount by region
DACH
10.1%
Benelux
12.3%
Nordics
13.4%
South EU
18.0%
Southern Europe discounts 5 points above band on deals under €50k. Deal desk review suggested.
Illustrative example. Figures are invented to show how the view works. In discovery we build it on your own data and KPIs.
Your industry changes the agenda
The canvas stays the same. How revenue is won and lost does not. Here’s the question we hear most from revenue leaders in each industry, and where agents help first.
CPG
How do we get a return on trade spend when retailers set the terms?
Trade promotion and price realisation
FMCG
How do we pass on cost increases without losing listings?
Price and pack recommendations by customer
Retail
How do we match competitor prices without matching every one?
Competitor price tracking and response
D2C
How do we grow repeat revenue, not just first orders?
Churn signals and next order offers
Automotive
How do we convert leads across a dealer network we don’t control?
Lead routing and dealer follow up
Healthcare
How do we win contracts in tenders that run for months?
Tender response and contract renewals
Energy
How do we keep business customers when contracts come up for renewal?
Renewal risk and contract pricing
Manufacturing
How do we stop price leakage across distributors and quotes?
Quote pricing and distributor rebate checks
Logistics
How do we quote fast enough to win and still make money on the lane?
Spot quote pricing and lane margin
BFSI
How do we grow share of wallet without pushing the wrong product?
Next best offer within suitability rules
B2B technology
How do we forecast accurately and grow net revenue retention?
Deal signals, health scores and expansion
Proof
Uplift in eCommerce sales from real time competitor pricing agents
Leading home appliances company. CRO and CMO Office
Of AI pricing suggestions accepted by the pricing team
Leading home appliances company. CRO Office
Increase in warranty conversions
Automotive insurer, GCC region
How the CRO Office connects
Revenue depends on the lead marketing hands over and the customer service keeps. The agents that serve the CRO Office share the same platform and data as the offices on either side, so the baton doesn’t drop.
How we’d start
Pilot 1
Price and discount intelligence
↳
Competitor and market prices tracked for your main products
↳
A recommended price and discount band for each deal or quote
↳
Run in one region or product line, against a control group
Your decision
Whether to roll it out to every region and the deal desk.
Pilot 2
Deal signals and forecast
↳
Every open deal checked against real activity and past wins
↳
At risk deals flagged weekly, with the reason and a next step
↳
Run alongside your current forecast for one or two quarters
Your decision
Whether the agent’s view becomes part of how you commit.
Both run under our Validation First Framework. They’re tested on your own data before you commit a larger budget, and if the numbers don’t hold, we tell you.
Your intervention map
Bring this year’s number and the part of it you’re least sure about. We bring the CRO Office canvas. In one session we map it to your sales motion and stack, and mark where agents would pay back first.
01
Your CRO Office canvas
What you run and answer for, checked against how your sellers, partners and success team really work.
02
Your value chain
The canvas placed on your industry and your route to market, with the systems behind every number.
03
Your intervention points
Each leak with an agent design, its controls and the KPI it moves. Delivered as a mind map, an architecture view or an interactive dashboard.
AI for the CRO Office, answered
What can AI do for the CRO Office?
Agentic AI protects revenue at the points where it usually leaks. Agents recommend price and discount per deal from live market data, flag deals at risk before they slip, follow up every lead within minutes, update the CRM for sellers and warn account owners about churn weeks earlier. The result is more revenue at a better price and a forecast you can stand behind.
How does AI improve sales forecast accuracy?
By reading what actually happens in each deal instead of what the seller enters. Deal signal agents look at emails, meetings, call notes and buyer engagement, compare them with deals that closed before and flag the ones that are slipping. Managers review evidence, not opinions, before they commit a number.
Can AI reduce discounting without losing deals?
Yes. Pricing agents track competitor and market prices and look at what similar deals closed at, then recommend a price and a discount band for each deal. Sellers and the deal desk keep the final say. In one client, the pricing team accepted 70% of AI suggestions and eCommerce sales rose 15%.
Will AI agents replace sales reps?
No. They take the admin off your sellers. Agents log activity, write recaps, draft follow ups and prepare account briefs, so reps spend more of the week with customers. The relationship, the judgment and the negotiation stay with your people.
Do we need to replace our CRM?
No. Agents work on top of Salesforce, HubSpot, Microsoft Dynamics and the call, pricing and billing tools you already run. Most of the value comes from joining data those tools hold separately, not from adding another system.
Where should a CRO start with agentic AI?
With price or forecast. A pricing pilot shows its effect on margin within a quarter. A deal signal pilot runs alongside your current forecast, so you can compare both before you change how you commit. Each one gives you numbers to take to the CFO before a larger rollout.
