Revenue intelligence for subscription and carrier billing
Know which customers were worth acquiring. Before you buy more of them.
Spend sits in one system, revenue in another, and churn in a third. Nobody in the business can say which channels and campaigns actually made money. We build that answer, and we put it in writing.
Day 94
Carrier portal pays back. Paid social does not.
The problem
Blended numbers hide the decisions
Blended CAC, blended ARPU, a single churn rate. Averaged together, the channel that funds the business and the channel that quietly drains it cancel each other out, and the report stops telling anyone what to do on Monday. The numbers are usually all present somewhere: in the billing platform, the acquisition reports, the carrier settlement files. They are just never joined on the same definition of a customer.
4.2x on spend
Affiliate portfolio
Fund it
0.7x on spend
Paid social, broad targeting
Cut it
Break-even, day 94
Carrier portal placements
Watch the payback
Illustrative example. Not a client figure.
See what we answer
What you get answered
The questions your reporting does not answer
These are commercial questions, not analytical ones. They get asked in board meetings and budget reviews, and they usually get answered with an educated guess because the underlying numbers live in systems that were never joined.
Where the money goes
- Which acquisition channels generate profitable customers?
- Which campaigns deserve more investment?
- Which campaigns should be discontinued?
What a customer is worth
- When does a customer reach break-even?
- What is the projected lifetime value of the customers we acquired this month?
- Which segments deserve additional investment?
Where the growth is
- Which customers are ready for a second product or a higher tier?
- Which part of the base is worth an offer, and which is worth leaving alone?
- Which segments are we over-contacting for no return?
Where revenue leaks
- Why are customers leaving?
- Where are we leaking recurring revenue?
- How healthy is the subscription base underneath the growth?
What we do
One customer base. Three decisions. One set of numbers.
One joined view of your customers, not three products bolted together. Built once from your acquisition, billing and behavioural data, with Flybridge underneath holding the definitions steady.
Customer Value Intelligence
Know what a customer costs, what they return, and when
What you paid to acquire a customer, what they return across their lifetime, and the day they cross into profit. One arithmetic rather than three reports, because a channel is only cheap relative to what its customers turn out to be worth. Broken out by channel, campaign and cohort.
See how it worksChurn Intelligence
Keep the customers who are actually worth keeping
Not every cancellation deserves a save offer. We rank why customers leave, which of those causes you can actually move, and which cohorts carry enough value to justify the spend.
See how it worksCross-sell & Upsell Intelligence
Know which customers are ready to buy more
Subscribers pressing against the limits of their plan show it in billing data long before anyone asks them. We rank the base by readiness and name the behaviour behind each ranking, so offers go to the customers worth making them to.
See how it worksKeelShift Flybridge
One view from above the systems, not inside any one of them
The aggregator, the ad platform and the carrier settlement file each count a conversion their own way, and taxonomies get rebuilt every time someone new takes over. Flybridge is the mapping layer across all of it: one definition of a customer, a campaign and a conversion, held steady so this quarter can be compared with last. It is the reason the three answers above agree with each other.
The proof
A finding that only holds where it was built is not a finding.
Most analysis is scored on the data it was built from, which is the one place it is guaranteed to look good. Nothing here reaches you until it has been tested somewhere it has never been.
1
Held back
Customers and whole periods are set aside before the work starts, and nothing we build gets to see them. They are fixed at the beginning rather than chosen at the end, which is the only version of this that means anything.
2
Tested against them
Every finding is checked against that held-out data. What survives reaches you. What does not is reported as not having survived, rather than quietly left out of the deck.
3
Gaps stated, not closed
Where two of your systems disagree, you get the size of the disagreement. Where the evidence is thin, that sits next to the finding in writing instead of waiting for you to find it.
If it earns it, standing monthly reporting starts. If not, you keep the report.
Why not a dashboard
A dashboard reports what happened. It will not tell you what to fund.
BI tools and marketing dashboards
They visualise what each system already holds, on that system's own definition of a customer, a conversion and a month. Quick to read, and silent on the question the budget actually turns on: which spend produced customers worth having.
KeelShift™
We reconcile those systems onto one definition, answer the commercial question directly, and say plainly when your data will not carry the conclusion. You get a decision with its reasoning attached, not another tile to interpret.
Why us
Everyone has AI now. Not everyone knows where this data lies.
Mobile VAS, carrier billing and digital content from the inside, not from a case study. We have owned the churn and lifetime-value numbers inside a major operator’s value-added services business, chased revenue the aggregator report and the settlement file disagreed about, and defended a payback figure to a commercial director who had every reason to doubt it.
Anyone can point AI at a dataset now, ourselves included, and it makes us considerably faster. It will not tell you that a failed charge is not a cancellation, or that the base moved last March because the operator changed something. That is the part that decides whether the number is worth acting on.
About Us- Senior practitioners who have run acquisition, churn and lifetime-value analysis inside telecom, VAS and iGaming operators.
- Every figure traces back to the customer behaviour behind it, so your team can check the reasoning rather than take it on faith.
- Your data, your terms. Anonymised identifiers by default, processed in the EU, deleted when the work is done. On-premise available.
The offer
Start with the Revenue Diagnostic
Fixed scope, ten business days. Send an extract and you will know which of these questions your data can already answer, which ones it cannot yet, and what the answers are worth in budget. Standing monthly reporting is the step after that.
