Predictable revenue and profit growth
Owner and CEO
See the real reasons behind what happens to revenue, and know what to do to keep the growth going.
Who it is for
Predictable revenue and profit growth
Know the cause, not the versions
You no longer have to guess why revenue was there yesterday and gone today. Aplora shows what is actually happening instead of another monthly round of blame between sales and marketing. You see the real causes and know what to do to keep growth going.
Decide on data, not instinct
Large companies have always decided on data: they employed the analysts who prepared it. Everyone else was left with instinct. AI removed that gap — there is finally someone to look at every deal, every conversation and every document, so decisions rest on fact rather than feel.
Grow without hiring in proportion
When more volume demands proportionally more manual work, margin falls as you grow. We find the operations that repeat and consume the team's capacity, and take them out of the process — so the next client does not add another headcount.
Questions the data cannot answer today
- Why did revenue move this month — and how much of that will repeat next month?
- Which commercial process limits growth more than the others right now?
- What does the gap between the best and the average people cost the company?
- What happens to the operational load if volume doubles?
What stays in your hands
Stays with you
- a process map showing where money or capacity is lost
- an effect model: what the result consists of and under which assumptions
- priorities — which process goes first and why that one
- the criteria by which an initiative continues or stops
The metrics this moves
- revenue and gross margin
- lead-to-deal conversion
- customer acquisition cost
- output per employee
What we use for this
Aplora Sales
Turns calls, CRM data, and your own sales methodology into a system that drives management action.
Explore this solutionAI Workflow Automation
Removes repetitive manual steps from end-to-end business workflows.
Explore this solutionDocument & Reporting Automation
Cuts the time spent producing documents and reports and moving data between systems.
Explore this solution
Cases
How this looked for others
ManufacturingAplora SalesClient under NDA
The best salesperson's playbook rolled out across a manufacturer's whole sales team
The team's result rested on two people; the rest closed several times less on the same workload. Nobody knew what exactly the leaders did differently: conversations were not reviewed, and the gap was explained away as “experience”.
- Conversion to a sale three months after rollout
- +25%
- Conversion to a sale after six months
- +72%
EdTechAplora SalesWe validated the system inside our own operations first
Conversation review in an admissions funnel: how we validated the system on ourselves
Conversation quality was judged from a few recordings a month. The reasons for a no stayed a hypothesis, commitments were captured from memory, and the CRM was filled in after the fact and only partially.
- Conversion from hot leads
- ×3.3
- Share of calls that went nowhere
- −40 pp
- Share of second contacts
- +30 pp
EdTechAplora SalesWe validated the system inside our own operations first
Lead scoring in the intake funnel: advisors stopped calling everyone in order
Hot and cold leads sat mixed together. An advisor spent the day on people with neither a reason nor an intent, while leads showing clear readiness went cold in the queue.
Read the case
EdTechAplora SalesWe validated the system inside our own operations first
The funnel from lead to purchase in one picture: where the money was actually leaking
Channels were compared on cost per lead rather than on the eventual sale, so a cheap channel looked better than an expensive one even when it brought people who don't buy. Nobody counted the losses between stages: for marketing the funnel ended at the webinar, for sales it began at the call.
- Google versus Facebook lead quality by conversion to sale
- ×3 in Google's favour
- Conversion at four or more touches versus one
- ×4–5
- Potential estimate: sales from the hot-lead pool identified
- +14–22 sales
eCommerce and retailAI Workflow AutomationClient under NDA
An online store's support front line stopped growing with its order volume
Operators were absorbed by repeat questions, complex enquiries got lost in the queue, and the knowledge base went stale faster than anyone could fix it.
- Enquiries that reach an operator
- −25–40%
- Ticket handling time
- −30–50%
- Support satisfaction (CSAT)
- +10–18%
Marketing and digital agenciesDocument & Reporting AutomationClient under NDA
The first ten days of the month stopped going into client reports
For the first 8–10 days of the month the team assembled reports instead of doing project work. Approvals dragged, payments moved with them, and every new client meant either overtime or a hire.
- Time to prepare a monthly report
- 10 days → 5 minutes
- Projects handled by the same team
- +30%
- Monthly saving on manual work
- ≈$5,000
EdTechAI Workflow AutomationClient under NDA
One account manager runs twenty-five cohorts instead of five
Account managers kept cohort statuses in their heads. Every new course meant either overload or loss of control: missed classes and blown deadlines surfaced after the fact, when the student had already fallen behind.
- Cohorts per account manager
- 5 → 25
- Cost of running one course
- −40%
EdTechDocument & Reporting AutomationClient under NDA
Course materials stopped going stale faster than they could be updated
A new module or an update took weeks. The load on methodologists grew faster than the team, and the product aged between releases: a student would see an example on a library version that no longer exists.
- Speed of releasing and updating material
- ×10
- Share of manual work in content production
- −50%
- Cost of producing content
- −40%
Consulting and professional servicesAI Workflow AutomationClient under NDA
Answers stopped living in people's heads: search across company documents, with the source attached
Finding an answer took time, and what turned up could be out of date. Different people answered the client differently, and the surest route was to ask a colleague — that is, to interrupt one more person.
- Time spent finding information
- −40–60%
- Errors caused by out-of-date instructions
- −20–35%
EdTechAplora SalesWe validated the system inside our own operations first
A sales candidate is assessed from a recorded conversation, not from the impression they leave
Hiring decisions were made on the impression the interview left. Interviewers assessed candidates differently, a mistake surfaced a month into the job, and the head of sales spent hours on reviews and arguments about who was better.
Read the case
EdTechAplora SalesClient under NDA
A school's sales team stopped depending on any one advisor's discipline
There was no priority, and strong leads were lost in the queue. Conversation quality was checked on a sample, follow-up depended on whether the advisor remembered, and the manager spent hours listening to recordings instead of working the bottlenecks.
- Progression to a second contact
- +22%
- Overall conversion to a deal
- +5 pp
- Advisor time spent on admin
- −70%
eCommerce and retailAI Workflow AutomationClient under NDA
Nurturing stopped being one campaign to the whole list
The customer profile was described from gut feel, nurturing was launched by hand and identically for everyone, and hypotheses took weeks to test. Sales received leads with no readable warmth and spent time on people who were not ready.
- Stage-to-stage funnel conversion
- +30–40%
- Conversion to sale
- +20–50%
EdTechAI Workflow AutomationClient under NDA
AI across four departments of a school: marketing, sales, content and operations in one loop
Growth meant one of two things: losing quality, or hiring into every department in proportion to volume. No single department was the bottleneck — the seams were, and nobody owned them.
- Revenue
- ×3 in 4 months
- Operating costs
- −60%