ABPRO_Data Defined

Build the report before the answer.

There are twelve white dots in this grid, each one where lines cross. Try to see all twelve at once. Most people can’t: the lines around each dot decide whether it shows.

Reporting works the same way. The frame around the data decides which accounts you see, so ABPRO_ sets the frame first and holds it through every view.

Twelve white dots on a grid of lines A grid of light lines on dark blue, with diagonal lines through every crossing. Twelve white dots sit at crossings. With the grid in place most people can only see a few dots at a time; with the grid removed, all twelve are visible at once.

Twelve dots, all at crossings. Hold your eyes still and count them.All twelve. None of them moved; only the frame around them changed.

After the extinction illusion described by J. Ninio and K. A. Stevens (2000), redrawn for ABPRO_.

Universe

Every report starts by deciding who is in it: which systems, which accounts, which dates, over what period. That’s the universe. In most reporting each view decides on its own, and in a book where a few accounts carry the revenue, that’s how those accounts go missing. ABPRO_ sets the universe once and holds it across every view.

The same twelve accounts, four views.

Each dot is an account, sized by its revenue. Twelve of them, the white ones, bring in 66% of it: the twelve dots from the grid above.

Each view sets its own universe

How most reporting works: every view, report or tool filters on its own.

Portfolio

12 of the 12 in view

Filter: all accounts, last 12 months

Every account is in.

Revenue, read forward

3 of the 12 in view

Filter: only accounts created in the last 6 months

Most of the big accounts are older than that.

Revenue, read back

8 of the 12 in view

Filter: standard pricing only

Big accounts often have custom pricing.

Sales

7 of the 12 in view

Filter: only accounts with a sales rep

House accounts, with no rep, drop out.

Every view looks complete. Move between them and you never see all twelve at once, so the accounts that carry the business look different on every tab, and the imbalance between them is lost.

One universe across every view

How ABPRO_ works: the universe is set once, and every view reads it.

Portfolio

12 of the 12 in view

Universe: all accounts, last 12 months

Revenue, read forward

12 of the 12 in view

Universe: all accounts, last 12 months

Revenue, read back

12 of the 12 in view

Universe: all accounts, last 12 months

Sales

12 of the 12 in view

Universe: all accounts, last 12 months

All twelve, in every view. Change the universe on purpose and every view changes with it; nothing changes because you switched tabs.

A book of 60 accounts. Rings mark accounts a view’s filter leaves out.

Decide who is in the report before you ask it anything.

Set the universe first and every answer is read on the same accounts, so answers compare. ABPRO_ is multi-universe: it ingests and connects many universes (revenue, investment and any other source of record) into consistent views, and within any view the universe is set and held across the reporting.

Population

Who is counted: qualified only, test and QA excluded, any dimension excluded by value.

Timeline

Which clock: when the account was created or the revenue generated; when the spend occurred or the activity logged. Why there are two.

Window & grain

How far back, how fine: a count of periods, at daily, weekly, monthly, quarterly or yearly grain.

Layers

What a number is made of: any view split by up to two dimensions, with the layers summing to the total.

Timeline

Revenue and investment each run on two clocks. An account is created once and earns for months after; spend lands in one week, and the leads, appointments and sales it buys arrive over the weeks that follow. The clocks don’t line up one to one, so every report has to say which it reads.

Revenue

When the account was created (the approval cohort), and when the revenue was generated

Revenue, R2L: approval cohort by statement monthApproval cohorts January to July down the side, statement months January to July across the top. Each cohort earns revenue from its own month onward, so each row starts one column further right; shading is brightest in a cohort's first months. A Total column gives each cohort's revenue in the range, a Total row gives each statement month, and the grand total sits where they meet. The March cohort is outlined.Revenue generated (statement month)Approval cohortJanFebMarAprMayJunJulTotalJanFebMarAprMayJunJulTotalRevenue, L2R: approval cohort by months since approvalThe same approval cohorts down the side, months since approval 0 to 6 across the top. Every cohort starts at month 0, and shading is brightest in the first months. Older cohorts reach further right. A Total column gives each cohort's revenue to date, a Total row gives each month since approval, and the grand total sits where they meet. The March cohort is outlined.Months since approvalApproval cohort0123456TotalJanFebMarAprMayJunJulTotalRevenue, R2M: each approval cohort's investment, then revenue returned per $1 at months 0, 1, 3, 12 and 60Approval cohorts January to July down the side. The first column is each cohort's investment; the next five are the revenue it has returned per $1 invested at months 0, 1, 3, 12 and 60 since approval, each column shaded on its own scale. Checkpoints a cohort has not reached yet show its baseline forecast, drawn fainter with a dashed outline. An Avg row under July averages the cohorts. The March cohort is outlined.Returned per $1, by monthApproval cohortInvestment0131260JanFebMarAprMayJunJulAvg
R2L: each approval cohort by statement month. A cohort starts in the month it was approved, so each row starts one column further right, and every month reads back to the cohorts that produced it, with a total for every cohort and every month.L2R: the same cohorts by months since approval. Every cohort starts at 0, so cohorts of different ages line up and compare like for like, and each row’s total is the revenue the cohort has generated to date.R2m: each approval cohort’s investment, then the revenue it has returned per $1 at months 0, 1, 3, 12 and 60. Checkpoints a cohort hasn’t reached yet show its baseline forecast, outlined. The Avg row averages the cohorts.

Investment

When the spend occurred, and when the activity was logged

Investment, TLD: sales by week and day, counted on the investment dateOne metric, sales. Weeks 1 to 6 down the side and days Saturday to Friday across the top; each cell is one day. A Total column gives each week, a Total row gives each day across the weeks, and the grand total sits where they meet. Sales are counted on the investment date. Under the grid, two yellow rows give each day's cost per sale and conversion rate (sales per lead). Week 3 is outlined.Day of the weekWeekSatSunMonTueWedThuFriTotalW1W2W3W4W5W6TotalCost PerCVRInvestment, TLD: sales by week and day, counted on the contact createdOne metric, sales. Weeks 1 to 6 down the side and days Saturday to Friday across the top; each cell is one day. A Total column gives each week, a Total row gives each day across the weeks, and the grand total sits where they meet. Sales are counted on the contact created. Under the grid, two yellow rows give each day's cost per sale and conversion rate (sales per lead). Week 3 is outlined.Day of the weekWeekSatSunMonTueWedThuFriTotalW1W2W3W4W5W6TotalCost PerCVRInvestment, TLD: sales by week and day, counted on the appointment setOne metric, sales. Weeks 1 to 6 down the side and days Saturday to Friday across the top; each cell is one day. A Total column gives each week, a Total row gives each day across the weeks, and the grand total sits where they meet. Sales are counted on the appointment set. Under the grid, two yellow rows give each day's cost per sale and conversion rate (sales per lead). Week 3 is outlined.Day of the weekWeekSatSunMonTueWedThuFriTotalW1W2W3W4W5W6TotalCost PerCVRInvestment, TLD: sales by week and day, counted on the sales dateOne metric, sales. Weeks 1 to 6 down the side and days Saturday to Friday across the top; each cell is one day. A Total column gives each week, a Total row gives each day across the weeks, and the grand total sits where they meet. Sales are counted on the sales date. Under the grid, two yellow rows give each day's cost per sale and conversion rate (sales per lead). Week 3 is outlined.Day of the weekWeekSatSunMonTueWedThuFriTotalW1W2W3W4W5W6TotalCost PerCVRInvestment, TLX: the funnel by week, counted on the investment dateSpend, visits, leads, appointments, sales and revenue down the side, weeks 1 to 6 across the top; each row is shaded on its own scale against its usual level. Spend and visits sit on the date they occurred; the funnel is counted on the investment date. Under the funnel, two yellow rows give each week's cost per sale and conversion rate (sales per lead). Week 3 is outlined.WeekFunnelW1W2W3W4W5W6SpendVisitsLeadsApptsSalesRevenueCost PerCVRInvestment, TLX: the funnel by week, counted on the contact createdSpend, visits, leads, appointments, sales and revenue down the side, weeks 1 to 6 across the top; each row is shaded on its own scale against its usual level. Spend and visits sit on the date they occurred; the funnel is counted on the contact created. Under the funnel, two yellow rows give each week's cost per sale and conversion rate (sales per lead). Week 3 is outlined.WeekFunnelW1W2W3W4W5W6SpendVisitsLeadsApptsSalesRevenueCost PerCVRInvestment, TLX: the funnel by week, counted on the appointment setSpend, visits, leads, appointments, sales and revenue down the side, weeks 1 to 6 across the top; each row is shaded on its own scale against its usual level. Spend and visits sit on the date they occurred; the funnel is counted on the appointment set. Under the funnel, two yellow rows give each week's cost per sale and conversion rate (sales per lead). Week 3 is outlined.WeekFunnelW1W2W3W4W5W6SpendVisitsLeadsApptsSalesRevenueCost PerCVRInvestment, TLX: the funnel by week, counted on the sales dateSpend, visits, leads, appointments, sales and revenue down the side, weeks 1 to 6 across the top; each row is shaded on its own scale against its usual level. Spend and visits sit on the date they occurred; the funnel is counted on the sales date. Under the funnel, two yellow rows give each week's cost per sale and conversion rate (sales per lead). Week 3 is outlined.WeekFunnelW1W2W3W4W5W6SpendVisitsLeadsApptsSalesRevenueCost PerCVR
TLD: one metric (here, sales), weeks down the page and days across, Saturday to Friday, with a total for every week and every day. Spend always sits on the day it occurred; the funnel sits on the date you choose. Cost Per (spend per sale) and CVR (sales per lead) sit underneath.TLX: the funnel with time across the page: spend, visits, leads, appointments, sales and revenue, week by week, each row on its own scale and counted on the date you choose. Cost Per (spend per sale) and CVR (sales per lead) sit underneath.

The March cohort is outlined in both Revenue views, and week 3 in both Investment views.

The Universe is Bound by the Timelines Referenced.

The timeline is set in the universe, so every view re-buckets on the same clock and the same population, and a figure opened from a summary carries the clock it was computed on. Leads, appointments and sales sit on the date the universe chooses, so Marketing and Sales count the same event the same way.

Mapping

Every system keeps its own IDs, names and clock. The mapping aligns them, across disjointed timelines and systems, into one reporting language, so one universe can be laid over another and the math behind every report and forecast still holds.

Sources, each in its own language

  • Statements & billingMerchant or customer IDs by statement month, from the summary export or MASS files
  • CRM & funnelLead IDs and owners, with a date at every stage
  • Ad platforms & spendCampaign IDs by channel and day
  • Commission & team costRep names by pay month
  • Budgets & targetsPlan lines by fiscal month

Maps, kept as tables

  • AccountsOne account, whatever ID each system gives it
  • PeopleReps, ISOs and teams, in every system’s spelling
  • CampaignsEvery lead tied to the source and spend that bought it
  • PricingPlans grouped the same way everywhere
  • TimelinesEvery date kept, labeled with its clock

One reporting language

  • Every metric defined onceWith its variables and dependencies documented
  • Multi-universeMany universes connected into consistent views, each held across the reporting
  • OverlaysOne universe laid over another on matched accounts and clocks
  • ForecastsOn the same definitions as the reports they extend

Maps are built with your team at setup and kept current as sources change. Transforms run with tests on every refresh, so a broken column never reaches a view.

Overlay across universes.

Because every universe speaks the same language, one can be laid over another without breaking the math.

Revenue return per $1

Spend by the month it occurred, laid over revenue from the cohort it bought: the baseline revenue return at 1, 3, 12 and 60 months.

The accounts above the line, traced back

The few accounts that carry the book, traced to the campaign, rep and week of spend that produced them, so the next dollar goes where the last great account came from.

Reps ranked on revenue

Sales activity laid over the revenue those accounts generated, so the leaderboard ranks what was produced.

Forecast over plan

Every cohort projected forward on its own history and laid over budget, on the same definitions as the actuals.

Every number the book runs on.

Each metric defined once, split by any layer, and checkable back to its column.

PortfolioThe book as it stands

  • Net revenue by statement month
  • Processing volume and take rate
  • MIDs on statements, new and lost
  • Concentration in the top accounts

Revenue and retentionCohorts, both directions

  • Cohorts forward from the first statement
  • Months attributed back to their cohorts
  • Lifetime and in-range revenue
  • Retention and churn rates by cohort

Marketing and acquisitionSpend to sale, week over week

  • Spend by channel
  • Cost per lead, appointment and sale
  • Conversion between every stage
  • Period to date against last year

SalesRanked on revenue, not activity

  • Rep and ISO leaderboards on revenue
  • Commission against that revenue
  • Weekly sales KPIs on their own dates

Forecast and planningWhere the book is heading

  • Every cohort projected forward
  • Forecast over budget and targets
  • Revenue return per $1 against baseline

Universe and drill-downOne frame, every view

  • Many universes, consistent views
  • R2L, L2R, TLD and TLX
  • Up to two layers on any view
  • Click any figure to see its source

Covered in one platform.

Revenue and retention analytics, marketing reporting, sales reporting and commission, and forecasts against budget: ABPRO_ covers each as part of one platform, in one reporting language.

What the team needsIn ABPRO_
Revenue and retention analyticsCohorts read forward and back, retention and churn rates by cohort, lifetime revenue, concentration
Marketing data and reportingSpend to sale, cost per stage, periods that compare, landing-page tests
Sales reporting and commissionRep and ISO leaderboards, commission against the revenue produced
Forecast and budgetEvery cohort projected forward and laid over budget
One set of numbersMulti-universe: one reporting language, so revenue, sales and marketing read the same number

See every view on a demo portfolio.

Book your demo and we’ll set a universe, take it through every view, then review your book with you.

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