Your data knows who is about to leave, who is worth a conversation, and what has worked before. What would you ask it? Your data knows who is about to leave, who your best customers are, and where to find more like them. What would you ask it? Your data knows how many people you have helped and how, and which supporters are worth a personal conversation. What would you ask it?
You get the result, not the homework.
One piece of work with a finish line: a written report that says what to do first.
You see the price of each stage before you agree to it.
Tell me what you’d ask, and I’ll say if it’s in there.
Customers, quotes, orders, notes and emails, in whatever systems and spreadsheets they ended up in.Case notes, registers, supporter records, applications and emails, in whatever systems and spreadsheets they ended up in. It has been going in for years, and reading it back has never been anybody’s job. The data is there, but it’s all over the place, and your team has a day job.
You can hand it over in whatever state it is in. Nothing needs tidying first.
What your records say counts for more than how many there are. A hundred logged conversations with real notes can hold more than ten thousand bare rows.
Your customers rarely announce that they’re leaving. Their orders get smaller, the gaps get longer, and by the time anyone notices, they have gone.
The time goes too. Every question your records could answer gets worked out by hand, or settled by a guess.
What is one regular customer worth to you a year?
Regular donations lapse without anyone announcing it, and your total only shows the effect months later.
The time goes too. Every question a funder or trustee asks gets answered by hand, or not at all.
What is one regular supporter worth to you a year?
Your records hold the customers who went quiet, the patterns in what people buy and when, the relationships that bring in work, and the people worth a conversation this quarter.
Your records hold the difference you have made to the people you support, the supporters who have stopped giving, what the funders who said yes had in common, and what happened to people after they left you.
Real conversations and projects in progress this year, described without names.
Renewal notes going back years, and members whose businesses have grown past their fee band. The work is to find who is due a conversation before the renewal window, and who is in the wrong band.
A membership body, 1,700 membersUseful to: Renewals and finance
Years of order history show the pattern forming months before anyone notices, in time to pick up the phone.
A trade printer, years of order historyUseful to: Account managers and the owner
Nobody can say for certain who sends the most work, so the same people are invited to everything out of habit.
A law firm, twenty years of mattersUseful to: Partners and business development
Around three-quarters of members buy the insurance, and the proportion has been slipping. Someone has been comparing mailings against sales by hand in a spreadsheet, and nobody yet has a plain answer to why.
A membership organisation with an insurance productUseful to: Membership and commercial teams
Their client history showed that the work they were proudest of and paid best for came from one kind of business, not the one they called their niche.
A brand consultancy, six years of clientsUseful to: Leadership, and the marketers they work with
Five hundred people get the newsletter and respond well each time, with no view of who buys when. Three years of orders should show which customers have a rhythm of their own.
An online retailer, three years of ordersUseful to: Marketing and email teams
Every support worker writes up every session. The outcomes funders ask about are all in there, written as stories, so nobody can count them without going back through everything by hand.
A support charity, eight years of case notesUseful to: Fundraising and trustees
The charity counts its events and participants, and what taking part changes for someone has never been drawn out of the registers and write-ups.
A participation charity, over a hundred eventsUseful to: Founder and fundraising
A decade of records holds the pattern: who stopped and what they had responded to before.
A medical charity, a decade of supporter recordsUseful to: Fundraising and finance
Every application is filed, and so is every outcome, but nobody has read them side by side. The work is to find the pattern in what funders rewarded, so the next bid starts from evidence rather than instinct.
A grant-funded charity, years of applicationsUseful to: Bid writers and the chief executive
Every campaign goes out to thousands, and whether it moved anything is answered by a colleague matching mailings to sales by hand. Joined properly, the records show which messages were followed by a purchase.
A membership charity, a decade of member recordsUseful to: Membership and finance
Each month a manager goes back through the case records to count by hand what the local authority asks for, when the counts are already in the notes.
A service charity, monthly returns counted by handUseful to: Service managers and operations
You decide on each stage with the last one’s result in hand, and you can stop after any of them.
Stage 1 is usually a matter of days. The full report depends on how quickly access comes through.
You find out whether your data can answer what you’re asking, and work out the questions with me if they aren’t clear yet.
You receive a written assessment either way, including a plain statement if the data cannot yet support the work.
From £750 + VAT
You see the whole process work on a portion of your data before the full set is committed.
You receive a working result on that portion, and a scoped, priced plan for the full report.
Your complete dataset is brought up to date, with gaps filled from trusted public sources. Then all of it is read against your questions.
You receive the report and the actions for your team, presented in person.
When your data has moved on or new questions come up, stage three can run again. The connections and clean-up built the first time are reused unless your systems have changed, so it costs less than the first report. If the picture hasn’t moved enough to justify it, I’ll say so.
Only need a list brought up to date and its gaps filled? See Data enrichment, a smaller project on its own.
Founder, Riselabs
I started Riselabs because the answer an organisation goes looking for is often already in its own records; nobody has the time to read them, so I do.
What comes back goes to the people who act on it: your own team, and the specialists you already work with on things like website traffic.
What comes back goes to the people who act on it: your own team, and the fundraising and communications specialists you already work with on how to tell the story.
You can, if you already know your data is sound and which questions you want answered. If you’re not sure, the first stage settles it before you commit to a full run on data that turns out to be thin.
A dashboard shows what is happening, and somebody still has to find the time to look and work out what to do. One client asked me for a dashboard before anything else, and I said it would not give them the answers they need. What they needed was answers to their questions, and something to do about them, in writing.
It usually is. Years of sporadic use, outdated contacts, duplicates and notes in free text are the normal starting point, and working through them is part of the job. The one thing that can’t be fixed is data that was never recorded, and you find that out in the first stage.
For example: A property company’s occupier list turned out to hold twenty-seven leases ending inside the year and a dozen tenants who no longer existed.
Yes, and it’s the normal case. How private the data is gets agreed with you before anything is provided. Anything sensitive can be anonymised by script on my own systems if required, and written data terms are put in place for anything that needs them.
For example: One charity’s partner list turned out to name the wrong person at most of the organisations on it.
No. Working out the right questions from what you have recorded is part of the first stage.
For example: A first question can be as plain as: who used to buy from us and stopped?
For example: A first question can be as plain as: when someone left, did we close their case well?
If someone on your team has a few clear weeks, they can. This is for when nobody has, and you want two things at the end: a view from someone who does this all day, and the work of pulling your records together from every system they sit in, whatever shape they’re in. A mix of software, AI and tools built for your particular data does the first reading; every finding is checked against your records before it reaches you.
Send the question you keep coming back to, and roughly what you hold. You’ll hear whether your data can answer it, and what it would cost. Even a half-formed question is a good place to start.
Or book twenty minutesTwenty minutes with Jackson. No slides.
