Built for B2B distributors and manufacturers
Reter finds at-risk revenue before you can see it. Not with rules or thresholds, but by learning every customer's distinct behavioral patterns.
Your ERP tells you what happened. Your team tells you what they think is happening. Reter shows you what's coming, what to do about it, and whether it worked.
Every retention tool built before Reter starts with the same assumption: that you can define in advance what a declining account looks like, write a rule for it, and apply that rule uniformly across your entire customer base.
That assumption is wrong.
A rule is a guess made in advance. It captures what someone decided to watch for, not what actually precedes decline in your specific customer base, with your specific products, across your specific markets. Every account gets the same rule regardless of who they are, how they buy, or what their history with your business looks like.
Rules-based systems do not learn. They do not adapt. They fire when the condition is met and stay silent when it isn't, whether or not the condition is the right one for that account, that relationship, or that moment.
The category leaders in B2B revenue retention built their platforms before the widespread adoption of AI and machine learning. Rules. Thresholds. Scorecards. The same logic dressed up with AI branding. The underlying capability has not changed.
Reter is built on a different foundation entirely.
Every company that deploys Reter gets a tailored ecosystem of machine learning models trained exclusively on their own customer data. Not a shared model. Not an industry template. Models that have studied your accounts, your customers, your patterns. Nothing else. Every order placed. Every product purchased. Every category entered and exited. Every relationship expressed through the decisions your customers make over time. The models learn what normal looks like across every dimension of account behavior your data can reveal, watch continuously for deviation from it, and get more accurate the longer they run.
This is what it means to learn your business rather than approximate it.
The models see what rules cannot: the account whose revenue looks stable but whose relationship is quietly eroding. The account whose behavior has shifted in ways that have historically preceded departure. The account that passes every threshold a human would configure and is on its way out.
Rules encode what someone already knew. Reter discovers what the data actually shows.
Business AI should know your business — and tell you what's coming, while there's still time to act.
By the time an account shows up in a revenue report, the decision has already been made. The competitor was chosen weeks ago. The order pattern shifted months ago. The conversation that would have saved it didn't happen, because nobody knew it needed to.
Reter alerts your teams months in advance. The models trained on your business learn what every account's behavior looks like when it's healthy, and recognize the deviations that have historically preceded decline — months before the revenue line moves.
This is the difference between reporting and prediction. A report tells you what already happened. A prediction tells you what's about to happen, with enough time to change it.
The vast majority of accounts heading toward material decline are flagged with months of advance warning — long before the impact appears in the revenue numbers, and long before the rep would have noticed on their own.
That window — between when the data knows and when the loss becomes real — is where Reter does its work. It's where saved revenue lives.
Foresight isn't a feature. It's the entire reason the rest of the system matters.
The rep sees which accounts are drifting before the manager asks. The manager sees it before the GM asks. The GM sees it before the board asks. And the customer gets a call before they thought anyone noticed.
Nobody is the messenger. Nobody is the gatekeeper. The org stops being a telephone game and starts being a nervous system — one that reaches all the way to the customer on the other end of it.
Now your reps see what the system sees. Reter doesn't replace them — it tells them what your data already knows and gives them a clear path to act on it.
That ecosystem of models watches every account continuously. When an account starts pulling back across any dimension your data can see, the system catches it. Not because a rule fired. Because something changed from what the system learned to expect from that specific account.
The vast majority of accounts heading toward material decline are flagged before the impact appears in the revenue numbers, with months of advance warning before it becomes visible.
The models tell you which accounts are at risk. The intelligence profiles tell you why.
A flag without context is noise. A flag with context is a conversation starter. Reter explains why an account is at risk: competitive displacement, pricing pressure, ownership changes, buying group shifts, product mix erosion, drawing on everything the system knows about that account's history and behavior. The rep walks into the call with a hypothesis, not a guessing game.
Each flagged account comes with a specific action tied to the revenue at stake: who to call, what to address, and why now. The system drafts outreach from the account's entire contextual history so the rep reviews and sends in seconds rather than researching from scratch. Every action is tracked. Every outcome is measured.
Not a dashboard to interpret. A managed revenue pipeline with accountability built in.
Your best rep knows their top 30 accounts by instinct. The rest get attention when something goes wrong. By then, it's too late. Reter monitors every account, every day, and shows your entire organization how they can act on the intelligence.
Which rep has the most at-risk revenue? Who acted on their flags this week? Who didn't? You'll know in 30 seconds without asking anyone.
Every flagged account gets a recommended action. If nobody acts, the system follows up and escalates to you when it matters. Problems don't disappear into a spreadsheet.
Which accounts were saved? Which were lost? Which interventions worked and which didn't? The evidence is there when leadership asks.
You used to coach on activity. Did you make the calls. Did you update the pipeline. Now you coach on outcomes — which customers were drifting, what your reps did, whether it worked.
The conversation changes shape. Not what's going on with your book but what worked for the accounts that recovered, and what would you do differently on the ones that didn't.
Reps stop defending. Managers stop probing. The hour you used to spend surfacing problems, you spend solving them — for the customer who would have left.
Behavior changes. Not because you told reps to change it. Because the evidence of what works is in front of everyone, every week. The rep gets better. The customer gets served. The next customer gets served faster.
Most systems monitor total revenue. If the number holds, the account looks healthy. But total revenue is a blunt instrument. It hides two problems that compound silently: product mix erosion and margin degradation.
Reter monitors product-level purchasing patterns. When an account drops an entire category, narrows their product mix, or shifts away from high-margin lines, the system flags it, often months before the impact reaches the revenue line.
Every account has a point of no return. Before it: reachable. After it: effectively gone. The gap between those two states is measurable. And right now, your team is finding out which side an account landed on after it no longer matters.
Reter watches every account against the pattern it learned from that account's own history. Not a universal timer. Not a threshold a human configured. The system knows what normal looks like for each account individually, and when an account starts deviating from its own normal, the system knows before the revenue line does.
When an account starts going quiet, your rep finds out. While the window is still open.
Every business that runs on repeat customers has accounts that stopped ordering. Some left for a competitor. Some changed their business. Some would come back if anyone called. Right now they all look the same. Gone.
Reter separates them. Every dormant account scored against its own history. How long has it been quiet relative to its own pattern. What was at stake before it went dark. The recoverable surfaced. The lost set aside. The rest put in front of the right rep with everything they need to have a productive conversation.
These accounts already know your product and your process. They don't need to be sold. They need to be asked back. Reter makes sure someone asks.
Your reps manage territories, not inbound leads. Some customers order weekly. Some order quarterly. Most of them, you only notice when they stop.
Every business that sells through reps is already sitting on a treasure trove of data about how their customers behave. Reter connects to where that data lives and puts it to work. Validated on over a decade of real customer data across multiple model generations, each measurably more accurate than the last.
Your data stays yours. Always. Reter connects to your systems, runs analysis, and stores results in your dedicated environment. No data pooling across customers.
Live in weeks, not months. No lengthy IT project. Reter connects to your existing systems. Your source systems stay untouched and your data is never pooled with other customers.
Most of the time, when Reter is quiet about an account, the account is fine. When it speaks, it's right the vast majority of the time. But the system only sees what's in your data.
A meaningful portion of accounts that eventually decline look completely healthy by every signal your customer data can surface, until the decline appears. The system cannot see the handshake deal a competitor made last week or the complaint that never got logged. Your reps know those things. Reter captures what they know and gets smarter with every interaction.
Some problems Reter finds can't be solved by a phone call. If an account is leaving because your pricing is out of line, the system will tell you that. But the fix is a business decision, not a rep action.
Reter shows you where the problem is. What you do about it is up to you.
That is why the system is built to learn from your reps, the things they know that the data does not show. Every action they take makes it smarter.
We'll show you what Reter finds in your data. Some of it will surprise you.
Find out which accounts need attention, which products are shifting, and whether your team is acting on the signals.