Skip to content
Aplora
Expert scenario

Handle more orders without growing the operations team, and see sooner which customers have stopped buying.

Wholesalers and distributors: orders from retail points, item selection, invoices and shipping documents, receivables, repeat orders.

A warehouse aisle between tall racks of boxes, with a worker moving a pallet.

Key constraints

  • margin per item is thin: what saves money is cost per operation, not markup

  • orders arrive any way at all — e-mail, messenger, spreadsheet, over the phone

  • the catalogue and stock change faster than the customer's price list is updated

Industry economics

  • The cost of processing one order multiplies by their number: saving minutes beats haggling over item price.

  • An order entered with an error costs twice: wrong goods, a return and a dispute with the customer.

  • A customer who stops buying usually leaves quietly: the loss shows in the quarterly report, when winning them back is already late.

Typical processes and pains

  • Symptom

    Orders arrive in free form and are typed into the system by hand.

    Economic consequence

    An operator spends minutes on every order, and entry errors turn into wrong shipments and returns.

    How many minutes does it take to turn an e-mailed request into an order in the system?

  • Symptom

    Items are picked from the manager's memory.

    Economic consequence

    The customer never hears about an alternative or a companion item, and average order value stays flat.

  • Symptom

    Receivables are tracked by hand in a spreadsheet.

    Economic consequence

    The reminder goes out late, and the decision to ship on credit is made without the full picture.

Priority AI scenarios

Turn incoming requests into orders without manual entry

  1. 1Parse the request
  2. 2match to the catalogue
  3. 3check stock and prices
  4. 4a draft order flagging contested items
Inputs
Customer e-mails, messages and spreadsheets, the catalogue, stock levels, pricing and discount rules.
Output
A draft order in the core system and a list of items that could not be matched unambiguously.
Where the human stays
The operator confirms contested items; nothing goes to shipment unapproved.
Integrations
Core system, ERP, e-mail, messengers
Metrics
Order processing time, share of items matched automatically, share of returns caused by wrong goods.
Limitations
Inconsistent item names on the customer side cap automatic matching: the synonym dictionary builds up as the work goes.

See who stopped buying before the quarter ends

  1. 1Compare buying cadence
  2. 2select deviations
  3. 3check correspondence
  4. 4a task for the manager with a due date
Inputs
Order history, the customer's usual buying cadence, correspondence with the manager.
Output
A list of customers deviating from their usual buying rhythm, with the reason where correspondence shows one.
Where the human stays
The manager decides how to work the account: the system supplies the grounds, it does not call on its own.
Integrations
Core system, CRM, e-mail
Metrics
Share of customers won back, time to react to a deviation, repeat orders.
Limitations
For customers who buy irregularly a deviation is indistinguishable from normal: the rule is tuned separately for them or not applied at all.

Where teams usually start

This is an observation across similar companies, not a universal recommendation: the order follows where your bottleneck actually is.
  1. 1Order processing is the usual start: the unit of measure is clear and the effect counts in minutes per order.
  2. 2Item selection and alternatives come next, if the catalogue is wide.
  3. 3Receivables and churn work come after the order history has become complete.
  4. 4What goes first is decided by the arithmetic, not by this sequence: where an operation costs most at your volume.

Industry systems and data

  • core system
  • ERP
  • CRM
  • e-mail and messengers
  • warehouse and logistics
  • electronic document exchange

Risks and constraints

  • The catalogue and stock must be readable in real time, or the draft order will diverge from reality.

  • Customer item names vary: the share matched automatically grows gradually, and cannot be promised in advance.

  • Adoption: operators will accept a draft only if they can see where each item came from.

  • Prices and discounts often live in verbal agreements rather than in the system — they have to be written down.

Which solutions apply

Frequently asked questions

Our customers name items any way they like. Will this work?

Partly at once, fully over time. Unambiguous items are matched from day one, contested ones go to an operator, and every decision they make feeds the dictionary. We estimate the share matched automatically on your historical requests before the work starts rather than promising a number up front.

We handle 50 orders a day. Will it pay off?

The arithmetic is simple: minutes per order times the number of orders times the cost of an operator hour, set against the cost of owning the solution. We do that arithmetic with you during the assessment — and if it does not add up, we say so.

Let's work through one workflow in distribution

Thirty to forty-five minutes on your specific case. If it isn't a fit, we'll say so on the call.