Implementations

Your best salesperson spends half the day on quotes. That time can be recovered

In a manufacturing company, a salesperson is often one of the most expensive and hardest-to-replace people on the team. They know the product, they know the customers, they can talk shop with an engineer on the other end as an equal. And they spend half the day putting together quotes, copy-pasting specs out of Excel, and digging up what was agreed with that customer three months ago.

Jarosław Jaśkowiak
Jarosław JaśkowiakJuly 18, 2026 · 3 min read

In short

  • When selling a configurable product, time does not go on customer conversations — it goes on everything around them: assembling quotes from scattered sources, classifying enquiries from five channels and chasing quotes with no reply.
  • Sales support ≠ selling. The first can be handed to a tool; the second stays with the salesperson.
  • The catalogue of options is not a list to implement in full — in the first week you pick one, at most two things that hurt the most in this particular team.
  • The first step is observational, not technical: you have to see the path an enquiry takes from arrival to close before anything gets built.
  • If the sales process is broken at its foundations, a tool will not fix it — it will only show the hole faster. That diagnosis is also worth something.

Where the time really goes in B2B sales

Selling a configurable product looks nothing like selling off a catalogue. Every order is its own quote. The decision cycle is long. The salesperson has to understand the product well enough to talk technically. With that profile, time doesn't leak away in conversations with customers — it leaks away in everything around them.

Putting together a single quote can take several hours. Product specs sit in one file, price history in another, and previous similar quotes are buried in emails or in the head of whoever happens to be on holiday. Inquiries arrive through five channels at once — a web form, email, a B2B platform, the phone, a trade show — and someone has to read them, classify them, and route them to the right person before selling even starts. And somewhere in all of that, some opportunities just fall through, because nobody remembered that a quote from three weeks ago is still waiting for a reply.

None of that is selling. It's sales admin. And that's exactly the part you can hand off to a tool.

What can realistically be built

This isn't about replacing the salesperson. It's about getting them to stop doing things that don't require a salesperson.

A quoting assistant that puts together a first draft from scattered sources — specs, price lists, the history of similar orders — and hands it to the salesperson to check and close. A tool that reads incoming inquiries regardless of channel, works out what they're about, and routes them to the right person. Something that keeps track of conversation status and flags quotes still waiting for a reply before the opportunity goes cold. For companies that export — preparing an export-market version of a quote with units, currencies, and formatting adjusted automatically, instead of translating each one by hand.

This isn't a list you implement in full. It's a catalogue you pick from — in the first week, one thing, maybe two, whichever hurts most in that specific team. The rest waits, or turns out not to be needed at all.

Problem-to-tool map for a B2B sales team: preparing a quote from scattered sources is taken over by a quoting assistant, inquiries from five channels are read and routed by a tool, and chasing unanswered quotes is replaced by status tracking and reminders.
Time in B2B sales leaks into sales admin — and that is exactly what a tool takes over.

Where to start

The first step isn't technical. It's observational.

Before anything gets built, you need to see how the sales team actually works — from the moment an inquiry lands to the moment the deal closes. Where the bottlenecks form, what reps do out of obligation rather than purpose, where knowledge gets stuck. Only that map tells you what's worth building. I go through the sales-team implementation in more detail on a separate page, along with how those four weeks play out.

One caveat I repeat for every team. If the sales process is falling apart at the foundations — no quote tracking at all, nobody knows who's talking to whom — AI won't fix that, it will just show you where the hole is, faster. Sometimes the diagnosis itself is the first result, and that's worth something too.

Frequently asked questions

How do we shorten quote preparation in B2B sales? By pulling together what is scattered today: specifications, price history and comparable past quotes. An assistant assembles the first version and the salesperson checks and closes it. The gain is largest where every quote is currently built from scratch.

Will a tool replace the salesperson? No. The point is that the salesperson stops doing things that do not require a salesperson — assembling quotes from scattered files, sorting enquiries, chasing deadlines. The customer conversation and the commercial decision stay with the person.

What do we do with enquiries arriving through many channels? Route them through a single recognition point: the tool reads the enquiry regardless of channel, works out what it concerns and directs it to the right person. Sorting the inbox is not selling, yet it can consume the first hour of the day.

Where should we start with the sales department? With one process rather than the whole department, and with observation rather than assumptions. A map of how the team works shows where bottlenecks form and what salespeople do out of necessity. Only then is it clear what to build first.

What's next

If your best people are spending more time processing quotes than selling, this is exactly the case where a first implementation makes sense. Start with one process, not the whole department.

See the sales-team implementationBook a 30-minute consultation


Jarosław Jaśkowiak

About the author

Jarosław Jaśkowiak

Over 20 years in B2B and technology. I lead Applied AI implementations in mid-size manufacturing companies — from identifying where AI delivers the fastest return, to a working tool in a single department. I write about what actually happens on the delivery side, without the hype.

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