+91 70034 16634 · hello@syscodes.in
Kolkata IST
eCommerce · 8 weeks
CocoaTown sell bean-to-bar and nut-butter machinery to craft chocolate makers in more than a hundred countries. The catalogue held everything a buyer needed and no order that a buyer could use.
30-min call with a senior lead · Reply within 1 business day · NDA on request
Sales
Organic traffic
As reported by the client.
CocoaTown make bean-to-bar and nut-butter machinery (melangers, grinders, roasters and winnowers) for craft chocolate makers and larger producers. The catalogue is deep and technically accurate, written by people who know the process. That depth is the reason serious buyers arrive in the first place. Nobody needed to make the writing simpler.
What the catalogue did not have was an order.
A chocolate maker does not search for a model name. They search for the stage they are stuck at and the batch size they need to reach. Listing every machine on one page and adding a search box would have made the catalogue faster to scan, not easier to decide from.
The gap showed up in the inbox. Buyers wrote to ask which machine fitted their batch. A sale that needs an email before it can start waits on a time zone. This is a considered purchase with a long research period. Every unanswered question adds days to it.
Navigation was rebuilt around two questions a buyer can answer: how much cocoa goes into a batch, and which stage is the problem. Product names answer neither. Every machine now sits under the stage it serves and carries the batch range it is built for. The menu is written in the words a maker already uses.
This purchase takes weeks and usually involves a spreadsheet. So the specifications had to sit on the page as text, not inside a downloadable PDF and not as a photograph of a table. Capacity, motor rating, drum size and footprint can then be copied, compared against a rival machine, and sent on to whoever has to approve it.
These machines ship worldwide, and a melanger wired for one country is scrap in another. A cheaper build puts voltage in a note at the bottom of the description and lets a sales email sort it out afterwards. The electrical standard was made a choice on the product instead, so the wrong machine cannot be ordered.
The catalogue leads with process stage rather than product family. A maker who cannot get their conche to the right texture arrives at the stage first and meets only the machines that serve it. Batch range sits on every card, so a producer working in small runs can rule out an industrial machine before opening it.
On the product page the specification table is the main event, not an afterthought below a gallery. It is plain text a buyer can select and paste into their own comparison. On a phone the table stays a table rather than collapsing into a list, because a buyer comparing two machines needs the rows to line up.
A maker knows which stage is failing before they know which machine fixes it, so the navigation starts where the problem is.
Capacity is the first filter a producer applies, so it appears in the listing rather than several clicks deep.
A specification locked inside a PDF cannot be pasted into a comparison, and comparison is the whole of a considered purchase.
If a choice decides whether the machine works at all in a country, it belongs on the page rather than in a follow-up email.
Capacity had been recorded in litres in some places and kilograms in others. Nothing could be filtered until that was fixed, and no script could fix it, because the conversion depends on what is being ground. The engineers settled one figure per machine by hand before the new navigation could be built at all.
Machine attributes live in metafields, so stage, batch range, motor rating and electrical standard are structured data rather than paragraphs. Meilisearch reads those fields, which is why a search for a capacity returns machines and not blog posts. The electrical standard is a product option, so the order carries the right specification into the warehouse.
The technical writing is why buyers arrive, and years of process notes already ranked. A restructure that broke those addresses would have traded one problem for a worse one. Every page kept its URL through a 301 map, and each one now links to the machine it describes. A maker reading about conching is one tap from the equipment that does it.
05Key solutions
The parts of the build a visitor would point at.
Capacity is the first thing a maker knows, so the catalogue narrows by how much cocoa goes into a batch.
Machines are grouped by the part of the process they serve, so a buyer starts from the problem rather than a model name.
The electrical standard is selected before checkout, which stops a machine reaching a country it cannot safely or legally run in.
Capacity, motor rating, drum size and footprint sit on the page ready to copy into a comparison sheet or an approval request.
Meilisearch queries structured machine fields, so a search for a capacity or a stage returns equipment rather than articles.
Years of process writing kept its addresses and now links straight to the equipment it describes, so reading turns into a shortlist.
06The result
What changed after launch.
Sales
Sales are up 28%. On a considered purchase with a long research period, that gain does not come from persuading anyone faster. It comes from letting a buyer confirm on their own, without waiting on a reply, that a machine matches their batch size and their electrical standard.
Organic traffic
Organic traffic is up 39%. The pages that already ranked kept their addresses through the restructure, and they now sit beside the machines they describe. A search about conching lands somewhere it can be acted on. The catalogue reads as one structure rather than as a list that grew.
The two figures work together rather than separately.
More of the right people arrive through the technical writing, and more of them can finish the decision without help once they do. Traffic without a way to decide is a cost. That is the part the restructure changed.
Tell us the number that is stuck. A senior lead replies within one business day with an honest view, free.
or WhatsApp +91 70034 16634
9.9/10 client score · 150+ projects · 100% on time
07The finished site
Live, and running the business it was built for.
Visit the live site (opens in a new tab)
08In their words
Buyers used to email us to ask which machine fits their batch. Most of them stopped, and the ones who still write ask better questions.
09Tech stack
What it is built on, and what it talks to.
10More case studies
Other projects where we named the number before we started.
eCommerce
A smart batting tee and a finished coaching app, sold from a stock theme. Rebuilt in neon and scanlines, without making the phone pay for it.
eCommerce
Vision and swing trainers that make no sense in a photograph. Moved out of a coaching site and onto a storefront built around the demonstration.
eCommerce
An established Amazon seller with no channel of its own. Catalogue ported across, two markets configured, and a storefront designed to convert rather than list.
11Start a project
Send the metric that is stuck and we will tell you honestly whether we agree.
You'll hear back from a senior lead, never a bot.
