Fishwife's Secret Ingredient

Two weeks ago, Pierre Jamet, Head of Sales at Fishwife, published a LinkedIn post nobody at Sous asked for. It opens: "Fishwife's secret ingredient? It's called Sous." Fishwife has been beta testing Sous since February, and what Pierre describes is self-serve syndicated data analysis in the most literal sense: a whole sales team pulling its own numbers and walking into category reviews with decks it built itself, in a few clicks. The specialist with years in the data is no longer the only person who can do the work. The rest is Fishwife's story, in their words.

The post that started this

Fishwife is the beloved tinned-fish brand: female-founded, launched in 2020 to bring conservas culture to North America, with tins designed like art prints. The brand grew fast, and fast growth in grocery means more retailer conversations and more data drops for the sales team carrying them.

Pierre runs that team. In February, Fishwife started beta testing Sous, and a couple of weeks ago he posted about it, unprompted: "We've been beta testing Sous since February — and I am FIRED UP about what our team can do now."

Then he listed the work itself: "Complex analysis? A few clicks. Performance recaps? A few clicks. Category review prep? A few clicks."

Each of those jobs lands in Sous as a workbook, one living document holding the question, the math, the charts, and the written story together. Fishwife's team does not export data into one tool and build charts in another. They ask, and the workbook comes back.

The old way: you needed years in the data

There is a reason "years of experience" was the requirement. Syndicated data is rule-bound. Some measures sum cleanly across retailers and periods; others, like distribution and velocity, break the moment someone totals the column. Panel data carries its own rules again. Learning where the traps sit takes years, which is why most brands ended up leaning on one experienced person, with everyone else waiting in that person's queue.

Pierre names the shift directly: "You no longer need years of experience wrangling syndicated & panel data (SPINS, NielsenIQ, Circana, Numerator) to pull world-class insights."

The four providers he lists are his shorthand for a whole category of specialist work his team used to route through one desk.

What changed: the whole team self-serves the syndicated data

Self-serve syndicated data analysis means anyone on a brand team can ask a question in plain language and get back a verified, provider-correct answer, complete with charts and a written narrative. Sous does this by keeping a rulebook for each provider it supports, so the math behind every answer follows the conventions of SPINS, Circana, and Nielsen rather than a generic spreadsheet formula. Performance recaps and category review prep stop depending on one specialist's calendar.

Pierre's version is shorter: "The best part: it levels up our WHOLE team." And the line after it is my favorite in the post: "Everyone's geeking out on the numbers now."

The detail worth noticing is who is doing the geeking. Salespeople. The people who sit across from buyers are arguing from numbers they pulled themselves that morning, checked against the same data the buyer will check them against.

Category review prep, on brand, and checked against the data

Pierre's post includes a screenshot that is the whole workflow in one image: a Sous workbook titled "Category Review Key Takeaways," with bar charts ranking Fishwife against King Oscar, StarKist, Wild Planet, Safe Catch, and Chicken of the Sea. A real category review artifact, for a real competitive set, built by the team that has to present it.

His verdict on the output: "Slides in our brand look, every number checked against the data? Chef's kiss."

That one line names the two things that decide whether a buyer meeting goes well, and behind it sit shipped pieces of Sous working together:

• The deck comes from the finished workbook. Sous Slides writes the story arc and renders every slide, so nobody spends the evening pasting charts into PowerPoint.
• The look is Fishwife's, automatically. Brand Styles captured the brand's identity once (logo, exact colors, fonts, layouts), and every export from anyone on the team now ships in it.
• Every number is checked before it reaches a slide. A deck cannot show a figure the verified analysis did not produce.
• Each figure stays traceable to the query in the workbook that produced it, which matters the moment a buyer asks where a number came from. Our trust and accuracy chapter explains why we hold that line everywhere.

Its category review decks now come out in that same look, without anyone on the team doing the formatting.

What it looks like inside a real brand

Six months into the beta, the pattern at Fishwife is the one we build for. The specialist is still there, busier with better questions, and the rest of the team no longer waits in the queue.

The work also keeps itself current. The workbooks behind those recaps and reviews sit on live data, so when the next period's file lands, they rebuild on their own: new numbers and a rewritten narrative, still in Fishwife's look. Category review prep is no longer a project the team restarts every period; it is something they open.

Getting started

If any of this sounds like your Monday, Pierre already wrote the call to action: "If you live in syndicated data and slide decks, go check out Sous."

Sign in at platform.asksous.ai and ask the question your team is waiting on right now: the complex analysis, the performance recap, the category review prep that Fishwife handles in a few clicks. For the bigger picture on where agents take this kind of work, start with the complete guide to agents in CPG.

The bottleneck was never the data. It was who could work it. At Fishwife, it moved.