Every week you decide what to promote, replenish, discount, or retire.
The numbers that should drive those calls are scattered. Sell-through sits in one export, margin in another, returns in a third, and the campaign that actually moved the unit is tagged to none of them. By Thursday you have stitched a view together by hand, and the decision was due Monday.
Product performance, inventory, margin, and channel review
Month-to-month implementation, cancel anytime
Commercial, ecommerce, operations, product, or service teams
The work jams in the same three places every week.
The merchandising view arrives after the call
A buyer wants to know which products to push and which to mark down. The answer means pulling SKUs, inventory, margin, returns, and channel numbers from separate places and lining them up by hand. That takes until Thursday, so the promote-or-discount call gets made on last week's picture.
A good segment never becomes a campaign
Marketing has the audience idea. Getting from that idea to a launched campaign means moving the segment through offers, creative, and approvals across four tools, and the performance never lands back where the segment started. The idea was right; the loop was too slow to run twice.
The return spike shows up in the margin report
A stockout, a bad batch of returns, or a service theme is building right now, but nobody sees it until it surfaces in next month's numbers. By then the margin is already gone and the customers who hit it are already annoyed.
So the instinct is to go buy a tool for it. That is usually the wrong first move. The tools mostly exist already. What is missing is the product, customer, inventory, and channel data lined up into one view the team actually opens.
Pick one workflow. Here is what changes in a month.
Weekly merchandising review
Someone rebuilds the same view every week from SKU exports, sales, inventory, margin, returns, and campaign tags, stitched together in a spreadsheet that is stale by the time it is done.
The review is one weekly view your buyers open, sorted by what to do next: which products to promote, replenish, discount, investigate, or retire. The stitching is done for them before the meeting, not during it.
Lifecycle campaigns
A segment idea lives in someone's head, gets built by hand, moves through offers and approvals across a few tools, and the results never make it back to the person who had the idea.
There is one path from segment to launched campaign to result to next move, so the marketer can run the same loop again next week with what they just learned instead of starting over.
Service and returns signals
Tickets, returns, reviews, and chat transcripts pile up in queues, and the pattern inside them only becomes visible once it has already cost margin or a customer.
A live view groups service themes as they form and flags the ones that should trigger a product, operations, or customer follow-up this week, not next month.
One workflow at a time, in four plain steps.
Map the workflow
We sit with the person who owns it and trace where the data starts, where it gets reworked, and which decision waits on it.
Decide who checks what
We agree on the product, customer, and inventory definitions everyone will use, how often they refresh, and who signs off before anything goes out.
Build the view your team opens daily
We ship the dashboard, the segments, the automations, and the AI-assisted steps that put the numbers in front of the team in time to act, not a week after.
Tune it with the people who use it
We run it with your merchandising, marketing, and ops people, fix whatever slows it down, and then move to the next workflow.
Where AI fits
AI does the reading and drafting that used to eat an afternoon. It summarizes what customers said in reviews and tickets, tags SKUs and issues consistently, drafts the first version of a campaign brief or performance note, and flags the stockout or margin drop worth a look. It works on clean, permissioned data, and it never makes the call. Your merchandisers and marketers decide what to promote, discount, or retire; the system just gets them there with the evidence in hand.
Guides for the exact workflows above.
If you would rather see how one of these gets built before you talk to us, each guide walks the workflow end to end, from the mess it starts as to the view it becomes.
How to Build a Weekly Merchandising Review Workflow Around Product, Inventory, and Margin
How to Build Customer Segmentation Workflows Your Team Can Actually Use
How to Build Lifecycle Campaign Operations That Keep Improving
How to Build Inventory and Demand Visibility Before Stockouts Become Fire Drills
How to Build Ecommerce Conversion Reporting That Shows Where Revenue Is Leaking
How to Connect Customer Service Signals to Product and Operations Decisions
The systems this connects to, and how we treat your customer data.
The hard part is rarely the dashboard. It is connecting the systems and files where your product, customer, inventory, and channel decisions actually live, and agreeing who owns each one.
Customer data stays inside its consent and permission rules, and pricing, promotion, and product decisions always run through an accountable person before they go live.
It is one workflow at a time, month to month, starting from $4,000/month, cancel anytime. We ship the first improvement your team uses before we talk about the next one.
Common questions
Which consumer and retail workflow should we fix first?+
Usually the one where the number arrives too late to act on: the weekly merchandising review, a segmentation or lifecycle campaign loop, inventory and demand visibility, ecommerce reporting, or a service workflow that buries the signal. We start where the business value is highest, the data is reachable, and we can ship something usable fast.
Does this work for ecommerce, stores, wholesale, or DTC?+
It works for any of them, because they all run on the same kind of data: products, customers, inventory, channels, and campaigns feeding a decision. Your systems differ, but the way we build is the same. We connect the right data, build the workflow, add AI where it earns its place, and check that your team actually uses it.
Where does AI genuinely help here, and where does it not?+
On the tagging, summarizing, and drafting that used to eat an afternoon. It labels SKUs and support tickets consistently, summarizes what customers said across reviews and returns, and drafts the first version of a campaign brief or the note explaining why margin moved this week. It does not decide what to promote, discount, or drop; your merchandising and marketing teams do, on data with the right permissions.
Tell us the workflow your team keeps rebuilding by hand.
Point us at the place where merchandising, inventory, campaigns, or ecommerce reporting still lags the decision. We will build the first view that keeps up with it.
We reply within 1 business day.
Rather score the workflow yourself first? Run the workflow calculator.