I spent 8 years building analytics for e-commerce brands. Now I'm building my own.
For the last eight years, I've been building analytics systems for e-commerce companies. Dashboards, reports, data pipelines — the whole stack. I've worked with brands doing a few thousand a month and brands doing millions.
And the same thing kept coming up: store owners don't look at their dashboards.
They set them up, they pay for the tool, and then they check it once a week (maybe). Not because they don't care about their numbers — they absolutely do. But because most analytics tools are built for analysts, not for the person actually running the store. You open Shopify's analytics, see 47 different charts, and close the tab because you have orders to pack and ads to manage.
So I started building briefpeak.
The idea is simple: connect your store, and every morning you get an email that tells you what happened yesterday. Revenue, orders, returns, how your products are performing — written in plain English, not buried in charts. If something looks off (returns spiking, a product suddenly selling out, revenue dropping), you get a smart alert. No login, no dashboard, no chart-deciphering.
Where things stand right now:
Backend is built — Shopify OAuth, data sync, BigQuery pipeline, all working and validated against live store data
9 free calculator tools are live at briefpeak.com/tools (profit margin, break-even, LTV, ROAS, CAC, discount impact, conversion rate, store health scorecard, and a sample smart brief)
Waitlist is open for early access to the actual email briefs - invite you to join!
Revenue: $0. This is pre-launch. I haven't charged anyone for anything yet.
Solo founder, bootstrapped, based in Europe. No funding, no plans to raise.
What's next: I'm building the brief engine now — the part that actually takes raw store data and turns it into a readable morning email. After that, it's the alert system, then opening up to the first batch of waitlist users.
I'm starting with Shopify and will add WooCommerce, Stripe, and other platforms after that.
I'm curious — for those of you running online stores (or building tools for store owners): what's the one number you actually check every day? Not the one you think you should check — the one you actually pull up first thing in the morning. I want to make sure the briefs lead with whatever that is.
Happy to answer any questions about the build, the stack, or the approach.
This is fantastic. Having run a few ecommerce stores, including Shopify among others, this is exactly what is missing.
To answer your question directly: the first number I check is revenue from the last 24 hours. Not weekly, not monthly. Everyday. Everything else , I think, is context for that one number.
I think the morning brief concept is smart because it meets store owners where they actually are. Nobody is opening a dashboard before coffee. It's why I built KPILIO and I think An email that tells you what happened while you were sleeping and flags anything worth worrying about is how this should have always worked.
The returns spiking use case is the one that will resonate most with store owners. That one hurts quietly and usually shows up late. If your brief catches that early it will save people real money for sure.
Following this closely. Good luck with the brief engine. I Love it.
~Robert
Robert, appreciate you sharing the specifics — "revenue from the last 24 hours, every day" is exactly the kind of signal I'm designing around. That daily heartbeat check before anything else really validates the brief format.
And yeah, the returns use case is one I keep coming back to. By the time most people notice it in a dashboard, the damage is already done. Early flagging there feels like the highest-impact win.
Interesting that you built KPILIO from a similar frustration. Would love to hear what you learned along the way. Following your work too.
In my day job. I always felt like I'm chasing the problem. In fact I'm chasing one right now haha. The biggest frustration, I think is having to dig out what happend, coming through loads of data just to find out it's a smart bot acting huma or campaigns got run youdidn't know where coming. I feel like that's the kind of blindsidedness I want to avoid. This is why I think yur product is needed too. When I wake up, tell me whats gong on with my business while I slept. PERFECT PERFECT PERFECT.
Robert, appreciate the energy here haha! That chasing the problem feeling is exactly what I kept running into too — spending the first hour of the day just figuring out what happened before you can even think about why.
Hope you catch whatever you're chasing right now :D Best of luck to you!
Thank you and likewiase. I hope we meet at some developers conference some day.
Hi Dave!
8 years of e-commerce analytics experience and now own tool—this journey has been very inspiring!
When users start using Briefpeak, questions like "How do I connect my store?" and "How do I analyze sales data?" will be repeated a lot.
I'm building SupportBridge for exactly this problem—AI drafts safe replies from approved FAQs (max 1 reply, the team always approves).
If you'd like, I'll do a free audit of your last 100 emails and share the exact timeline + ROI.
Thoughts?
the "built for analysts not operators" framing is sharp. seeing the same thing in beauty products - people buy inventory trackers and expiry apps but dont open them because theyre designed like spreadsheets not like tools for someone whos actually using the products. the email-first approach sidesteps that entirely. curious if youve thought about how much context is too much in the daily brief before it starts feeling like another dashboard in disguise
Really appreciate that parallel with beauty product tools — the "designed like spreadsheets" problem is exactly it. People don't lack data, they lack something that meets them where they already are.
Your question about context overload is something I'm actively wrestling with. Right now my rule of thumb is: if it requires the reader to cross-reference something else to act on it, I've failed. One insight, one recommended action, minimal supporting context. But honestly I'm still calibrating.
What made you start thinking about this in the beauty space?
building an app that tracks beauty product expiry dates and inventory. same problem you described - most tools in this space feel like data entry chores rather than something that actually fits into how people use their products. trying to keep the focus on surfacing whats expiring soon and getting out of the way rather than making people manage a database
This resonates a lot.
I’m building a D2C fashion brand, and honestly, I’ve felt the same thing, dashboards look impressive, but they rarely change what I do day-to-day.
The only numbers I actually care about are things like what’s selling today, what’s slowing down, and whether something needs immediate action.
Curious - when you tested this, what ended up being the one metric/store owners actually reacted to the most?
hey Rishav, would love to get your eyes on an early version when it's ready — is there a good way to reach you?
Honestly, the metric that got the most visceral reaction was sell-through velocity changes. Not just "this is selling well" but "this was selling well and just stopped." That shift from positive to negative momentum triggered immediate action almost every time. People would go check inventory, adjust ads, swap homepage placement — all within minutes of reading the brief.
Would love to hear how that maps to your fashion brand if you ever want to compare notes.
Eight years watching people not use dashboards is the exact right foundation for building something they will. The failure mode you described — set it up, pay for it, close the tab — happens because dashboards answer questions people aren't asking. A morning email that surfaces what changed and why meets people where they already are. To answer your question: from what I've seen talking to small store owners, the first number is usually revenue vs yesterday or revenue vs same day last week. The "vs yesterday" framing is more emotionally meaningful than any trailing average. Does the brief show that kind of comparison by default, or is it more absolute numbers?
Really appreciate the framing on "questions people aren't asking" — that's exactly the trap I watched teams fall into for years. Build the perfect dashboard, nobody opens it.
To your question: yeah, day-over-day comparison is the default view in the brief. Revenue vs yesterday, revenue vs same day last week. Both. You're right that the "vs yesterday" framing hits differently — it maps to how store owners actually think about their business. Trailing averages feel academic by comparison.
Curious what other numbers come up in your conversations with small store owners beyond revenue?
The insight: store owners don't ignore analytics because they're lazy. They ignore them because dashboards are built for analysts, not for people who pack orders. You're not building a better dashboard. You're building a signal that arrives when they're already in email. That's not a feature; that's respecting where their attention actually is.
Really interesting take.
From what I’ve seen, it’s not just that people don’t check dashboards — even when they do, it’s hard to connect numbers to what’s actually hurting revenue on the site. Curious how you plan to bridge that gap.
That's exactly the gap I kept running into on the agency side. People would stare at a conversion rate drop and have no idea where to even start digging. The brief format is my attempt at solving that — each one ties a specific metric shift to a likely cause and a concrete next step, rather than just flagging that something changed.
Still iterating on how much context to include without making them overwhelming. Would love to hear what kinds of signals you've found hardest to make actionable.
From what I’ve seen, the hardest part is going from “conversion dropped” to understanding what actually changed on the site — especially when it’s something small but impactful.
Your approach of tying metrics to likely causes makes a lot of sense.
Curious how you arrived at that — was it mostly from patterns you kept seeing with clients, or did anything specific push you in that direction?
Mostly patterns from clients. The same 5-6 root causes kept showing up: someone changed a price without telling anyone, a discount code broke, a top-selling product went out of stock, shipping times crept up, a campaign started driving traffic to the wrong landing page, etc.. Once you've seen those enough times, you can map most metric shifts to a short list of likely causes and check them automatically. At least I hope you can haha!
The "small but impactful" ones are the hardest — like a single SKU going out of stock that was driving 20% of conversion. That's the stuff dashboards will never surface.
Yeah, that makes a lot of sense — those are exactly the kind of issues that are obvious in hindsight but easy to miss in the moment.
The SKU example is a good one, I’ve seen similar cases where one small change quietly impacts a big part of revenue.
Interesting that these patterns repeat so consistently — feels like most of the value is in surfacing them quickly rather than analyzing more data.
Serving ecommerce brands to building your own gives you a massive unfair advantage. You've seen what metrics actually matter across thousands of stores. Are you building on a specific platform or going custom?