Dmitry Nekrasov

Jetmetrics

JetMetrics is an analytics tool for Shopify brands and agencies.
We help users understand what drives key metrics like LTV, Total Sales, Add to Cart Rate, and Retention – through clear, interactive metric maps.

Our platform shows how metrics are connected, highlights changes, and suggests actions.
Built for Shopify founders, marketers, and e-commerce agencies who want fast insights and fewer dashboards.

More at → jetmetrics.io

Chief Executive Officer

Community Sprints

Expert & Advisor

Datmark

We developing analytical products and solutions based on Microsoft Power BI for ecommerce, SaaS and gamedev
datmark.com

Techobearing

SEO optimization;
Paid ads;
Email marketing;
Developing and implementation of analytical structure (BI, ETL, predictive solutions).

Head Of Marketing

Vivat Trade

Development analytical and sales predictable system in the biggest FMCG regional retail company (90+ stores).

Head of Sales analytics

Manager of Organizational development

I help Shopify stores finally understand what’s happening with their metrics – and what to do next.

At JetMetrics (jetmetrics.io), we build interactive metric maps that show what drives key KPIs like Total Sales, LTV, Add to Cart Rate, Retention, and more.

No more guesswork. No more 20-tab dashboards. Just one map that explains what changed and why — with all the data behind it.

So what we do best:
→ Visualize how your Shopify metrics are connected
→ Help you spot hidden drops or growth points
→ Let you click into any metric to explore trends, breakdowns, and ideas
→ Give agencies a clear way to show impact to clients
→ Support founders and marketers in making smarter, faster decisions

It is built for:
+ Shopify store owners and founders
+ E-commerce marketing teams
+ Agencies working with DTC brands

If you're tired of wrestling with reports and still not sure why your retention dropped or why sales spiked last week – JetMetrics might just save your sanity.

Want to give it a spin? → jetmetrics.io 👈

SaaS product for e-commerce analytics

𝐇𝐨𝐥𝐲 𝐜𝐨𝐰! 555 𝐋𝐨𝐨𝐤𝐞𝐫 𝐝𝐚𝐬𝐡𝐛𝐨𝐚𝐫𝐝𝐬 𝐢𝐧 𝐨𝐧𝐞 𝐩𝐥𝐚𝐜𝐞
[1739 pages | 74% copyable | for 68 sources]

Almost 9 months ago, we posted a set of 389 dashboards (https://lnkd.in/deGKKKJR).

Now it's time to update it. 

With our dear Eugenia Shtanova, we have combined all the great dashboards we've found before in one place.

Categories:
+ Marketing = 370
+ Finance = 13
+ Sales = 57
+ CRM = 21
+ Web = 94

From 57 authors (including Ivan Palii, Siavash Kanani, Christina LeVasseur (Brodzky), Chloe Christine, Mykyta Soima, Dana DiTomaso, Thomas Eccel,  Aleyda Solís, Bojan Basrak, Sheik Shahul M, Louis DUBRUEL, Tyler Rabey, Ludovic Cellier, Thiago Fagundes)

Drop a '555' comment to get this

Enjoy!

Co-founder @ jetmetrics.io | Like Google Maps, but for Shopify metrics

🍯 Free Master Guide: 1100 E-commerce Metrics

We’ve compiled all the key e-commerce and marketing metrics you need to:

– deeply understand your business
– make informed decisions
– and achieve greater results

This free resource is your go-to reference, covering all major areas of your operations.

What’s Inside?

Access a comprehensive list of 1100 metrics from the following categories:
→ SEO
→ CRM
→ Email
→ Orders
→ Loyalty
→ Finance
→ Returns
→ Referral
→ Product
→ Content
→ Support
→ Logistics
→ Influence
→ Inventory
→ Checkout
→ Facebook
→ Activation
→ TikTok Ads
→ Operational
→ Google Ads
→ Amazon Ads

Leave a '1100' comment and I'll send it over

#metrics #ecommerce

Map of 52 CRM metrics in e-commerce

What's it included:

4 areas:
→ Retention
→ Acquisition
→ Customer Base
→ Active Customers

3 types of metrics:

→ Result  (21 metrics)
Quantitative metrics that are calculated based on the result of the period. As a rule, they are influenced by actionable metrics and other result or costs metrics.

→ Diagnostic (21 metrics)
Metrics, which are typically show the ratio of two other metrics. They cannot be impacted directly (not actionable ☝), but they show the state of the metrics that link.

→ Actionable (10 metrics)
Metrics that can be directly impacted by specific actions (this is your starter point!)

And they are all interconnected in a clear system of relationships:
1) Direct impact – solid green arrow
2) Reverse impact – solid red arrow
3) Direct connection without impact – dashed green arrow
4) Reverse connection without impact – dashed red arrow

This map is a very detailed view of CRM metrics in e-commerce.

It can be transformed into:
- more general driver trees
- KPIs for teams and agencies
- more logical dashboards and reports

This is a basic step for turning messy numbers into a framework for thinking.

--

ℹ️ This is a part of our metrics knowledge base 'JetMetrics Lite'
(with 1100 metrics and 1845 growth tactics inside)

#metrics #crm

Your analytics library is growing 📚

Over the past few months, we’ve published a series of deep dives on Substack — exploring where analytics often goes wrong (and how to make it useful again).

Each one covers a real e-commerce problem — from misleading AOV growth to broken retention — and shows how to read metrics in context, not isolation.

Here’s your full reading map:

1) If you want to grow LTV — don’t start with LTV
→ https://lnkd.in/dbW9sBWZ

2) 10 customer segments that hurt your margin — and how to spot them
→ https://lnkd.in/dk_N4Ypg

3) 15 hidden patterns from metrics overlap
→ https://lnkd.in/d_h4MXU7

4) Analytics mistakes you can’t afford
https://lnkd.in/dKdAJUFS

5) Your CR is falling — 4 places to look first
https://lnkd.in/drSAX4Mg

6) Averages are lying to you — here’s what to use instead
https://lnkd.in/dG2bprMx

7) Why your retention breaks even when RPR looks fine
https://lnkd.in/dp5GhmWz

8) 6-step framework to quickly pinpoint why your metric dropped
https://lnkd.in/d7Acnnuw

9) Don’t trust AOV alone — it can rise while business shrinks
https://lnkd.in/dmZuTkMb

10) 10 Metrics You’re Probably Misreading
https://lnkd.in/d_4xjR2W

11) How discounting kills your metrics — and how to stop it
https://lnkd.in/diDrCFxh

12) Why AOV dropped even though my product prices didn’t change
https://lnkd.in/dJUTtn-b

13) Why 90% of customer segments don’t make money
https://lnkd.in/dZGwKUsS

14) How to Identify and Fix Underperforming Products Using Metrics
https://lnkd.in/dN-BwVfS

15) 5 types of metric relationships — and how they trick you
https://lnkd.in/dnrhmUns

16) Revenue is down — but traffic is stable. Where to look next?
https://lnkd.in/dZbWbJVm

All articles are free to read on our Substack:
blog.jetmetrics.io

A single metric is just a point.
Analytics is the connections between them.

Most dashboards stop at the 𝘄𝗵𝗮𝘁.
They show changes (traffic ↑, conversion ↓, AOV =)
but not 𝘄𝗵𝘆 those changes happen.

True analytics starts when you see relationships,
not numbers.

When you stop asking “𝘄𝗵𝗮𝘁 𝗱𝗿𝗼𝗽𝗽𝗲𝗱?”
and start asking “𝘄𝗵𝗮𝘁 𝗶𝗻𝗳𝗹𝘂𝗲𝗻𝗰𝗲𝘀 𝘄𝗵𝗮𝘁?”

Because metrics don’t live alone.
They interact, amplify, or cancel each other out.

That’s where understanding begins.
And where decisions actually make sense.

--

This visual is part of how we think at Jetmetrics – turning dashboards into metric maps that explain, not just describe.

[Article] If you want to grow LTV — don’t start with LTV

In e-commerce, LTV looks like the ultimate goal — big, neat, reassuring. 

But you can’t move it directly. LTV is a result, not a driver.

When teams try to “optimize LTV” as a single number, they end up doing odd things:
- over-discounting,
- forcing activations,
- or hiding margin issues — the dashboard looks better, the business doesn’t.

Our fix is simple: look under LTV, not at it.

Break it into parts you can actually manage — AOV, ARPPC, Lifetime — and work the drivers there.

That’s the point of our guides and cheat sheets: less mystique around the “super metric,” more clear levers you can pull.

Check this article on our Substack 📖

"We have 40+ dashboards"
Which one actually explains, not just describes?

We rebuilt a framework for analytics dashboards around 4 simple questions:

1) How we think
2) How we track
3) Who owns what
4) What we do next

Because dashboards shouldn’t just describe data. 
They should explain systems.

1) How we think
From charts and averages
↳ to metric maps and stories
[!] we visualize what influences what instead of just “what happened”

2) How we track
from fragmented metrics
↳ to a coherent analytical model
[!] every event sits where it belongs in the customer journey.

3) Who owns what
from passive observation
↳ to accountable ownership
[!] margin, returns, and delivery speed stay healthy even when chasing growth.

4) What we do next
from static reporting
↳ to continuous improvement
[!] metrics lead directly to hypotheses, tests, and impact.

---

Old dashboards describe.
New dashboards explain.

📌 Save this if you’re redesigning your analytics process, or send it to the teammate who keeps saying “we just need better visualizations”

#dashboards #analytics

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