★ Proof

Shopify Case Studies: The Actual Dashboards

12 accounts, ₹49Cr+ in tracked revenue, shown as unedited Shopify Analytics screenshots. Client names are blurred; not a single figure is touched.

12 case studies
₹49Cr+ tracked revenue
6-month journeys documented

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Each case below shows what the account looked like, what the data was saying, the main problem we were solving, what we focused on, and a month-by-month account of the six-month period.

The screenshots are visible on the card rather than hidden behind a click, and they can be enlarged. Everything identifying the client is blurred, because these are live businesses in competitive categories. Nothing about the numbers has been edited.

★ Straight from Shopify

Real revenue, real dashboards

12 D2C stores we scaled, with the Shopify Analytics screen behind every number — what the data showed, what was broken, and what we did month by month.

₹49Cr+

Revenue tracked

Stores scaled

+366%

Best growth

FULL-FUNNEL GROWTHEstablished D2C — fashion, lifestyle & beauty

CASE 08

₹124.38MTotal sales

↑ 366%

52,547Orders

6.56MSessions

₹2,413AOV

Shopify Analytics · client name blurred, figures untouched

What the data says

This is the broadest growth case in the set. Sales, orders, sessions and AOV all improved strongly. The growth is not dependent on one metric.

The problem to solve

The opportunity was to improve both sides of the equation: bring more people into the store and increase the value of the people who buy. That makes this the best full-funnel case.

What we focused on

Scale Meta acquisition while keeping the landing and product experience strong.
Improve product mix, bundles and upsells to increase basket value.
Use remarketing and retention to get more value from acquired customers.
Test creative, audience, landing page and offer together rather than in isolation.
Track the full journey from session → product view → cart → checkout → purchase.

The 6-month journey — month by month

Month 1
What was happeningThe store already had a strong traffic and sales base.
The workStart with a full-funnel audit and identify the biggest gap between traffic, orders and revenue.
Month 2
What was happeningThe sales curve stayed relatively stable.
The workUse this as the testing phase across creatives, audiences, landing pages, product mix and checkout friction.
Month 3
What was happeningA major step-up appears in the sales curve.
The workScale the combinations that are showing stronger commercial results instead of spreading spend evenly.
Month 4
What was happeningThe higher run-rate holds and AOV starts adding another growth lever.
The workWork on basket value through product mix, bundles or upsells while continuing acquisition growth.
Month 5
What was happeningThe curve accelerates again.
The workAt this point the story changes from testing to scaling a repeatable growth system.
Month 6
What was happeningThe period closes at ₹124.38M sales, 52.5K orders and 6.56M sessions.
The workUse this as the flagship case: traffic grew, orders grew and AOV grew, giving the brand multiple independent growth levers.

META TRAFFIC → ATC SCALEHigh-volume D2C — accessories, beauty, fashion

CASE 02

₹115.62MTotal sales

↑ 20%

127,756Orders

5.08MSessions

₹893AOV

Shopify Analytics · client name blurred, figures untouched

What the data says

Shopify explicitly shows Meta add-to-cart sessions moving from 82 to 52.7K. At the same time, sessions rose 43%, orders 22% and sales 20%. AOV was almost flat, so this is mainly a volume and funnel-efficiency story.

The problem to solve

The main issue to solve was not ticket size. The stronger question was whether paid traffic was creating enough real product intent after the click. The Meta ATC number gives a very clear signal that this part of the funnel changed dramatically.

What we focused on

Improve the match between Meta creative and the page people land on.
Test audiences, products and creatives around real add-to-cart behaviour, not only clicks.
Make the product page answer the key buying questions quickly.
Use retargeting for visitors who showed intent but did not complete the purchase.
Scale only after the landing-to-cart path is stable.

The 6-month journey — month by month

Month 1
What was happeningThe business was already handling a very large traffic base.
The workSet a clear baseline for sessions, add-to-cart behaviour and orders. Review where Meta traffic was stopping after the click.
Month 2
What was happeningSales stayed relatively steady while traffic remained high.
The workTest different creative angles and landing experiences. The goal is to turn more of the existing traffic into product intent.
Month 3
What was happeningThe sales curve held at scale and began moving upward.
The workShift budget toward the audiences and products that showed stronger downstream action. Do not judge success only by CTR.
Month 4
What was happeningThe business maintained a clearly higher sales level than the comparison period.
The workScale the strongest Meta → landing page paths and keep the product-page experience consistent with the ad promise.
Month 5
What was happeningThe gap versus the comparison period stayed strong.
The workWith AOV almost unchanged, focus the story on more people entering the funnel and more people reaching meaningful intent.
Month 6
What was happeningThe period closes at ₹115.62M sales, 127.8K orders and 5.08M sessions.
The workUse the Meta ATC jump as the hero proof point, then connect it to the broader sales and order growth.

HIGH-VOLUME E-COMMERCE SCALEApparel, beauty & everyday-consumer D2C

CASE 04

₹68.47MTotal sales

↑ 17%

41,625Orders

1.87MSessions

₹1,536AOV

32.06%Returning

Shopify Analytics · client name blurred, figures untouched

What the data says

Sales, orders and sessions all increased while AOV stayed almost flat. That makes this a clean volume-led growth case rather than a price-led case.

The problem to solve

The key challenge was maintaining conversion quality while traffic increased. The lower returning-customer rate also means acquisition quality and retention should be discussed separately rather than hidden.

What we focused on

Scale paid acquisition without allowing landing-page quality to drop.
Test product pages and collection pages to keep conversion healthy at higher traffic.
Use creative testing to keep acquisition volume consistent.
Keep the basket value stable while increasing order volume.
Build a stronger remarketing and retention layer as acquisition scales.

The 6-month journey — month by month

Month 1
What was happeningThe store started from a solid base with higher traffic and sales than the comparison period.
The workSet the baseline and identify which acquisition paths were already working. Avoid changing everything at once.
Month 2
What was happeningThe sales curve softened.
The workUse the dip as the optimisation phase: review traffic quality, landing pages, product availability and conversion leaks before adding more spend.
Month 3
What was happeningSales stabilised and prepared for the next rise.
The workKeep the winning paths live and test new creatives/products around them rather than rebuilding the whole funnel.
Month 4
What was happeningA major upward step appears in the sales curve.
The workThis is the main scale moment. Increase spend behind the strongest combinations while protecting the website experience.
Month 5
What was happeningRevenue kept climbing while AOV remained stable.
The workThe story becomes simple: more good traffic + more orders, without needing a big change in price or basket size.
Month 6
What was happeningThe period closes at ₹68.47M sales and 41.6K orders.
The workPosition this as controlled scale — the store grew through volume while keeping AOV broadly steady.

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₹50Cr+ ad spend managed
32+ brands scaled
Unedited figures, blurred clients

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