Opponens
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Know why your store’s numbers moved

Opponens is an investigation engine for your Shopify store. Every morning it reads your data, tests every likely cause of what changed, and shows you the evidence.

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14 days free on every plan. Read-only. Billed through Shopify.

Morning briefing

Tuesday 30 June, ready at 7:00

Conversion4.32%−2.90 pts
Visits150K+100%
Social visits55K+377%
Discount spend£89K+19%

Conversion is 4.3%, against 7.2% on the same days last year. Twice as many people visited, and far fewer of them bought.

Conversion rate, 23 Jun to 29 Jun. This year, latest 4.08%. Same days last year, latest 7.86%.

Conversion rate
DateThis yearSame days last year
23 Jun4.18%5.82%
24 Jun4.10%7.15%
25 Jun4.70%7.24%
26 Jun4.55%6.78%
27 Jun4.15%7.89%
28 Jun4.48%7.61%
29 Jun4.08%7.86%

Ruled out4 checks
  • Traffic volumeMore visits than last year, not fewer
  • CheckoutCompletion about flat, 65% to 62%
  • PaymentsOne bad day on 19 June, then normal
  • PricesDiscount depth flat at about 22%

Dashboards tell you what changed. Someone still has to work out why.

That’s what an investigation engine is for. Opponens reads the same numbers you would, tests every likely cause, and tells you which one it was.

A dashboardOpponens

Conversion fell yesterday.

Conversion fell 40% on 18 June, when your Father’s Day offer ended. Last year it came back. This year the social visitors stayed, and they buy at 2%.

This week is down on last week.

Compared like for like with the same week last year, you’re ahead. Last week had a bank holiday in it.

Here are 40 charts.

Here is the one that explains it, with the figures underneath and the causes it ruled out.

Why did conversion fall?Reading

3 explanations to test.

Inside the investigation engine

Every question runs the same way: read everything, suspect everything, keep only what the data supports.

  1. It reads your store

    Sales, orders, sessions, the conversion funnel, discounts, inventory and product performance, straight from Shopify. Read-only, every time.

  2. It tests every likely cause

    Each possible explanation is checked against the data, broken down by traffic source, device, product and discount code. Most of them don’t survive.

  3. It measures what moved

    The cause that holds up is sized like for like, against the same days last year, so a holiday or a promotion can’t pass for a trend.

  4. It writes it up

    A plain English account of what happened, with the figures and charts behind every finding, in your admin and your inbox before you start the day.

What the engine brings you, every morning

The briefing is the habit. The questions are there when something needs a closer look.

  • The Morning Briefing

    What changed overnight, why, and what deserves your attention, written before you open the admin.

  • Ask in plain English

    Type the question you’d ask an analyst. A full investigation comes back.

  • Like for like, always

    Year on year and period comparisons lined up by day of week and season.

  • Breakdowns that go deep

    By traffic source, device, product, country and discount code, until the cause turns up.

  • Questions on a schedule

    Save the questions you rely on and have them answered weekly or daily.

  • Evidence with every finding

    Each finding carries the figures and the chart it came from.

Every finding comes with its evidence

Not a verdict to take on trust. The claim, the charts it came from, the figures underneath, and the explanations it ruled out.

Sample finding · Harbour & Pine, a real store renamed

Conversion fell when the Father’s Day rush ended, and the crowd it brought in never left.

Conversion fell by about 40% on 18 June, the Father’s Day delivery cutoff, when the FATHERS10 offer ended and the gift buyers left. The same dip happened last year, and conversion climbed back. This year it didn’t, because the visitors changed: social traffic nearly tripled and buys at about 2%, and direct visitors now bounce almost twice as often. Search visitors buy just as they did last year, so the site is fine. Sales are still up 23%.

Both years dip after Father’s Day. Only last year comes back.

Conversion rate, 1 Jun to 19 Jul. This year, latest 4.0%. Same days last year, latest 8.2%.

Conversion rate
DayThis yearSame days last year
1 Jun4.5%2.7%
2 Jun4.7%2.5%
3 Jun3.6%2.7%
4 Jun3.7%3.2%
5 Jun6.1%3.5%
6 Jun5.4%3.2%
7 Jun5.9%3.8%
8 Jun6.0%4.1%
9 Jun5.6%4.3%
10 Jun6.1%6.7%
11 Jun6.1%8.6%
12 Jun6.0%6.7%
13 Jun6.8%5.8%
14 Jun7.1%4.9%
15 Jun7.7%5.5%
16 Jun7.4%5.0%
17 Jun7.0%4.9%
18 Jun5.6%4.7%
19 Jun4.5%4.8%
20 Jun3.7%5.8%
21 Jun4.6%6.4%
22 Jun3.9%6.8%
23 Jun4.2%5.8%
24 Jun4.1%7.2%
25 Jun4.7%7.2%
26 Jun4.5%6.8%
27 Jun4.2%7.9%
28 Jun4.5%7.6%
29 Jun4.1%7.9%
30 Jun4.5%6.3%
1 Jul3.3%4.6%
2 Jul3.8%5.1%
3 Jul4.2%5.4%
4 Jul3.6%5.6%
5 Jul4.0%6.2%
6 Jul4.0%6.2%
7 Jul4.0%5.8%
8 Jul4.3%6.9%
9 Jul4.0%6.7%
10 Jul4.7%7.1%
11 Jul3.6%7.3%
12 Jul4.0%6.5%
13 Jul3.8%6.8%
14 Jul3.8%6.4%
15 Jul4.2%5.9%
16 Jul4.3%6.4%
17 Jul4.0%6.5%
18 Jul4.8%7.1%
19 Jul4.0%8.2%

Last year the crowd went home after Father’s Day. This year it never left.

All visits a day

Visits a day, 1 Jun to 19 Jul. This year, latest 36k. Same days last year, latest 27.1k.

Visits a day
DayThis yearSame days last year
1 Jun23.4k34.7k
2 Jun26.6k30.5k
3 Jun29.3k30.8k
4 Jun31.7k24.5k
5 Jun20.5k30.3k
6 Jun30.5k28.5k
7 Jun25.2k36.1k
8 Jun20k35.1k
9 Jun22.3k28k
10 Jun21.5k21.7k
11 Jun23.6k14.7k
12 Jun23.7k13.5k
13 Jun28.5k12.4k
14 Jun29.9k15.1k
15 Jun23k16.9k
16 Jun23.1k14.1k
17 Jun21.6k14.7k
18 Jun21.7k15.4k
19 Jun21.7k14.5k
20 Jun26.9k13.6k
21 Jun27k15k
22 Jun21.3k15k
23 Jun20.8k10.7k
24 Jun20.5k9.1k
25 Jun20.9k10.4k
26 Jun20k10.4k
27 Jun24.4k10.8k
28 Jun24.4k10.8k
29 Jun19.1k13k
30 Jun18.1k13.8k
1 Jul27.2k20.4k
2 Jul22.6k17.8k
3 Jul22.7k16.3k
4 Jul31.5k16.4k
5 Jul26.3k18.4k
6 Jul22.9k19.6k
7 Jul20.2k13.3k
8 Jul20.6k14.1k
9 Jul23.9k13.1k
10 Jul24k12.3k
11 Jul37.6k11.7k
12 Jul30.3k14.8k
13 Jul21.9k15.6k
14 Jul24.5k12.5k
15 Jul23.3k11.9k
16 Jul30.3k12k
17 Jul29k14k
18 Jul38.5k16.7k
19 Jul36k27.1k

Social visits a day

Social visits a day, 1 Jun to 19 Jul. This year, latest 15.3k. Same days last year, latest 3.1k.

Social visits a day
DayThis yearSame days last year
1 Jun8k4.8k
2 Jun8.3k3.5k
3 Jun7.9k3.8k
4 Jun9.1k3.4k
5 Jun8.3k4.5k
6 Jun8.8k4.7k
7 Jun10.1k4.2k
8 Jun7.8k4.3k
9 Jun9.1k3.6k
10 Jun8.8k2.7k
11 Jun9k1.9k
12 Jun9.8k2k
13 Jun8.7k2k
14 Jun12.5k2.2k
15 Jun9.2k2.1k
16 Jun9.2k4.5k
17 Jun9.2k5.7k
18 Jun9.2k5.4k
19 Jun9k5.6k
20 Jun7.7k3.7k
21 Jun9.6k2k
22 Jun8k2.1k
23 Jun7.4k1.5k
24 Jun8k1.4k
25 Jun7.9k1.5k
26 Jun7.8k1.5k
27 Jun7.7k1.8k
28 Jun9k1.8k
29 Jun7k2k
30 Jun6.6k4.3k
1 Jul7.5k6.1k
2 Jul7.8k5.4k
3 Jul9.2k5.6k
4 Jul9.4k5.3k
5 Jul10k5.8k
6 Jul8.3k7.5k
7 Jul7.8k3.5k
8 Jul7.9k2k
9 Jul8.2k2.3k
10 Jul9.6k2.3k
11 Jul9.5k2.3k
12 Jul11.5k2.7k
13 Jul8.1k2.4k
14 Jul7.7k2.2k
15 Jul8.3k2.1k
16 Jul10.5k2.1k
17 Jul13.5k2.6k
18 Jul12.3k3.4k
19 Jul15.3k3.1k

By source, the four weeks after the cutoff

Visits, conversion and bounce rate by source in the four weeks after the cutoff, last year to this year
Source, last year to thisVisitsBuyBounce
Social87k → 252k2.7% → 1.9%37% → 56%
Direct253k → 296k7.2% → 3.9%35% → 64%
Search55k → 136k9.4% → 8.5%24% → 27%
Email3k → 10k6.2% → 4.6%22% → 41%

The drop is at the cart, not checkout

Share of visits reaching each step, the three days before the cutoff and the five days after
Step15–17 Jun20–24 JunMove
Added to cart15.0%10.0%−33%
Reached checkout11.0%6.8%Follows
Completed checkout65%62%About flat

Ruled out

  • Traffic volume. Visits held near 23,000 a day and rose to 29,000 by mid July. More traffic, not less.
  • Checkout and payment. Completion drifted three points and payment failures spiked for one day. Too small to carry a 33% fall at the cart.
  • A price rise. Discount depth barely moved, 23.2% to 22.0%. Discount spend fell because orders fell.

Read-only by design

An engine you can let into the store without a second thought.

  • It never changes your storeOpponens reads your store’s data to investigate and explain. Every decision stays with you.
  • It reads only what it needsSales, orders, sessions, the funnel, discounts, inventory and products. Each permission is there for a reason you can read.
  • Billing stays in ShopifyYou approve the plan in your admin and Shopify bills you, so Opponens never sees a card number.

Read it where you already work

The same investigations, wherever you are when the question comes up.

  • In your Shopify adminThe briefing and every investigation, inside the admin you already have open.
  • In your inboxThe Morning Briefing arrives by email, ready before you start the day.
  • In Claude and other MCP clientsAsk about your store from the assistant you already use, with the same evidence attached.

One trial, four plans

Every plan starts with 14 days free. Choose the plan you want in Shopify, and you’re billed from day 15.

Compare plans

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What changes

Pulse

A weekly read on the store
$29per month
Try it free

Starter

The briefing every morning
$79per month
Try it free

Growth

For stores asking a lot
$199per month
Try it free

Scale

For teams that live in the numbers
$499per month
Try it free
Morning Briefing
PulseWeekly
StarterDaily
GrowthDaily
ScaleDaily
Questions you ask, each month
Pulse2
Starter4
Growth15
Scale40
Ready-made investigations, each month
Pulse4
Starter8
Growth30
Scale80
Free trial
Pulse14 days
Starter14 days
Growth14 days
Scale14 days
Evidence with every finding
PulseIncluded
StarterIncluded
GrowthIncluded
ScaleIncluded
Read-only access to your store
PulseIncluded
StarterIncluded
GrowthIncluded
ScaleIncluded
Prices in USD per store, billed monthly through Shopify. Cancel any time from your Shopify admin.

Questions merchants ask

Straight answers about your data, billing and what Opponens does.

  • No. It reads your store’s data to investigate and explain. Every decision stays with you.

Read your first briefing today

Install Opponens and your first Morning Briefing runs straight away, on your own store.

  • 14 days free on whichever plan you choose
  • Read-only: it never changes your store
  • Billed through Shopify, cancel from your admin
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