The raw count of unique opens over time. This is volume, not percentage, so it moves with both how many you sent and how engaging the send was.
At a glance
The total number of unique opens per period bucket, plotted over the selected window. This is a count, not a ratio: it answers “how many opens did the program generate” rather than “what fraction of delivered emails were opened”. That distinction matters, because opened volume rises when you send more even if engagement quality falls. Read it alongside the rate trend: rising volume on a flat rate is healthy growth from more sending; rising volume on a falling rate means you are buying opens with raw send pressure. Like all open metrics, the count is inflated by Apple Mail Privacy auto-opens, so treat absolute levels as directional.
| What it counts | The sum of opens_unique per period bucket, plotted as an area chart over the selected window. |
| API endpoint + statistics field | POST /api/campaign-values-reports and GET /api/metric-aggregates for the Opened Email metric, returning the opens_unique statistic. |
| Email vs SMS aggregation | Email only. SMS has no open event, so it is excluded. |
| MPP impact | Heavy. Apple MPP auto-opens add machine opens to opens_unique, so the count overstates real human opens. The trend remains useful because the MPP contribution is roughly proportional to volume. |
| Chart type | Area. |
| Time window | 30D vsP |
| Alert trigger | A sustained drop in opened volume against the recent baseline, especially when send volume held steady. |
| Roles | owner, marketing |
Calculation
Calculated automatically from your Klaviyo data. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading.Worked example
An illustrative pet-supplies brand on Klaviyo, sending a steady weekly campaign cadence. Reading the dashboard on 14 Apr 26 for the trailing 30 days (14 Mar 26 to 12 Apr 26), the opened-volume area chart by week looks like this (illustrative figures):| Week | Delivered | Unique opens | Open rate |
|---|---|---|---|
| 14-20 Mar 26 | 52,000 | 23,400 | 45.0% |
| 21-27 Mar 26 | 53,500 | 24,075 | 45.0% |
| 28 Mar-3 Apr 26 | 78,000 | 31,200 | 40.0% |
| 4-12 Apr 26 | 54,000 | 24,300 | 45.0% |
- Opened volume is a count, so week 3’s spike to 31,200 is mostly explained by sending 46% more email, not by better content. The opened area chart rose, but that is send pressure, not engagement quality. This is exactly why volume must be read next to the rate.
- The rate fell while the volume rose. Open Rate Trend dipped to 40% in the same week. The combination “more opens, lower rate” is the signature of reaching deeper into less-engaged segments: you got more total opens, but a smaller share of each send opened.
- Whether week 3 was worth it depends on downstream metrics, not opens. If the extra send drove proportional clicks and orders, the volume push paid off. If Clicked Trend and orders did not rise with opens, you spent list goodwill for little return and raised fatigue risk.
- The MPP caveat applies to the count too. A meaningful slice of these 24,000-plus weekly opens are Apple Mail pre-fetches, not humans. The opened-volume line is therefore best read for direction and proportionality, not as a literal human headcount.
- A falling opened volume on steady send volume is the alarming pattern. That would mean fewer of the same number of emails are being opened, which usually points to inbox placement or list decay rather than a content miss. None of the weeks above show that, the dips here are all explained by send volume.
Sibling cards merchants should reference together
Opened Trend is a volume metric. It only means something next to a rate and a send count:| Card | Why pair it with Opened Trend |
|---|---|
| Open Rate Trend | The percentage view of the same metric. Volume rising on a flat rate is healthy growth; volume rising on a falling rate is send pressure. |
| Email Open Rate | The single-period rate headline. Combine with this count to judge whether more opens came from more sending or better engagement. |
| Engagement Funnel | Places opened volume in the full delivered, opened, clicked, converted cascade so you can see whether opens translated downstream. |
| Total Sends | The denominator behind volume. A jump in opened volume next to a jump in sends is expected; a jump with no extra sends is the interesting case. |
| Click-to-Open Rate | The MPP-resistant quality check. High opened volume with low CTOR means many of those opens were shallow or machine-driven. |
Reconciling against Klaviyo
Where to look in Klaviyo:- Klaviyo → Analytics → Metrics, then the Opened Email metric, for the unique-opens count over time.
- Klaviyo → Campaigns, then a specific campaign’s analytics, to attribute a volume spike or dip to a particular send.
- Klaviyo → Analytics → Performance, for the blended program view across campaigns and flows.
| Reason | Direction of divergence |
|---|---|
| Time zone. Vortex IQ buckets opens by UTC day; Klaviyo uses your account time zone. Opens near midnight can land in a different bucket. | Either direction, usually marginal. |
Unique vs total opens. This card uses unique opens (opens_unique). If you compare against a Klaviyo view showing total opens, ours reads lower. | Ours reads lower against a total-opens view. |
| Page caps. Campaign-values reporting pages at 50 records per pull, so very high-volume accounts can see slight aggregation truncation. | Reported volume runs marginally low for very large senders. |
| MPP filtering. If a Klaviyo view has its MPP filter on and ours counts machine opens, the counts diverge. | Klaviyo’s filtered view reads lower. |
| Campaign vs flow scope. A campaign-only Klaviyo view will not match our blended campaign-plus-flow count. | Ours reads higher than a campaign-only view. |