At a glance
Ranked list of the merchant’s top-performing campaigns and programmes by purchase lag, the median time between a Dotdigital send (or click) and the resulting placed-order event. Reveals which sends drive immediate purchase (“flash” cadence) vs which build pipeline that converts later (“nurture” cadence). The card surfaces the campaigns that are most worth replicating and the cadences that are silently building backlog.
| What it counts | For each top campaign / programme send in the 90-day window, the median lag (in hours) between the send/click event and the corresponding Placed Order event. Ranked by purchase volume so noise from low-volume sends is suppressed. |
| Definition of “sent” | Delivered sends (excludes bounces). The lag clock starts at delivery, not at queue or accept. |
| Open rate basis | n/a, this card is purchase-lag focused, not engagement-focused. |
| Bounce handling | Bounces excluded from both numerator and denominator (no purchase can be attributed to a bounced send). |
| Attribution model | Dotdigital’s default 7-day click-attribution window. The card uses the click-to-order timestamp delta where a click exists; falls back to send-to-order for view-through orders. View-through is a 1-day window with smaller weight. |
| Currency | n/a for the lag itself, the underlying revenue is in account base currency. |
| Programme vs campaign | Both included. Programmes (lifecycle automations) typically show 2 to 6 hour median lag for transactional triggers (abandoned cart) and 24 to 72 hours for nurture sequences. One-shot campaigns show a sharp 6 to 24 hour spike with a long tail. |
| Multi-touch attribution | Last-touch, the most recent click before the order gets credit. A customer who clicks two campaigns over 5 days, then orders, attributes the lag to the most recent click. |
| Refunded orders | Included. The card measures lag-to-place-order, not lag-to-keep-revenue. |
| Time window | 90D (90-day rolling window for stable medians) |
| Alert trigger | - (informational card, no native alert; pair with revenue trend cards) |
| Roles | marketing |
Calculation
Calculated automatically from your Dotdigital data. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading.Worked example
A UK DTC homewares brand on BigCommerce + Dotdigital, mature email programme. Window covers 12 Jan 26 to 12 Apr 26 (90 days).| Rank | Campaign / Programme | Type | Recipients | Attributed orders | Median lag | Recovered revenue |
|---|---|---|---|---|---|---|
| 1 | Abandoned-Cart Step 1 | Programme | 18,400 | 988 | 2.4 hours | £37,400 |
| 2 | Mother’s Day promotion (one-shot) | Campaign | 92,000 | 612 | 8.1 hours | £24,800 |
| 3 | Welcome programme Step 2 | Programme | 4,200 | 384 | 22.6 hours | £14,200 |
| 4 | Spring Edit campaign | Campaign | 84,000 | 488 | 14.8 hours | £18,400 |
| 5 | Browse Abandonment programme | Programme | 3,100 | 246 | 6.8 hours | £8,800 |
| 6 | Win-back programme | Programme | 2,200 | 142 | 48.2 hours | £6,200 |
| 7 | Post-purchase upsell Step 3 | Programme | 4,400 | 168 | 72.4 hours | £4,800 |
| 8 | Loyalty tier nudge campaign | Campaign | 12,400 | 184 | 36.4 hours | £7,600 |
- Abandoned-Cart Step 1 has the shortest lag (2.4 hours) and the highest recovered revenue. This is the merchant’s most valuable single send, every minute the programme is paused costs roughly £15 in lost recovery. The median of 2.4 hours means most recoveries happen within the same browsing session.
- Win-back lag is 48.2 hours, much longer than transactional triggers. That’s expected behaviour for a win-back send to dormant contacts; they need time to re-engage. The merchant should not optimise for shorter win-back lag (it would damage open rate); they should optimise for win-back conversion rate over the 7-day window.
- Mother’s Day campaign showed an 8.1-hour median lag, longer than abandoned cart but shorter than nurture programmes. This is a classic tentpole pattern: the email lands, customers browse, decide overnight, and most place orders the next morning. Compare against last year’s Mother’s Day campaign (if available) to see whether lag has shortened (better targeting, faster intent capture) or lengthened (more promotional fatigue, longer consideration).
- Post-purchase upsell Step 3 has 72.4-hour lag but generates £4,800. This is the “slow burn” tier of the programme, customers come back days later, often after using the original product. A merchant who pauses Step 3 to “trim” the programme will see no immediate revenue impact but lose £4,800 / 90 days = ~£1,600 / month over time.
- Browse Abandonment lag (6.8 hours) is faster than the campaign average. Browse abandonment fires earlier in the funnel than cart abandonment, but the customer has demonstrated less commitment. The shorter lag tells you the programme is hitting a high-intent population, every minute it’s paused costs revenue.
Sibling cards merchants should reference together
| Card | Why pair it with Top Sends → Purchase Lag |
|---|---|
| Top Campaigns by Revenue | The revenue-rank view. Pair with this lag-rank view to find campaigns that drive a lot of revenue but late (slow-burn winners) vs little revenue but fast (high-intent niche). |
| Programme Revenue Mix | The programme-vs-campaign split. Programmes typically lead the lag-rank list because they fire on intent triggers; campaigns sit in the middle. |
| Abandoned-Cart Recovery | The single highest-value entry on most merchants’ lag-rank lists. |
| Email-Attributed Revenue | The total. This card is the decomposition; pair to see which sends are pulling weight. |
| Send Cadence | The frequency view. Helps identify whether long-lag campaigns reflect customer behaviour or simply infrequent sending. |
| Welcome Programme Status | The on-off check for the Welcome programme, typically rank 3 to 5 on the lag-rank list. |
| Klaviyo Top Send to Purchase | Klaviyo equivalent. Same definition, comparable bands. |
| BigCommerce Total Revenue | The denominator for share-of-revenue calculations. |
Reconciling against the vendor’s own dashboard
Where to look in Dotdigital: Dotdigital does not expose a “purchase lag” view natively. The closest screens for cross-checking the inputs:- r1-app.dotdigital.com → Insights → Programme Performance for per-programme attributed revenue and conversion-window settings.
- r1-app.dotdigital.com → Campaigns → individual campaign report for per-campaign send-to-conversion timestamps in the activity log.
- r1-app.dotdigital.com → Reports → Custom Reports can be configured to show
Placed Order timestamp - Send timestampper recipient, the manual reconstruction of this card.
| Reason | Direction | Why |
|---|---|---|
| Median vs mean. Dotdigital’s reports default to mean lag where they expose it; this card uses median, which is more robust to outliers. | Vortex IQ lower than mean | Use median for “typical customer behaviour”; use mean for total-time accounting. |
| Click-vs-send anchor. Dotdigital may anchor lag from send timestamp; this card anchors from the most recent click before the order. | Vortex IQ shorter | The click anchor is a better measure of merchant-driven intent. |
| Time-zone. Dotdigital reports run on account locale; Vortex IQ runs on UTC. | ±1 hour at boundary | Averages out across the 90-day window. |
| Conversion window. Dotdigital’s default 7-day attribution window is honoured. A merchant who shortened the window mid-period sees a smaller eligible recovery population for that period. | Slight depending on changes | Re-baseline after window changes. |
| Top-N ranking. Vortex IQ ranks by purchase volume; some Dotdigital exports rank by revenue or recipients. | None on data, only on order | Re-sort the export to match. |
| Card | Expected relationship | What causes legitimate divergence |
|---|---|---|
klaviyo.klv_xc_top_send_to_purchase | Same shape, comparable bands | Klaviyo’s default attribution window is 5-day click + 1-day view; Dotdigital is 7-day click. Dotdigital lags read slightly longer on average. |
bigcommerce.total_revenue | Sum of recovered revenue from this card ≤ BC total revenue | Email-attributed share is typically 5 to 15% on Dotdigital-BC stores, lower than Klaviyo because Dotdigital is closer to Mailchimp in automation depth. |
adobe_commerce.total_revenue | Same shape | Dotdigital-Magento is a more mature integration; expect higher email-share (10 to 20%) and tighter lag distributions. |
Known limitations / merchant FAQs
Why does my abandoned-cart programme show up at the top? Because abandoned cart fires on the highest-intent moment in the customer journey (a known shopper has put items in their basket and left). Median lags of 1 to 4 hours are normal, the customer is often still in the same browsing session when they receive Step 1. If your abandoned-cart programme is not at or near the top, something is broken: pixel mis-firing, programme paused, or a deliverability issue. My one-shot campaigns show longer lags than programmes. Should I move spend toward programmes? Usually no. The lag is a behavioural artefact, not a quality signal. Programmes fire on intent triggers and naturally see short lags; campaigns are blast sends to a broader audience whose intent state varies. The right read is recovered revenue per send, not lag. A 14-hour-lag campaign that drives £24,800 with one send is still more efficient than a programme that drives £4,800 over 4,400 recipients. Can I optimise to shrink the lag on a slow programme? Sometimes yes, sometimes no, depending on the programme intent. Win-back and re-engagement programmes have long lags by design (you’re waking a sleeping audience); shortening the lag would mean sending more aggressively to dormant contacts, which spikes unsubscribes and spam complaints. Welcome and post-purchase programmes have more flexibility; tighter sequencing (Day 1, Day 2, Day 4 instead of Day 1, Day 5, Day 10) often pulls lag down without engagement loss. Why is the median lag on my Mother’s Day campaign so much shorter than my Spring Edit campaign? Tentpole moments compress consideration time. Mother’s Day, Black Friday, Valentine’s, all have a hard date that pulls customers off the fence faster. Spring Edit is a soft-promotional campaign without a deadline; customers browse, save, return days later. The lag pattern is a useful signal that confirms which promotions are actually time-sensitive (consumer perception) vs which are pretending to be. Does the card include orders placed via channels other than the web store? Only orders flowing through the connected commerce platform (BigCommerce, Magento, etc.) and producing aPlaced Order event in Dotdigital. POS orders, Amazon orders, marketplace orders, and manual phone orders that don’t sync back as Dotdigital Placed Order events are not counted. For multi-channel merchants, this card is “web-attributed” lag.
Can a customer’s order be attributed to multiple sends?
No. Last-touch attribution: the most recent click before the order gets full credit. The lag is calculated against that most recent click. This means a customer who clicks Step 1 on Monday, Step 2 on Tuesday, then orders Wednesday morning shows up under Step 2’s lag, not Step 1’s. The aggregate revenue is correct (no double-counting); the per-send breakdown reflects the customer’s most recent interaction.
Why is the lag for my SMS campaigns much shorter than email?
SMS has higher open rates (~95% vs ~25% for email) and higher immediate-action rates because the message is on the customer’s lock screen. SMS lags of 30 minutes to 2 hours are normal; email lags of 6 to 24 hours are normal. If you’re running both channels, the SMS lag will pull the campaign’s median down even when most of the recovered revenue came from email.
What if my top sends are all below the lag-rank threshold (e.g. all programmes show 24+ hour lags)?
That’s a signal worth diagnosing. Either (a) your audience has long consideration cycles (B2B, high-AOV homewares, gifting), or (b) your programmes are firing too late (Step 1 of abandoned cart sent 2 hours after abandon instead of 30 minutes, for example). Check the programme delay settings; modern best practice is Step 1 at 1-4 hours after abandon, Step 2 at 24 hours, Step 3 at 48 to 72 hours.