At a glance
Daily count of distinct customers placing their first order on BigCommerce, plotted as a 90-day area chart. The shape of the line is the leading indicator for “is the top of the funnel working”, a flat or falling trend means acquisition has stalled even if revenue still looks healthy on the back of returning customers.
Calculation
Worked example
A US homewares brand on BigCommerce Pro, looking at the 90-day window 13 Jan 26 to 12 Apr 26.
What’s interesting:
- The April recovery is fragile. A 305 fortnight after a 218 fortnight looks like a turnaround but the long-term shape (412 → 597 → 348 → 290 → 218 → 305) is a 47% peak-to-current contraction. A single influencer collab is not a strategy; the underlying acquisition engine has weakened.
- Channel mix is doing the heavy lifting under the hood. When this trend dips, drill into BC Channel Revenue Mix, most stores see new-customer share concentrated in 1-2 channels (paid search + Meta usually). A drop here typically means one of those channels has decayed (rising CPM, blocked ad account, fatigued creative).
- B2B Edition stores see a step pattern. A new wholesale buyer signs up once and then orders repeatedly for years; the trend looks like a series of plateaus with occasional steps up. This shape is healthy for B2B but would be alarming for D2C.
- Guest-heavy stores have noisier trends. If your store doesn’t require account creation, every guest checkout reads as a “new customer” because we treat
customerId = 0rows as guests. Comparing 90-day shape is still useful but the absolute numbers will differ from your CRM. - The April 12 reading is partial. The latest day in the chart is always the current day with partial data; it will firm up to a higher value as orders trickle in through the rest of the day. Don’t read trend reversals from a single most-recent bar.
- Check Total Revenue over the same window. If revenue is steady but new customers are falling, you’re surviving on returning customers. That works for 1-2 quarters; beyond that the LTV well runs dry.
- Open BC Channel Revenue Mix and compare current 30 days to prior 30 days. Look for a channel whose share has shrunk by more than 5 percentage points; that’s where acquisition decay is concentrated.
- Cross-reference with Google Ads and Google Analytics acquisition cards. A drop here that maps cleanly to a CPM rise on Meta or a quality-score drop on Google Ads is a paid-channel diagnosis.
- Audit organic traffic via BC Organic Recovery Rate. Organic decay is slower but more dangerous; it usually traces back to indexing or content gaps that compound over months.
- Run a quick mix test, the share of new-customer orders coming from POS, social, and B2B portal often tells the whole story before you’ve opened a second card.
Sibling cards merchants should reference together
Reconciling against the vendor’s own dashboard
Where to look in BigCommerce Control Panel: The closest native view is Analytics → Customers (Plus / Pro / Enterprise plans). The “Customers” tab shows new vs returning over time; the over-time chart there is the direct counterpart to this card. Standard plan stores will need to use Customers → View and filter byDate created to approximate the same view manually.
For B2B Edition stores, the B2B → Companies view shows new B2B accounts but not retail customer trends; do not confuse the two.
Why our number may legitimately differ from BC Analytics:
Cross-connector reconciliation:
Same-metric documentation cross-reference (for agencies running multiple platforms):
shopify.customer_trend(planned)adobe_commerce.customer_trend(planned)
Known limitations / merchant FAQs
My new-customer trend is dropping but revenue is steady, should I be worried? Yes, but not panicked. Steady revenue on a falling acquisition trend means returning customers are carrying the store. That works for 1-2 quarters, then LTV runs out and revenue follows acquisition down with a 3-6 month lag. The right action is to investigate the channel mix now (see BC Channel Revenue Mix) rather than wait for revenue to catch up to the warning. My acquisition trend is bumpy, with one good fortnight followed by one bad fortnight, why? Almost always paid-channel cycles. If you run paid social or paid search in 2-week sprints, the trend’s bumps map 1:1 to campaign timing. Smooth out by running rolling 28-day averages, or compare same-month-this-year to same-month-last-year for stores with strong seasonality. Why does my B2B Edition store show a flat trend with no growth? Healthy. B2B customer counts grow slowly because each customer represents a relationship, not a transaction. A B2B trend that grows 5-15% year-over-year is good; one that grows 50% may be over-promising on credit terms. Use BC Top Customers to confirm new B2B customers are converting to repeat orders within 60-90 days. Does this card include POS first-time customers? Yes, every channel including POS. A walk-in customer to a physical store who buys and provides their email at the till counts as a new customer on this trend. If you want web-only the right comparison is BC Analytics → filter by Online Store channel, but check that you actually want to ignore in-store acquisition (most omnichannel brands do not). My most recent day reads as zero, is the integration broken? Almost always sync lag. Today’s bar is partial until end of day. If a full day later still reads zero, check Settings → Sources → BigCommerce status; webhook delivery may be backed up. Webhook lags of more than 30 minutes are unusual and worth a support ticket. Why is my “new customer” count higher here than in BigCommerce Analytics? Two likely reasons. (1) BC Analytics may filter to web-only by default; we include every channel. (2) BC Analytics may count by registration date, not first-order date; a customer who registered last quarter but bought today appears here today, not in BC Analytics’ “new customers this quarter”. My store ran a giveaway and acquisition spiked but didn’t retain, did the giveaway help? Probably not, depending on AOV. Giveaway-acquired customers convert to repeat at 5-15% versus 30-50% for paid-search and organic-acquired customers. The right way to evaluate giveaway ROI is to track the giveaway cohort 60-90 days later via BC Top Customers cohort filter; a giveaway with 8% LTV-effective conversion needs to be very, very cheap to break even. Can I segment this trend by acquisition channel? Not from this card directly. The right pair is BC Channel Revenue Mix for the channel-share view, plusgoogle_analytics.ga_acquisition for the source-medium view. We are working on a per-channel acquisition trend card; track the V2 backlog if relevant.
How does this card treat customers from my B2B portal versus my retail storefront?
They share a single customerId namespace in BC. A B2B customer who also buys retail (rare but happens) counts once on the date of their first BC order across either side. To split, filter by company_id != null (B2B) versus null (retail).