Web Store
BigCommerce
Connect your AI to BigCommerce
Ecommerce managers, merchandisers, and customer support teams run the store through BigCommerce, but orders, products, customers, and coupons live on separate screens that take time to export and reconcile. AI can answer those questions in seconds, but only if it stays read-only, so it cannot change store data, and shares customer details and order contents only with people entitled to see them.
Why it matters
Capabilities that matter most for BigCommerce
01
Read live store data from any AI client
Ask about orders, products, variants, customers, coupons, categories, and gift certificates and get answers from the store as it is now, not from last week's export.
02
Tools and prompts ready in the app store
17 read tools and 15 read-only prompts for jobs like order reviews and catalog pricing audits are ready to add to your account in a click.
03
Read-only by design
The tools only read. Nothing in the store can be changed through them, and customer details and order contents are shared only with people who are allowed to see them.
03
One question across BigCommerce and your other systems
Cross-system prompts line up BigCommerce with the CRM, ERP, accounting, and email platforms you already run, so a question that spans both has one answer.
Use cases
Example AI Use Cases for BigCommerce
scenario
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Spot-checking prices by eye across a long catalog means a negative margin, a zero price or a sale price above the regular price can sit unnoticed among thousands of rows. Variants can carry their own prices too, so a product that looks fine can still hide a bad variant.
What popdock provides
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Optionally name a brand or a minimum price, and it reads the BigCommerce products and applies fixed pricing rules: zero or empty price, sale price above price, cost above the selling price, retail price below price, and margin under 10 percent. For flagged products it also checks up to 20 products for variants with the same problem. Results are sorted by severity and show the figures behind each flag. It only reads and recommends, never edits a price, and says so plainly when nothing is found or when results may be truncated.
Business outcome
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Pricing problems surface in severity order with the figures behind each flag, so negative margins are caught by a check rather than by eye.
scenario
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Newsletter sign-ups on the store and the people in Drip drift apart, and nobody compares them. Someone who signed up at checkout may never reach Drip, or may have unsubscribed there, so they are never emailed or are emailed against their wishes.
What popdock provides
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It reads BigCommerce newsletter subscribers added in the last 90 days, or the period you choose, up to a limit you set, and looks each email up in Drip. You get three lists: in BigCommerce but not in Drip, in both but not active in Drip, such as unsubscribed, and in both and active, with counts and the email, name, source and date added for the first two. Emails are compared ignoring case and spaces, it never copies anyone between systems, and it stops when there are no subscribers.
Business outcome
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Operations sees which store sign-ups are missing from Drip or unsubscribed there, so gaps can be fixed on purpose, not discovered by accident.
scenario
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Newsletter sign-ups on the store and subscription status in HubSpot drift apart because nobody checks them against each other. A shopper may sign up at checkout and never become a HubSpot contact, or may have opted out in HubSpot already.
What popdock provides
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It reads BigCommerce newsletter subscribers added in the last 30 days, or the period you choose, and looks each email up in HubSpot. When a contact exists, it reads that contact's subscription names and statuses. You get subscribers with no HubSpot contact, subscribers whose HubSpot status is not subscribed with the subscription name, and a count of those fully consistent. Emails are matched ignoring case, it never suggests re-subscribing someone who opted out in HubSpot, and nothing is changed.
Business outcome
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Marketing sees which store sign-ups are missing or opted out in HubSpot, with opt-outs respected and never flagged for re-subscription.
scenario
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The revenue Mailchimp credits to a campaign rarely agrees with what the store recorded. Checking it means listing the attributed customers, then searching BigCommerce for each one's orders, refunds and unpaid amounts, and nobody does that order by order.
What popdock provides
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Give a campaign id, and optionally a start date, and it reads the campaign's revenue and the orders Mailchimp attributes to it. It then checks up to 25 of those customers in BigCommerce by billing email, summing order totals and refunds and noting unpaid orders. You get both sets of figures and the difference, customers who disagree by more than 1 percent, and customers Mailchimp credits with no store order. It says when a match was by billing email only, refuses to compare differing currencies, and says if only the first 25 were checked.
Business outcome
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Finance sees how far Mailchimp's campaign revenue is from store orders and which customers explain the gap, with the 25 customer limit stated.
scenario
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Before an account call, a rep checks the CRM for the organization, its people and deals, and then searches the store separately to learn what the account actually buys. People who buy but are not in the CRM, and contacts who never buy, are easy to miss.
What popdock provides
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Give an organization name, and optionally a lookback period, and it finds the organization in Pipedrive, refusing to continue if the name matches more than one. It reads the organization's people and deals, finds each person in BigCommerce by email and also searches store customers by company name. It then pulls their orders for the period. You get the owner, open and won deals, store spend and order count, spend per person, store buyers who are not CRM people and CRM people who never bought. It only reads and nothing is changed.
Business outcome
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Reps walk into an account call knowing whether CRM follow-up matches real buying, including buyers the CRM does not know about.
scenario
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Gift certificate liability is checked by exporting the store's balances and comparing them with a balance sheet line by hand. The two drift apart unnoticed, and expired certificates that still carry a balance are rarely spotted.
What popdock provides
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Give an as-of date, which defaults to today, and it sums the balances of active BigCommerce gift certificates, lists the five largest and notes any past their expiry date. It then searches the Rillet balance sheet for a matching line, trying gift, then deferred, then unearned, and shows which line it used. You get the store balance, the ledger liability and the difference. If no ledger line is found it says so and stops instead of assuming zero, certificates in different currencies are reported separately, and nothing is changed.
Business outcome
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Finance sees whether the store's outstanding gift certificate balance agrees with the ledger liability, without a zero assumed when no line exists.
scenario
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Big web orders arrive and nobody in sales knows whether the buyer is already in the pipeline. Finding out means pulling the order list, then searching Salesforce for each buyer's contact and open opportunities one at a time.
What popdock provides
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Give a minimum order total and optionally a lookback period, which defaults to 14 days, and it finds the BigCommerce orders at or above that amount. It looks up each buyer's email in Salesforce for a contact and, when one exists, any open opportunity. You get a table per order with total, currency, payment status and the Salesforce result, then the orders with no contact as follow-ups. Orders with no billing email are listed as unmatchable, totals are never compared across currencies, and nothing is changed in either system.
Business outcome
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Sales gets a follow-up list of large orders from buyers not yet in Salesforce, and sees which buyers already have an open deal.
scenario
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Store managers export order lists and pivot them by hand to see counts, revenue and refunds by status. The totals drift by the time the sheet is shared, and the largest orders and refunded ones are easy to overlook in a long export.
What popdock provides
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Ask for the last 7 days, or another period, optionally limited to one order status, and it reads the BigCommerce orders. It reports a headline of orders, revenue and refunds, a table by order status, a table by payment status, the discount total and the five largest orders. Orders with a refund are noted. It reads orders only and does not guess at causes. If nothing is found it says so, and if the record limit is hit it warns the figures may be incomplete and names the filter that would narrow them.
Business outcome
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Store managers get current order counts, revenue and refunds by status without an export, with truncation stated instead of hidden.
scenario
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An agent handling a case copies the customer's email into the store admin to find the order the customer is talking about. The case is in one system, the orders are in another, and picking the wrong order wastes time on the call.
What popdock provides
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Give a Salesforce case number, and optionally a lookback period, and it reads the case subject, status and priority and the contact's email. It finds that person as a BigCommerce customer and lists their orders with date, status, payment status, total and refunded amount. It reads the items on the order that looks related to the subject and says which order seems relevant and why, or that none obviously is. It stops when the case has no contact or the match is ambiguous, and nothing is changed in either system.
Business outcome
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Support sees the customer's recent orders next to the case and the most likely related order, without leaving the case to search the store.
scenario
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To answer whether a customer has paid, support and collections staff open the store for the orders, then the ledger for the invoices and payments, then a spreadsheet to line them up. Orders with no obvious invoice, or overdue invoices, are easy to miss.
What popdock provides
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Give a customer email, and optionally a lookback period, and it finds the BigCommerce customer and their orders, then the Rillet customer with payment terms, invoices, payments and credit memos. You get a customer header, tables of orders and invoices, total ordered against total invoiced against amount due, overdue invoices, and orders with no obvious invoice. Both systems' statuses are shown, and it never calls an order unpaid on the invoice side alone. It stops on an ambiguous email, shows the store side only if there is no Rillet record, and nothing is changed.
Business outcome
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Support and collections answer whether a customer has paid from one view of orders, invoices and amounts due, with both statuses shown.
scenario
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Someone chases an order from the storefront into the ERP by searching two admin screens. They cannot easily tell whether it was imported, invoiced or paid, or whether the lines and totals made the trip intact.
What popdock provides
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Give a BigCommerce order id, and optionally a Business Central company, and it reads the order and its lines, then finds the Business Central sales document that holds the order id as its external document number. It compares line count, quantities and amounts, then looks for the posted invoice and its remaining amount. You get a short timeline from order to document to posted invoice, plus a list of discrepancies. Totals from both sides are shown before any gap is called an error, since tax or shipping can explain it. It only reads and nothing is changed.
Business outcome
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Finance sees how far an order has progressed into Business Central and where it differs, without calling a tax or shipping gap an error.
scenario
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Finding where a web order landed in the ERP, and whether the totals and lines agree, is a manual hunt across two systems. The order may have been keyed with a different reference, or with a changed quantity or price on one line.
What popdock provides
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Give a BigCommerce order id, and optionally a Dynamics GP company, and it reads the order and its lines. It then finds the Dynamics GP sales document whose customer PO number holds the order id, using the closest amount if several match. It compares total and tax, then matches lines by SKU and item number, listing lines only on one side and lines whose quantity or price differs. It ends with a verdict of in step, differs or not in Dynamics GP, stops when a record is missing, and says the order may have been keyed with a different reference. Nothing is changed.
Business outcome
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Finance sees whether a web order reached Dynamics GP and agrees with it, line by line, with a clear verdict.
scenario
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Buyers see what sells in BigCommerce but see stock and open purchase orders in Dynamics GP, so spotting the best sellers that are about to run out means adding up order lines by hand and looking each SKU up in a second system. Refunded lines get counted by mistake, and a SKU runs dry before anyone raises a reorder.
What popdock provides
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Name a GP company and, if you like, how many days to look back and how many top SKUs to check. It reads recent BigCommerce orders, adds up units sold per SKU without the refunded lines, then looks up on hand and on order stock and open purchase orders for each top SKU in that company only. You get days of cover and next promised date per SKU, with low cover and no order due flagged. SKUs that are not in PowerGP Online are listed separately, the number of orders read is capped and stated, and nothing is changed in either system.
Business outcome
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Buyers see which best sellers will run out before supply arrives, in one read-only report, without cross-checking two systems.
scenario
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Web prices are set in BigCommerce while costs sit in Dynamics GP, so margins are worked out in a spreadsheet after exporting both. Products with thin or negative margins go live, and a web price that drifted from the GP price list is only noticed by accident.
What popdock provides
--
Give a GP company, a minimum margin percent and, optionally, a brand. It reads the BigCommerce products, looks up the current cost and price list for each SKU in that company and calculates margin on the price the customer pays. You get a table of products under the threshold and a second table where the web price differs from the GP list price by more than 5 percent. Products with no GP item or a zero cost are skipped and counted, rows in another currency are flagged rather than compared, and nothing is changed in either system.
Business outcome
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Thin margin products and web prices that drifted from the GP price list are found before customers buy them.
scenario
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BigCommerce shows one stock level and Dynamics GP shows another, and comparing them SKU by SKU means opening two screens. The store oversells when its level is above what GP holds, and stock sits unlisted when GP holds more than the store shows.
What popdock provides
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Name a GP company and, optionally, a SKU and a GP site. It reads BigCommerce inventory levels, including variant SKUs, then reads quantity on hand and on order from PowerGP Online for each SKU, summing sites when none is named. You get a table sorted by the largest difference, with oversell risk and stock not listed online flagged. Store only SKUs are listed and continued past, products where the store does not track inventory are noted, a run without a SKU covers the first 50 products and says so, and nothing is changed.
Business outcome
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Oversell risk and unlisted stock show up in one sorted comparison instead of a manual check across two systems.
scenario
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When a customer calls, their orders are in BigCommerce and their balance and overdue invoices are in Dynamics GP, so support opens both and pieces the account together. With no shared id, the wrong customer is easy to pick, and a high overdue balance goes unnoticed while the customer keeps ordering.
What popdock provides
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Give a customer name or email and a GP company. It finds the BigCommerce customer, reads their recent orders with totals and refunds, then finds the PowerGP Online customer by name and reads balance due and open items with days past due. You get identity in both systems, order history, GP standing and one line on any concern. If several customers match on either side it lists them and stops, the GP match is stated as a match by name and not a confirmed identity, and nothing is changed.
Business outcome
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Support sees orders and account standing together, with the identity caveat stated, and answers the customer in one pass.
scenario
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The web catalog and the Dynamics GP item master drift apart, and comparing them means exporting both into spreadsheets and matching SKUs by eye. Products go live with no GP item, items never reach the store, and web prices fall below GP cost without anyone noticing.
What popdock provides
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Name a GP company and, optionally, how many records to read per side. It reads BigCommerce products and PowerGP Online items, matches SKU to item number ignoring case and spaces, and retries a missing SKU once before calling it missing. You get three lists: store products with no GP item, GP items with no store product, and matches where cost differs or the web price is below GP cost, with counts. If no SKU matches it says the systems appear to use different identifiers and stops, capped reads are labelled as samples, and nothing is changed.
Business outcome
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Missing items and below cost web prices surface in one reconciliation report instead of spreadsheet matching.
scenario
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To confirm a web order reached Dynamics GP, finance searches sales documents by customer and date and hopes the PO field holds the order number. Totals and statuses are compared by eye, and nobody is sure whether the order was invoiced or paid.
What popdock provides
--
Give a BigCommerce order number and a GP company. It reads the order status, payment status, total and lines, then searches PowerGP Online sales documents from a week before the order for one whose customer PO equals the order number. For a match it compares amount and status and checks receivables for an invoice and whether it is paid. If the order number is not recorded in GP it says so and offers close candidates labelled unconfirmed, never as a match. It stops if the order is not found, and nothing is changed.
Business outcome
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Finance sees whether a web order was entered, invoiced and paid in GP, with any difference in total stated.
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