Shopify Magic
Shopify's built-in AI for content, store tasks and its Sidekick assistant.
- Native to the platform many stores already run
- Content and task help with zero setup
- A giant's AI roadmap included in the plan
All guides Industries
A store that sells while you sleep. Properly.
An online store generates the same questions, the same content needs and the same decisions daily, at every hour. AI answers the order questions, writes the catalog, personalises the marketing and watches the stock. This guide covers where it pays, the established platforms, and when a custom build earns its keep.
- WISMOanswered without tickets
- Catalogwritten at import speed
- Campaignspersonalised, not blasted
- Stockbought before it runs out
What AI does in an online store
The compounding wins sit in four places. Service: order status, returns and product questions resolved instantly, which is most tickets. Content: product descriptions and variants produced at catalog scale, in every language you sell in. Marketing: segments, flows and campaigns tuned per customer. Operations: demand forecast into buying, pricing watched, fraud flagged. Each is measurable against revenue.
01
The customer asks; the store answers
Where is my order, does it fit, how do returns work: resolved on the spot, in chat, mail or WhatsApp.
02
Products get words that sell
Descriptions, attributes and SEO text drafted from your product data, per language, per channel.
03
Marketing meets the person
Flows and campaigns keyed to behaviour: the abandoner, the regular, the lapsed, each addressed differently.
04
Operations look ahead
Demand signals become buying suggestions; anomalies in orders and payments get flagged early.
When this solution makes sense
A good fit if
- Support drowns in order-status and returns questions
- Hundreds of products lack proper descriptions, translations or both
- Marketing is one newsletter to everyone
- Bestsellers run out while slow stock ties up cash
- You sell in two languages but serve properly in one
Probably not yet if
- Traffic and orders are tiny; fix acquisition first
- Product data is so thin there is nothing to write or answer from
- Nobody will review AI content before it goes live
- You expect AI to fix a product or price problem
What changes
Support volume that scales without headcount
The repetitive majority of tickets resolves itself; people handle the exceptions.
A catalog that is finally complete
Every product described, translated and searchable, including the long tail nobody had time for.
Marketing that converts by knowing
Behaviour-keyed flows outperform the blast, visibly, in the numbers.
Cash and stock in better places
Buying follows the forecast instead of the fear, in both directions.
What teams use it for
- Order status and returns automation
- Product description generation
- Catalog translation at scale
- Abandoned cart and winback flows
- Demand forecasting into buying
- Review and question responses
The established platforms
These platforms lead the space. They are real, established businesses, and most stores will run several of them.
Klaviyo
The ecommerce marketing platform, with AI across segments, flows and content.
- The reference for email and SMS in ecommerce
- AI segmentation and campaign assistance
- Deep store-data integration
Gorgias
The ecommerce helpdesk with AI resolving support inside store context.
- Built around orders, returns and store data
- AI agent resolves the repetitive majority
- Standard in the Shopify ecosystem
Nosto
Personalisation and search platform tuning what each shopper sees.
- Recommendations and search that learn
- Merchandising rules with AI inside
- Long-established in commerce personalisation
Triple Whale
Analytics and attribution for ecommerce, with AI reading the numbers for you.
- The store's numbers in one place
- AI summaries and anomaly alerts
- Popular across DTC brands
Off the shelf or custom?
When a platform is enough
Most stores should buy: the platform-native AI plus the category leaders above cover service, content and marketing well, and integrate in days. Configure properly, ground the content in your product data, and measure.
When custom wins
Custom wins at the seams: catalog pipelines from supplier data no app understands, bilingual content with native Spanish quality, service agents that reach into your ERP or logistics beyond the store platform, forecasting for your particular demand shape, or when app fees at your volume exceed owning the piece.
Where Sabemos fits
Custom build
We build the pieces your store cannot buy: content pipelines from your product data in Spanish and English, service AI wired past the platform into your real systems, and forecasting tuned to how your demand behaves.
Setup and onboarding
Assembling the stack? We choose against your platform and volume, integrate the tools, ground the content and flows in your data, and hand over a store that runs on rails you understand.
Frequently asked questions
Where should a store start?
Support automation if tickets hurt, catalog content if products are underdescribed, marketing flows if everything goes to everyone. Pick the leak that costs most; each pays back alone.
Will AI product descriptions hurt SEO?
Thin, generic ones will, human or AI. Descriptions grounded in real attributes, written in your voice and reviewed, perform; that is a process question the store controls.
Can it handle Spanish and English properly?
Yes, with locale rules: Spain Spanish is not default output. A bilingual catalog pipeline with native review is standard work for us.
What about the fees at scale?
Per-ticket and per-contact pricing is fine until volume makes it a tax. When a line item outgrows the cost of owning that capability, that is the custom trigger.