BigCommerce - Integration and Automation

Common Integration Use Cases Between BigCommerce and Loci

1. Personalized product and content recommendations on storefront pages

Data flow: Loci → BigCommerce

Loci analyzes shopper behavior, content engagement, and browsing patterns to generate relevant recommendations that BigCommerce can display on product detail pages, category pages, cart pages, and landing pages. This helps retailers surface complementary products, related guides, and high-converting content at the right moment in the buying journey.

• Improves conversion rates by tailoring on-site experiences to each visitor
• Increases average order value through cross-sell and upsell suggestions
• Reduces manual merchandising effort for ecommerce and content teams

2. Dynamic content blocks for campaigns and promotions

Data flow: Loci → BigCommerce

Marketing teams can use Loci recommendations to populate campaign landing pages, homepage modules, and promotional banners in BigCommerce with content and products most likely to resonate with specific audience segments. This is especially useful for seasonal campaigns, category launches, and audience-specific promotions.

• Supports more relevant campaign experiences without manual page updates
• Helps marketing teams quickly adapt content based on user behavior
• Improves engagement across paid, email, and onsite traffic

3. Content-driven product discovery for high-consideration purchases

Data flow: BigCommerce → Loci

BigCommerce product catalog data, category structure, and product attributes can be sent to Loci so its recommendation engine can better understand the commercial context of the store. Loci can then recommend supporting content such as buying guides, comparison articles, installation instructions, or FAQs that help shoppers move from research to purchase.

• Strengthens product discovery for complex or technical catalogs
• Reduces friction in the buying process by surfacing helpful content
• Supports content and commerce alignment across merchandising and editorial teams

4. Behavior-based personalization using ecommerce events

Data flow: BigCommerce → Loci

BigCommerce customer activity such as product views, cart additions, purchases, and repeat visits can be shared with Loci to refine recommendation logic. Loci can use this behavioral data to identify intent and recommend the most relevant next piece of content or product, such as a setup guide after a purchase or a replenishment article after repeat buying patterns.

• Enables more accurate personalization based on real shopper intent
• Improves post-purchase engagement and repeat visits
• Creates opportunities for lifecycle marketing and retention programs

5. Personalized post-purchase content journeys

Data flow: BigCommerce → Loci → BigCommerce

After a purchase is completed in BigCommerce, order and product data can be passed to Loci to recommend relevant onboarding content, usage tips, accessories, or replenishment information. Those recommendations can then be surfaced back in BigCommerce account pages, order confirmation experiences, or customer service portals.

• Improves customer satisfaction after the sale
• Reduces support demand by proactively delivering helpful content
• Creates additional revenue opportunities through accessories and repeat purchases

6. Segment-specific merchandising for B2B and enterprise buyers

Data flow: Bi-directional

BigCommerce customer and account data can be used by Loci to tailor recommendations for different buyer types, such as wholesale customers, distributors, or enterprise accounts. In return, Loci can recommend content and products that BigCommerce uses to personalize storefront experiences by segment, industry, or account tier.

• Supports account-based commerce experiences
• Improves relevance for different customer groups and buying roles
• Helps sales and ecommerce teams align on targeted digital journeys

7. Analytics-informed optimization of content and commerce performance

Data flow: Loci → BigCommerce and analytics platforms

Loci recommendation performance data, such as click-through rates, content engagement, and conversion influence, can be shared with BigCommerce reporting workflows or connected analytics tools. Teams can use this insight to refine product placement, content strategy, and merchandising rules based on what actually drives engagement and sales.

• Provides visibility into which recommendations influence revenue
• Helps content, ecommerce, and analytics teams make data-backed decisions
• Supports continuous optimization of onsite experiences

8. Automated content enrichment for product pages

Data flow: Loci → BigCommerce

Loci can recommend supporting editorial assets, FAQs, how-to articles, and related media to enrich BigCommerce product pages with content that improves shopper confidence. This is valuable for categories where education and trust are critical, such as electronics, home improvement, beauty, or specialty retail.

• Increases page depth and usefulness without manual content curation
• Helps reduce bounce rates on product detail pages
• Improves collaboration between ecommerce, content, and product teams