Build Recommendations
Show each shopper products they actually want to see.
Why teams choose 247 Labs
We have delivered secure products for retail, ecommerce, and other customer-facing operating environments for more than a decade.
Clients stay with 247 Labs because we combine practical product thinking with strong engineering and reliable delivery.
Our team has shipped platforms, data products, and custom software across demanding technical and operational settings.
Our Clients
The platforms and partners we build with.
We integrate across the tools and technologies trusted by enterprise teams, grouped by where they fit in the stack.
Healthcare
Government
Technology
Finance
Services
Recommendation services for more relevant product exposure and measurable lift.
We scope each engagement around one customer signal model, one delivery path, and one measurable business outcome so the system can support real growth decisions.
Recommendation readiness assessment
Review data quality, current merchandising logic, and product signals before model work begins.
Recommendation engines
Build product recommendation logic for product pages, cart, lifecycle, and merchandising placements.
Personalized merchandising
Tailor product exposure and ranking to individual behavior and purchase history.
Recommendation placements
Deploy recommendation slots across the journey where they are most likely to convert.
Lift testing and tuning
Measure recommendation impact against a baseline and tune strategies for conversion and AOV.
AI platform integration
Connect recommendation systems to ecommerce, marketing, and data tools already in use.
Challenge Map
Fix the relevance gaps that make recommendations feel generic.
Recommendations fail when signals are weak, the same products show for everyone, or placements never reach the parts of the journey where they would convert.
Recommendations still show broad popularity instead of what each shopper wants.
We build recommendation and merchandising logic that uses behavior, purchase history, and product interaction data to make product exposure more relevant across the journey.
Strong fit for higher-SKU stores.Recommendation slots only appear in one place and miss most of the buying path.
We design recommendation placements across product pages, cart, search, and lifecycle touchpoints so relevant products reach shoppers where they are most likely to act.
Best for high-traffic stores.Nobody can tell whether recommendations are actually driving more sales.
We add lift measurement and testing so teams can compare recommendation strategies against a baseline and see real impact on conversion and average order value.
Useful for data-driven teams.Case Studies
Retail proof for conversion and engagement.
Serenity Kids: store optimization that improved conversion
30% higher conversion and 25% lower bounce rate
247 Labs optimized Serenity Kids' Shopify store with faster performance, better navigation, product recommendations, and a smoother checkout, proving strong impact on core ecommerce metrics.
Read case study →
Holstee: commerce platform scaled around strong demand
10,000 monthly orders and 150,000 users
247 Labs designed and launched Holstee's ecommerce brand experience and supported its growth, demonstrating strong delivery across product experience and digital commerce scale.
Read case study →
Raw Elements: richer search and multi-brand product experience
Sales grew substantially after the new launch
247 Labs built a custom ecommerce platform for health products with memberships, tokens, categories, and full search, showing strong execution in product discovery and commerce structure.
Read case study →Capabilities
The strategy, build, and insight layers recommendation teams need.
We help teams choose the right use case, build the system correctly, and keep measurement and relevance in view from the start.
Pick the right recommendation use case
We align product signal quality, placement fit, and success metrics before recommendation work starts.
- Use case prioritization by value
- Data readiness review
- Merchandising workflow mapping
- KPI and rollout definition
Build usable recommendations
We develop models, APIs, dashboards, and integrations that fit your current ecommerce environment.
- Recommendation pipelines
- Ranking and placement logic
- Analytics dashboard delivery
- Marketing and store integration
Make recommendation signals useful
We design insight layers that help teams act on relevance, conversion, and value trends sooner.
- Recommendation performance views
- Placement response insight
- AOV and conversion tracking
- Testing and lift analysis
Protect customer data and trust
We design recommendation delivery around consent, governance, auditability, and controlled data use.
- Consent-aware data use
- Role-based access rules
- Audit and version history
- Data retention controls
Tech Stack
Recommendations should connect to the ecommerce stack you already run.
We build around your systems so customer signals can move into real merchandising work instead of staying fragmented.
247 Labs delivered a web platform that not only looked exceptional but performed exactly the way our data models required. They took the time to understand the analytical demands behind the front end and built something that genuinely supports how we work. It was one of the smoothest development engagements I have been part of.
Malak Ahmad, Data Analyst, Deloitte
Business Benefits
Recommendations work when product exposure becomes more relevant.
The value comes from better targeting, stronger placements, and exposure shaped by real behavior.
Better recommendation relevance
Show products that reflect actual customer interest instead of one broad list for everyone.
Higher average order value
Surface complementary and relevant products that encourage larger, more confident baskets.
More converting placements
Put recommendations across the journey where shoppers are most likely to act on them.
Smarter merchandising moves
Support ranking and assortment decisions with stronger customer response data.
Better use of behavior data
Turn ecommerce signals into governed inputs that support practical commercial decisions.
Ready to build recommendations that improve relevance and conversion?
Talk with 247 Labs about your customer signals, placement gaps, and rollout plan so recommendations can support measurable ecommerce growth.
Start Your Recommendations ProjectFAQ
Common questions before a recommendations initiative moves forward.
That depends on the approach. Some recommendation logic can start with modest order and behavior history, while richer models improve as more signal quality and depth become available.
Yes. We commonly integrate recommendation logic into existing ecommerce and marketing systems so teams can improve relevance without rebuilding the whole stack.
We establish a baseline first, then track lift in conversion, average order value, engagement, and click-through against a control or prior state.
We design around consent-aware tracking, controlled data use, role-based access, and retention rules so recommendations stay easier to govern over time.
Let’s build something
great together.
We’re happy to answer any questions you may have and help you determine which of our services best fits your needs.
Call us at 1-877-247-7421 or email hello@247labs.com
Your Benefits:
- Client Oriented
- Independent
- Competent
- Result-driven
- Problem-solving
- Transparent
What happens next?​
1
We schedule a call at your convenience
2
We do a discovery and consulting meetingÂ
3
We prepare a proposalÂ
Office Locations:
Schedule A Free Consultation
