Industries
Olakai for Retail & E-Commerce
Connect every AI tool to a number on the P&L.
Personalization, demand forecasting, fraud detection, customer service — AI is everywhere in retail. The problem is connecting tool spend to GMV, conversion, and margin. Olakai is the layer that makes that connection.
Every AI tool, mapped to the P&L.
Your merchandising team uses AI for demand forecasting. Your marketing team uses AI for personalization and campaign optimization. Your customer service team uses chatbots and returns agents. Your fraud team uses AI scoring. And your engineering team uses Copilot and Cursor to build the platform underneath all of it.
AI touches every line of your P&L. The question is whether you can connect each tool’s cost to the revenue, conversion, or margin it actually moves — and catch the shadow tools nobody approved. That’s what Olakai does.
By the Numbers
Most retailers have piloted AI, but few connect deployments to measurable business outcomes.
The gap between AI experiment and AI advantage is a measurement problem — you can’t scale what you can’t prove across channels and seasons.
Three lenses, one platform
Olakai is one platform with one data model and one set of controls. Assistive IQ, Coding IQ, and Agent IQ are the three lenses you use to look at it — they share data, share context, and share Kai. What you learn in one lens is immediately visible in the others.
Assistive IQ
Track AI usage across merchandising, marketing, and store operations teams. See which tools are driving content velocity and which are just sitting in license counts.
Coding IQ
Measure AI coding tool ROI across the engineers building your storefront, checkout, and recommendations stack.
Agent IQ
Measure every customer-facing and back-of-house agent — chat, returns, fraud, demand forecasting — against GMV, conversion lift, and unit margin.
The KPIs that matter in retail
Every pillar gives you a different lens on AI performance. Here are the metrics that matter most for retail organizations — measured by Olakai, across every vendor, every team.
Assistive IQ
Content velocity
Assets produced per marketer per week with AI assistance
License ROI
Revenue attributed to teams with active AI tool usage
Shadow AI risk
Unauthorized tools in merchandising and customer data workflows
Coding IQ
Storefront velocity
Cycle time delta for front-end and checkout engineering teams
AI adoption rate
% of PRs AI-assisted across the e-commerce platform team
Provider comparison
Which AI coding tool delivers the most value per dollar
Agent IQ
Customer service deflection
% of support tickets resolved without human intervention
Fraud detection rate
False positive reduction from AI fraud agents
Demand forecast accuracy
Improvement in inventory planning from AI agents
Why Measurement Changes Everything
From Inventory Guessing to Forecast Confidence
Measure forecast accuracy, inventory turnover, and carrying cost savings across SKUs and seasons. When you can prove AI forecasting is reducing waste and stockouts, the investment case for scaling becomes obvious.
From Mass Marketing to Measurable Personalization
Track segment-level conversion rates, customer lifetime value, and campaign ROAS. Prove that AI segmentation is driving real revenue lift, not just sending more emails to more people.
From Loyalty Erosion to Revenue Protection
Measure retention rates, reactivation success, and revenue per retained member. When you can quantify the dollar value of every saved loyalty member, churn prevention becomes a provable revenue line.
From Supply Chain Chaos to Measured Efficiency
Track logistics cost per order, on-time delivery rates, and supplier performance. When you can connect AI optimization to margin improvement across your fulfillment network, operations earns its seat at the strategy table.
From Shadow AI Risk to Controlled Adoption
Replace “block everything” with “measure and govern.” See which unsanctioned AI tools access customer data, quantify the PCI and privacy risk, and bring high-value usage into the fold with proper oversight.
From Support Cost to Customer Delight
Measure auto-resolution rates, response times, and CSAT scores across peak and off-peak periods. Prove that AI support handles seasonal surges without sacrificing the customer experience.
Ask your AI program a question. Get a reasoned answer.
Kai is the conversational layer across every Olakai data source. Anyone in the business can ask the questions that matter, and Kai pulls the data, runs the analysis, and shows the reasoning behind every answer.
“Which AI initiatives drove conversion lift last quarter, and what’s the ROI per channel?”
Explore Olakai on your own terms.
Drop your work email below and we’ll send you a private link to a live Olakai environment — pre-loaded with realistic retail data so you can click around at your own pace, run a few Kai queries, and see exactly what your AI program would look like inside the platform.
No account to create. No demo call to book. No commitment. If you want a guided walkthrough after, we’re one click away.