Demand forecasting
Per-SKU, per-location forecasts with promotions and seasonality accounted for.
- Confidence ranges
- Promotion uplift
- New product estimates
Home / Industries / Retail & E-commerce
Sell more of what moves. Stop buying what does not.
Retail runs on two decisions repeated endlessly: what to buy and what to show whom. Get both slightly better and the margin difference compounds every single week.
ForecastingReorderingPersonalisationSupportPricingTransfersWin-backForecastingReorderingPersonalisationSupportPricingTransfersWin-backForecastingReorderingPersonalisationSupportPricingTransfersWin-backForecastingReorderingPersonalisationSupportPricingTransfersWin-back
/ THE LEAK
Where the money goes.
Same business, two ways of running it. The gap is what automation is worth to you.
Without AI
Margin leaking quietly
- ✕Best sellers stock out on the weekend that mattered
- ✕Cash sits in lines that have not moved since spring
- ✕Every visitor sees the same homepage regardless of history
- ✕Support questions pile up and conversion drops after hours
- ✕Prices were set at launch and have never been revisited
With Hagamart AI
Margin protected
- ✓Reorder points that move with real demand and supplier lead time
- ✓Slow stock flagged early enough for a small markdown to work
- ✓Returning visitors shown what they are actually likely to buy
- ✓Instant, accurate answers on stock, sizing, delivery and returns, always
- ✓Pricing reviewed against demand and competitors rather than left to drift
/ WHAT WE BUILD
Six systems for retail & e-commerce.
Smart reordering & transfers
Recommends transfers between locations before it recommends buying more.
- Dynamic reorder points
- Inter-branch transfers
- Supplier lead-time aware
Personalised merchandising
Recommendations, search and homepage content that respond to behaviour.
- Semantic product search
- Cross-sell and bundles
- Returning-visitor content
24/7 customer support
Stock, delivery, returns and product questions answered from real order data.
- Order status lookups
- Returns handling
- Pre-purchase advice
Pricing & promotion analysis
Which discounts bought volume and which just gave away margin you would have had.
- Elasticity by category
- Discount leakage
- Competitor monitoring
Replenishment & win-back
Consumables reordered at the right moment, lapsed customers contacted before they are gone.
- Predicted reorder timing
- Lapsed detection
- Automated win-back
/ SERVICES
The services behind it.
Every build on this page is assembled from these. Start with one.
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AI Forecasting & Analytics
Demand forecasting, churn prediction and dashboards built …
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AI Operations & Inventory
AI that watches your stock and operations hourly, and warn…
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AI Marketing Automation
Campaigns, content and follow-up that run themselves and c…
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Custom Software Development
Storefronts, portals and internal tools built around how y…
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AI Chatbot Development
Chatbots that sell and support around the clock, trained o…
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AI Sales & Lead Automation
Instant lead response, automatic qualification and follow-…
/ FAQ
Questions we get from retail & e-commerce.
Does this work for a physical shop as well as online?
Yes, and multi-channel is where it works best — one view of stock across shop and web prevents both overselling and the situation where a product is sitting in one place while selling out in another.
Which platforms do you integrate with?
Shopify, WooCommerce, Magento, BigCommerce, Square, Lightspeed and most POS and accounting systems. Where a connector does not exist we build one.
How long before we see a return?
Support automation and cart recovery typically show up within the first month because they act on existing traffic. Forecasting and reordering take a full buying cycle to prove out.
Can it handle thousands of SKUs?
Yes — high SKU counts are where automated forecasting has the clearest advantage, because that is precisely where manual review stops being possible.
Is personalisation going to feel creepy?
Only if it is done badly. We keep recommendations based on obvious, explainable behaviour — what someone browsed and bought — rather than inferences customers would find unsettling.
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