You have 12+ months of order history in an ERP or commerce platform
B2C personalization tools break in B2B. Prices depend on contracts. Buyers order on cycles. Accounts have many users with different roles. Elogic Commerce builds AI personalization on your ERP order history, so every account sees the right products, prices, and reorder prompts.
17+ years in ecommerce, since 2009
200+ commerce specialists
NPS 70 post-launch client surveys
5.0 on Clutch 64 verified reviews
Trusted partnerships
Trusted by ecommerce teams
★★★★★ 5.0 · 64 reviews on Clutch
Mid-market & enterprise · EU & US
ISO 9001 and 27001-aligned processes for quality and security management.
What is AI personalization for B2B ecommerce?
AI personalization for B2B ecommerce adapts catalogs, recommendations, and reorder prompts to each account using order history, contract terms, and buyer role, not just clicks. Elogic Commerce builds personalization engines on ERP data, so a plant manager and a purchasing lead at the same customer each see what moves their next order.
Your ERP already holds the strongest personalization signal in commerce: years of real orders per account. Most stores never use it. Elogic Commerce connects that history to the storefront, portal, email, and your sales reps, and turns it into predictions: what this account needs next, when they will need it, and what they buy elsewhere that you also sell. Personalized reorder prompts pair naturally with an AI chatbot that can take the order in the same thread.
In brief
- Elogic Commerce builds B2B personalization on ERP order history, contract terms, and buyer roles
- No per-seat licensing: the engine, models configuration, and dashboards are your IP
- Lift is proven against a holdout group, or reported as the honest absence of lift
What the engine does
Personalization that respects B2B reality: contracts, roles, cycles, and approval flows. Every feature is measured against orders, not clicks.
Predictive reorder prompts
The engine learns each account’s consumption cycle and prompts the reorder before stock runs out. On the portal, by email, or through the sales rep.
Account-based recommendations
Cross-sell and upsell computed from what similar accounts buy, filtered by this account’s catalog, contract, and stock. Relevant, allowed, and in stock.
Next-best-product for sales reps
Reps see ranked suggestions per account with the reason why. Assisted selling gets the same intelligence as the storefront.
Personalized quotes and carts
Suggestions appear where B2B decisions happen: on quotes, carts, and order templates, priced correctly per contract.
At-risk account signals
Ordering slows before churn happens. The engine flags declining accounts early so your team acts before the revenue is gone.
Measurement built in
Every surface runs as an experiment. You see lift in reorder rate, average order value, and revenue per account, not vanity metrics.
Reordering made effortless, selling made smarter
Buyers see their predicted needs before stock runs out and approve in one click. Reps see the next best product per account, with the reason attached. Both run on the same engine.
- • Reorder prompts timed to each account’s real consumption cycle
- • Suggestions filtered by contract, catalog, and live stock
- • Rep view shows the evidence behind every recommendation
B2C personalization tools vs a B2B personalization engine
The tools are not bad. They model a different business. Here is exactly where they break in B2B, and what replaces them.
| B2C personalization tool | Elogic Commerce B2B engine | |
|---|---|---|
| Price source | One list price | Contract price per account, from the ERP |
| Catalog | Everyone sees everything | Account catalogs and permissions respected |
| Buying pattern | Impulse and taste | Consumption cycles and reorder timing |
| Users | One shopper | Many buyers per account, with roles and approvals |
| Where it renders | Storefront widgets | Portal, carts, quotes, email, and sales rep tools |
| Success metric | Click-through rate | Reorder rate, AOV, and revenue per account |
How much revenue sits in your order history?
The 2-3 week data audit sizes the opportunity before you commit to a build.
Built on the data you already own
No new tracking empire required. The core signal is your ERP order history, joined with account data and storefront behavior, processed under strict access rules.
• Respects account catalogs, contract prices, and role permissions everywhere it renders.
• GDPR-aligned: aggregate modeling, role-based access, and data kept in your infrastructure.
• Works with your platform’s native tools where they are enough, custom where they are not.
• One engine can serve B2B and B2C sides of a hybrid B2B2C business with different rules.
Commerce platforms
- Adobe Commerce (Magento)
- Shopify Plus
- BigCommerce
- Salesforce Commerce Cloud
- commercetools
- Shopware
Data sources
- SAP S/4HANA
- NetSuite
- Microsoft Dynamics 365
- Visma
- Odoo
- CRM
- Email platform
Delivery surfaces
- B2B portal
- Storefront
- Sales rep tools
- Quotes & carts
Where B2B personalization pays off
Four programs we build most often. Each starts with your order history and a measurable target.
01
Distributor reorder automation
Consumables and parts reorder on predicted cycles. Buyers approve with one click. Order frequency rises and small leaks to competitors close.
02
Rep-assisted selling
Sales reps open an account and see what to offer next, with evidence. Quote-to-order rates improve because suggestions are grounded in real history.
03
Personalized portal and email
Each account’s portal home and email digest shows their products, their prices, and their likely next needs. Engagement becomes ordering.
04
Hybrid B2B2C personalization
One engine, two rule sets. Consumers get taste-based recommendations. Business accounts get contract-aware, cycle-aware suggestions.
How we deliver
Structured, governed, accountable. The same delivery framework behind every Elogic Commerce build: defined discovery, milestone delivery, RACI accountability, and transparent reporting.
• STEP 1
Data audit
We review your order history depth, product data, and account structure, and confirm the signal is strong enough to predict from.
• STEP 2
Model and rules design
We design the prediction models and the B2B rule layer: catalogs, contracts, roles, and approvals that every suggestion must respect.
• STEP 3
First surface live
We launch one surface first, usually reorder prompts on the portal, behind an A/B test, in 8-10 weeks.
• STEP 4
Expand surfaces
Recommendations roll out to carts, quotes, email, and rep tools, each measured against orders.
• STEP 5
Run and improve
Models retrain on new orders, experiments continue, and a monthly review keeps the program tied to revenue.
Built on proven B2B delivery
Personalization compounds on top of solid portals and ERP sync. This is the delivery record Elogic Commerce builds it on.
5×
Faster order approvals after digitizing B2B workflows on Adobe Commerce
40% fewer manual orders
B2B self-service portal with SAP S/4HANA and PIM integration
3+ years
Engagement period
+31%
Increase in checkout conversion rate
-65%
-65%
+$1.1M
New B2B revenue stream unlocked in year 1
2.5 months to launch
B2B wholesale portal for 1,400+ wholesale users, live and transacting
Engagement at a glance
Every engagement is scoped after discovery, with milestone-based billing and transparent change management. No surprises.
| Engagement | Typical timeline | Investment | Best for |
|---|---|---|---|
| Data and opportunity audit | 2-3 weeks | Scoped after discovery | A verdict on your data readiness and a sized estimate of the personalization opportunity |
| Personalization build | 3-5 months | Scoped after discovery | Engine, B2B rule layer, and the first surfaces live behind A/B tests |
| Managed optimization | SLA-backed retainer | Scoped after discovery | Model retraining, new surfaces, experiments, and monthly revenue reviews |
Turn reorders into your growth engine
A 30-minute call tells you if your data can predict, and what to launch first.
Is this the right fit?
We tell you honestly when we are not the right match, and we recommend an alternative.
Accounts reorder on cycles: consumables, parts, supplies, ingredients
Prices and catalogs differ per account or contract
Sales reps assist orders and could use ranked suggestions
You run a B2B portal, or plan one, and want it to drive orders, not just take them
Better fit elsewhere if
You sell one-off, non-repeating purchases with no reorder pattern.
Your order history is short or inaccessible. Fix data access first, and we can help.
You need simple B2C ‘you may also like’ widgets. Your platform’s native tools may be enough, and we will say so.
Industries we build AI Personalization
Let’s talk
Start with the data audit. In 2-3 weeks you know whether your order history can predict, and how much revenue is on the table. Tell us what you are working on. We come back with an honest assessment of fit, scope, and timeline.
Ready to chat?
Send your requirements. We reply within one working day with a fit assessment and next steps.
AI personalization in B2B ecommerce: frequently asked questions
Because B2B adds rules B2C tools do not model. Prices come from contracts, not lists. Catalogs differ per account. Buyers have roles and approval limits. Purchases follow consumption cycles, not impulses. A B2B engine must respect all of this, or its suggestions are wrong, unpurchasable, or both.
Native tools such as those in Adobe Commerce or Shopify are a good B2C baseline. They do not read your ERP order history, and they do not enforce contract pricing, account catalogs, or approval rules. The Elogic Commerce engine does both, and it also serves reps, quotes, and email, not only the storefront.
Yes. Modeling runs on aggregate patterns, access is role-based, and data stays in your infrastructure. Elogic Commerce holds ISO 27001 and SOC 2 Type II certifications, and the design is GDPR-aligned.
The data audit takes 2-3 weeks. The first surface, usually predictive reorder prompts, is typically live behind an A/B test in 8-10 weeks of the build. The full program across portal, email, and rep tools runs 3-5 months.
Typically 12 or more months of order history at account and SKU level, clean product data, and account structure from your ERP or platform. The two-to-three-week data audit tells you exactly where you stand before you commit to a build.
Every surface launches behind an A/B test. We track reorder rate, average order value, revenue per account, and rep quote-to-order rate. You see the lift against a control group, in orders and revenue, not clicks.
Yes. Hybrid B2B2C is a core Elogic Commerce specialty. One engine runs two rule sets: taste-based recommendations for consumers, contract-aware and cycle-aware suggestions for business accounts.
Related AI solutions from Elogic Commerce
Analytics & Forecasting
Ask your commerce data questions in plain language and get backtested forecasts.
AI Chatbots
ERP-grounded chatbots that answer with live orders, stock, and each account’s contract prices.
AI Search
Hybrid semantic search that finds the right part in large, spec-heavy catalogs.
About Elogic Commerce
Elogic Commerce is an ecommerce development company founded in 2009, headquartered in Tallinn, Estonia, with offices in Prague, Munich, Dresden, Amsterdam, Stockholm, London, New York. With 200+ commerce engineers, architects, and project managers, Elogic Commerce specializes in complex B2B and B2B2C ecommerce, enterprise replatforming, ERP, CRM, and PIM integration, and long-term managed support across Adobe Commerce (Magento), Shopify Plus, BigCommerce, Salesforce Commerce Cloud, and commercetools.
The B2B personalization practice turns this integration depth into revenue: predictive engines built on ERP order history, delivered with contract-aware rules and A/B-tested measurement. Elogic Commerce holds ISO 27001 · SOC 2 Type II · ISO 9001 certifications, an NPS of 70, and a 5.0 rating on Clutch. The company is a certified Adobe Commerce Silver Solution Partner, Shopify Plus Partner, Certified Bigcommerce Partner, Salesforce Select Partner, and Hyvä Bronze Partner, and received the Magento Community Engineering Award at Adobe Imagine 2019.