---
title: Recommendation module settings by industry
description: "Mail recommendation module weights (see Module adjustment and tuning) don't have one universal \"correct\" setting. The right starting point depends heavily on your business type: how often customers repurchase, how considered the purchase is, and how big your catalog is. This article gives you six starting-point profiles by industry, so you have a validated baseline to configure your e-mail modules from, and then A/B test against your own data."
---
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# Recommendation module settings by industry
### What is this article about?
Mail recommendation module weights (see [*Module adjustment and tuning*](https://content.raptorservices.com/help-center/module-adjustment-and-tuning?hsLang=en)) don't have one universal "correct" setting. The right starting point depends heavily on your business type: how often customers repurchase, how considered the purchase is, and how big your catalog is. This article gives you six starting-point profiles by industry, so you have a validated baseline to configure your e-mail modules from, and then A/B test against your own data.
#### Prerequisites
- An e-mail recommendation module already set up and returning results. See *Introduction to Mail Recommendation Strategies*.
- Familiarity with what each weight does. See [*Module adjustment and tuning*](https://content.raptorservices.com/help-center/module-adjustment-and-tuning?hsLang=en).
### The six archetypes at a glance
| Parameter | Durable fashion | Beauty / consumables | Food / grocery | High-tech | Travel | Marketplace |
| --- | --- | --- | --- | --- | --- | --- |
| History size | 50 | 50 | 50 | 30-50 | 10-20 | 40-50 |
| Cross-sell weight | +10 | +8 | +10 | +12 | +6 | +8 |
| Look-alike weight | +7 | +5 | +3 | +4 | +12 | +8 |
| Buy history weight | -8 | +8 | +12 | -6 | -6 | -4 to 0 |
| Basket weight | -10 | -10 | -10 | -8 | -5 to 0 | -10 |
| Visit / search weight | +3 | +2 | 0-2 | +6 | +6 | +4 |
| Popularity / fallback | Low | Medium | Low | Medium | High | Low + shuffle |
| Trending period | 30 days | 14-30 days | 7-14 days | - | 7-14 days + 360 days | 7-14 days |
🔍 **Note**: one pattern holds across every archetype: basket weight stays negative everywhere, so items already in the basket are never re-suggested. Buy history weight is the only parameter that flips sign depending on the business, negative for durable purchases and travel, positive for consumables and groceries that get rebought regularly.
### 1. Durable fashion / ready-to-wear
| Parameter | Value | Why |
| --- | --- | --- |
| History size | 50 | Clothing taste is stable, so the underlying preference matters more than the last isolated session. |
| Cross-sell weight | +10 | Completing the outfit (top to bottom, accessory) lifts the basket value, the main lever for average order value. |
| Look-alike weight | +7 | Suggesting similar items in the same style keeps discovery going without drifting from the subscriber's taste. |
| Buy history weight | -8 | Customers don't re-buy the same garment, so it needs active suppression, though not excluded entirely. |
| Basket weight | -10 | Never re-suggest what's already in the basket. |
| Visit history weight | +3 | A recent visit signals useful intent, but weaker than a purchase. |
| Popularity / fallback | Low | Individual signals are rich, so there's little need to lean on a popularity fallback. |
| Trending period | 30 days | A low-volatility audience, so a long window avoids noise. |
### 2. Beauty / cosmetics / consumables
*(fragrance, skincare, hygiene)*
| Parameter | Value | Why |
| --- | --- | --- |
| History size | 50 | Very regular habits; a long history captures the repurchase ritual. |
| Cross-sell weight | +8 | An associated routine (cleanser, cream, serum) has strong complementarity. |
| Look-alike weight | +5 | Useful to prompt trying a variant, but secondary to replenishment. |
| Buy history weight | +8 | Key inversion versus fashion: the product gets rebought, so re-promote it at the right moment. |
| Basket weight | -10 | Always negative, even for consumables. |
| Visit history weight | +2 | A supporting signal alongside the regularity of purchases. |
| Popularity / fallback | Medium | A good base for newcomers, but individual data takes priority once available. |
| Trending period | 14-30 days | Matches the pace of launches and beauty trends. |
### 3. Grocery / food / FMCG
*(recurring shopping)*
| Parameter | Value | Why |
| --- | --- | --- |
| History size | 50 | The "typical basket" shows up in the long history, that's where the value is. |
| Cross-sell weight | +10 | Recipe or occasion pairing (pasta, sauce, parmesan) is very strong complementarity. |
| Look-alike weight | +3 | Limited use, the goal is replenishment, not alternatives. |
| Buy history weight | +12 | The most positive of all six archetypes: almost everything here is schedulable replenishment. |
| Basket weight | -10 | Basket anti-redundancy. |
| Visit / search weight | 0-2 | Browsing matters little against repeat purchases. |
| Popularity / fallback | Low | Massive, reliable purchase data makes a popularity fallback less necessary. |
| Trending period | 7-14 days | Short seasonality, weekly products and promotions. |
### 4. Electronics / durable high-tech
*(big-ticket, considered purchase)*
| Parameter | Value | Why |
| --- | --- | --- |
| History size | 30-50 | Few purchases but each is highly meaningful, so keep the entire history. |
| Cross-sell weight | +12 | The accessory (case, warranty, cable) is the biggest post-purchase margin lever. |
| Look-alike weight | +4 | Low, offering a second phone right after a purchase makes little sense. |
| Buy history weight | -6 | Durable goods: customers don't buy another one right away. |
| Basket weight | -8 | Anti-redundancy. |
| Visit history weight | +6 | A long research phase means a visit is a very strong intent signal. |
| Search history weight | +6 | A product search expresses explicit intent ahead of purchase. |
| Popularity / fallback | Medium | Useful for discovery, but the decision stays individual. |
### 5. Travel / trips
| Parameter | Value | Why |
| --- | --- | --- |
| History size | 10-20 | Very few events per person; lean on recent activity rather than a history that mostly doesn't exist. |
| Cross-sell weight | +6 | Becomes more of an upsell (upgraded board basis, extra stars), with limited true complementarity. |
| Look-alike weight | +12 | The core of the engine here: whoever liked the Canary Islands will like the Balearics. |
| Buy history weight | -6 | Customers don't rebook a trip that's already departed. |
| Basket weight | -5 to 0 | Persistent baskets are rare in a travel booking journey. |
| Visit / search weight | +6 | Without a purchase, the destination viewed or searched is the best available signal. |
| Popularity / fallback | High | Around 92% of customers book only once, so the wisdom of the crowd carries most of the recommendation. |
| Trending period | 7-14 days + 360 days | A short-term window for offer trends (private sales) plus a long window as a stable base. |
### 6. Marketplace / large catalog
*(10.000+ SKUs)*
| Parameter | Value | Why |
| --- | --- | --- |
| History size | 40-50 | Lots of signal available; a long history helps refine within a huge catalog. |
| Cross-sell weight | +8 | Real complementarity exists, but it's variable across such a broad range of categories. |
| Look-alike weight | +8 | Essential for navigating a very broad offering. |
| Buy history weight | -4 to 0 | Depends on the durable/consumable mix, neutral by default, then segmented by category. |
| Basket weight | -10 | Anti-redundancy. |
| Visit history weight | +4 | A good browsing signal in a deep catalog. |
| Popularity / fallback | Low + shuffle | Otherwise best-sellers crush the long tail; shuffle reintroduces diversity. |
| Trending period | 7-14 days | A volatile catalog with fast turnover. |
🔍 **Note:** these values are validated starting points to configure from and A/B test, not fixed rules. Your own catalog structure, history depth, and customer behaviour will shift the ideal setting over time.
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