Customer storyTeract

Reactivating store stock to boost click & collect

Thousands of SKUs sold in store did not exist on the website, for lack of a product page. Teract asked Upsellr to rebuild that data: in one month, 2,972 products enriched and approved, ready to go back online.

Robotic lawn mower on a garden lawn, flower pots in the background

Gamm VertJardiland

At a glance

Teract, a major player in French retail with Gamm Vert and Jardiland, had many SKUs available in store but missing from its PIM and its national product repository, and therefore invisible on its website. On a first batch of 5,000 products, Upsellr identified 67.3% of the SKUs from partial data, and delivered 2,972 enriched and approved product pages in one month, without involving the central PIM teams.

  • 1,749 products existed only in stores before Upsellr.
  • 128,000 units of stock involved in Jardiland stores.
  • A product page rebuilt and published in a few hours instead of several weeks.
  • No involvement from the central PIM teams.

Products on the shelf, missing from the website

Teract, a major player in French retail (Gamm Vert, Jardiland), runs a dense network of stores and a constantly changing catalog.

Yet many SKUs available in store were in neither the PIM nor the national repository. Without a product page, they could not be shown on the e-commerce website or offered for click & collect.

The result: lost online visibility, a gap between the stores’ actual stock and what the website offered, and a click & collect flow performing below its potential.

The goal

Bring the SKUs available in store but missing from the PIM back into the digital journey.

Without tying up internal teams on time-consuming manual work.

A 5,000-SKU pilot, starting from partial data

The first batch covered eight families, from regional produce to gardening and pet food. At the start, 1,856 products had a BAN label and 1,538 had supplier information.

Pilot products, by family
  • Regional produce1,527
  • Gardening1,028
  • Pet food621
  • Livestock482
  • Clothing and footwear425
  • Fittings359
  • Household UPC354
  • DIY204

Upsellr was brought in to automate the whole chain, in four steps:

  1. Retrieve : product information from the available sources: the web, manufacturer websites, partner databases.

  2. Structure : the missing data in the format expected by the Teract PIM and the e-commerce feeds.

  3. Generate : product names, descriptions, technical attributes, visuals and FAQs.

  4. Standardize : the metadata to the feed format, so that the online offer matches the stores’ offer.

Two SKUs out of three found

Finding a product from a bare label is the hardest step. Of the pilot’s 5,000 SKUs, the agents identified 3,367, and the rate climbs when a BAN label was available at the start.

overall identification rate
67.3%
with a BAN label
80.5%
without a BAN label
59.5%
Identification rate, by family
  • Household UPC83.0%
  • DIY82.8%
  • Livestock80.0%
  • Gardening73.5%
  • Fittings73.0%
  • Regional produce70.0%
  • Pet food44.6%
  • Clothing and footwear37.0%

Revenue lying dormant in stores

In one month, Upsellr delivered 2,972 enriched and approved products. Of these, 1,749 had until then only been listed locally: as far as the website was concerned, they did not exist.

units of stock involved in Jardiland stores
128,000
in estimated latent revenue
€100,000
Rebuilding and publishing a product page

BeforeSeveral weeks

With UpsellrA few hours

2,950 products can now go back on click & collect, without the central PIM teams having to step in: the range visible online now reflects what the stores actually offer.

Upsellr helped us quickly rebuild complete, structured product data, to put our store stock back online without depending on the PIM. A real step forward for the omnichannel experience.
Seydi SarrSeydi SarrE-merchandising Manager, Teract

Toward full industrialization

The pilot turned a product data gap into a competitive advantage. Three projects are now under way:

  • industrialize the approach across other departments and other Teract banners;
  • extend it to the whole “local store” catalog;
  • add structured attributes for visibility in generative engines.

Sources and method

  • One-month pilot on a first batch of 5,000 SKUs sold in store and missing from the PIM.
  • Identification rate: share of SKUs for which the agents found the product from the starting data (BAN label, supplier information).
  • Stock and latent revenue: estimate for the Jardiland stores concerned, based on the identified products.
  • Lead times and products back online: benefits presented at the end of the pilot.

Frequently asked questions

Key takeaways from this project.

Why were products sold in store missing from Teract’s website?

These SKUs were in neither the PIM nor the national repository. Without a complete product page, they could neither be shown on the e-commerce website nor offered for click & collect.

How many products did Upsellr process during the pilot?

A first batch of 5,000 SKUs across eight families (regional produce, gardening, pet food, livestock, etc.). In one month, 2,972 products were enriched and approved.

What does a 67.3% identification rate mean?

Out of 5,000 SKUs often described by a bare label, the agents found and documented 3,367 products. The rate rises to 80.5% when a BAN label was available at the start.

Did Teract’s PIM teams have to step in?

No. Upsellr automated the collection, structuring and generation of content, in the format expected by the PIM and the e-commerce feeds.

What is the sales potential of these products?

The identified products represent 128,000 units of stock in the Jardiland stores concerned, and an estimated latent revenue of €100,000.

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