Nextail Case Study: Addressing Source Feed Optimization

Nextail Data Feed Optimization Case Study

 

Nextail is the omnichannel department of Blokker Holding a very large retail company with 10 retail chains, 2200 brick & mortar stores in 8 countries (like The Netherlands, Belgium and Germany) and more than 21.000 employees. Brands include Blokker, Intertoys, Leen Bakker, Xenos & Cook & Co. Nextail operates 20 webshops and is marketing its 250,000 products on 200 shopping channels.

Arjen Hoek, as Manager Performance Marketing, oversees all performance marketing activities with his team at Nextail and DataFeedWatch is their partner in data feed driven marketing. Nextail was facing several challenges when they wanted to make a choice for a new data feed solution. Here’s what these challenges were and how they used DataFeedWatch to resolve these.

 

How to improve the quality of our source feed?

Arjen: "We export data feeds from 20 online stores. Our IT-department makes sure that the feeds are stable and contain as much information as possible. The content and quality of the data differ per store. Sometimes the feeds do not contain some of the data that we need  and often we are able to optimize the data for the PPC-campaigns that we run on various channels."

Here are some of the improvements for Google Shopping made possible through DataFeedWatch:

  • Title: Included brand and other product attributes in the title. More information in the title improves CTR and conversion rate
  • Descriptions: Added keywords to the descriptions so the channels serve our ad for the proper search terms
  • Product Type: Created a product_type for each product, based on its (sub) category.
  • Custom Labels: We applied a label for products that are on sale or are part of a special promotion, so we can adjust our bids for these products in Google Shopping.
  • Categories: Mapped our product types to the appropriate channel-category improves our conversion rate. Products are not categorized very well in our source feed, but DataFeedWatch Bulk Editing enables us to solve that problem.
  • Remove: Products that just have too little data in the source feed are simply removed from the channel feeds, so these products do not lower our overall performance or lead to disapproval (for example: missing image-url)
  • New Channels: We’re adding new channels continuously. By copying the mappings from other channels, this can be done in just a few minutes.

 

How to include your stock positions?

Arjen: "Generating our source feeds impacts on the performance of our online stores. Therefore we chose to set up a separate stock-feed. We are updating the stock status per product multiple times per day via this feed; in DataFeedWatch we can merge that ‘stock feed’ with our master product feed. This way, our stock is always reflected accurately in our online offerings."

 

How to beat competitors with lower prices?

Arjen: "When your competitor is offering the same product at a lower price, selling is an uphill battle. We have very strong brands, so we don’t have to beat every competitor on price, but it is important that our prices are competitive. We use a dynamic pricing tool that automatically adjusts the prices in our webshops, according to our own criteria. Still, for some products we are just not competitive and we don’t want to waste our advertising money on these products.

"We can prevent that by using the competitor price data from our dynamic pricing tool . This tool shows us a live price-rank for all our products. We export this price rank from our pricing tool to DataFeedWatch. We can use that for example like this:

"Price-rank shows if a price is ranked number 1 (the cheapest) or whether we are outranked by competitors. We are able to exclude all products in a certain category from our data feed, if the price rank is more than (for example) 3, because we don’t want to compete if we’re not among the best 3 prices. On a similar note, the dynamic pricing tool, will tell us when our competitors’ products are out of stock or when the price-rank has changed, so we can add it back to our feeds."

 

How to include Gross Margin in our bidding strategy?

Arjen: "The CPA of a product should not exceed its gross margin, or you will lose money on every product sold. Products with a high margin can ’afford’ a higher bid. Likewise, you need to be careful not to overspend on low-margin-products. Having margin-data available in your PPC-campaigns is therefore crucial. This is how we solved that:

"Our gross margins are stored in a different system (not in our online store). We export a feed with margin-data per product from that system and DataFeedWatch merges that with our master product feed. That enables us to create custom labels based on margin-data; we can use these custom labels in our Google Shopping campaign to tweak our bids and make sure that our bids are in line with the gross margin of every product."

 

How to feed other marketing apps?

Arjen: "We use several apps and services to optimize our RoI. We use feeds to dynamically create Google Adwords campaigns, Facebook Campaigns and some other apps that we automatically feed with product data. All these apps rely on excellent product data and they all have their own specific requirements with regard to the format and the fields of the data provided. We can create those feeds according to their exact specs with the Custom Channels from DataFeedWatch. Custom Channel enables us to select the feed format (xml, csv, etc) and define the fields and the values. We can optimize the feeds for other apps in the same way as we optimize our shopping channel feeds."

 

How to feed ‘Where to buy’?

Arjen: "We list our products on the sites of our suppliers. If a consumer visits a manufacturer’s site, (s)he will find one of our shops on that website. We are able to list the appropriate products by creating a data feed for the suppliers’ websites. This is easy to execute by using Custom Channels on DataFeedWatch."

 

Minimize optimization time

Arjen: "With feeds being uploaded to 200 channels on a daily basis, we need to be very efficient when it comes to optimization. DataFeedWatch is very intuitive and making changes is often done in less than a minute. For more complicated issues like regular expression, we rely on their support; live chat is available from early morning till midnight and will resolve most of our questions right away. Optimizing data feeds should be done by the same people that optimize our PPC-campaigns. With DataFeedWatch that is an easy task to take on."

 

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