Stelrad operate in a highly competitive industry and whilst they are busy year-round, like to take advantage of the autumn and winter months. As heating specialists both supplying and manufacturing products, we had twice the opportunity to increase the visibility of the brand, which already has credibility. Our objectives for this campaign were clear, with Stelrad wanting to achieve the following to compete at a bigger scale:
Stelrad had previously worked with another digital marketing agency and so we conducted a review historical sales performance and analyse the product portfolio based on spend vs returns to identify the best starting point. Using this information, we went on to create a keyword mapping file to relate to each product type and identify USPs for each radiator category.
We also further refined and optimised the shopping product feed through title optimisation, segmentation, and inclusion of GTINs to help assign products to their correct category within shopping. As part of this, we segmented our match types for each search campaign to effectively manage bids by search query.
We wanted to make sure the campaign was a success from the start, so we created a series of best seller campaigns to ensure those items with greatest revenue return and highest sales are given adequate exposure.
To manage this, we updated the tracking on the website to understand the sales journey and which products have a higher propensity to sale vs those with high traffic but minimal sales performance. We then reported this data back to the client through bespoke Data Studio reports to capture relevant Ecommerce performance by product and category level.
- We blended the data from both GA and Google Ads to identify which products sell onsite vs. those with media spend vs. those which have converted in Google Ads. By doing this, we were able to better understand the top drivers by traffic and spend as well as where the opportunities lie and how we could reduce wastage.
- Mapping of sales products by categories to see quantity/revenue/traffic on product ranges to know where best to place bids and to help drive revenue.
- Creation of sales funnel view in Data Studio to see which products have a greater propensity to convert and thus understand where best to place bids.
- Creation of timelines in auction insights to understand when competitors make a move in terms of bid adjustments and how to respond to fluctuations in impression share.
- Segmentation of campaigns into granular subcategories by type, room, function, brand, features to enable more control on media activity.
- Implementation of DSA campaigns to help mine for additional search queries.
- Use of G-Sheets within Merchant Centre to optimise the product feed with enhancements to titles/images/descriptions and other attributes to help increase the data quality in shopping.
We have seen huge growth in traffic from all channels from 20k, to 42k+ monthly users during quiet periods, with a further peak in traffic expected during the Autumn/Winter (high sales season). This is a total increase of 110%.
Revenue increased by 445% MoM, from an average of £42k, to £229k.
Conversions increased by 648% from 50, to 374 conversions generated in one month.
Further to this, the rise in revenue contribution made by Google Ads from £25k, to £93k. This is a total increase of 272%.
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