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Marketing Executive

Jamie Gentile-Clarke

Managing Director

Matt Cooke

Website Manager

Nathan McEvoy-Swann

Head of Digital and CRM

Charita Chutoorgoon

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Wattbike

the human-led tech-enabled ecommerce agency

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Fitness

Website Development

Implementing scalable Shopify solutions for Wattbike’s new product launches

Parkside Tiles

Shopify design & build services

Retail

Ecommerce Design & Development

Refining online retail through a custom Shopify design and build for Parkside Tiles

Alert Electrical

SEO & PPC

Driving 20% revenue growth for Alert Electrical in just 3 months

Nottingham Lighting Centre

Home & Garden

Interiors

Building a scalable online presence for Nottingham Lighting Centre

David Morris

Jewellery

Luxury

David Morris x Japan: Building a Shopify store for the Japanese Luxury Jewellery Market

Alfresco Chic

How we delivered a 79.27% boost in conversions for Alfresco Chic through smart PPC

Optimising David Morris’ digital footprint with impactful, multi-faceted SEO 

Wholesale

Website Migration

Powering a faster, smarter ecommerce experience for Alert Electrical

Redesigning luxury: Ecommerce web design for London Jeweller, David Morris

Revitalising growth for Alert Electrical through PPC and SEO

Alert Electrical is a well-established electrical wholesaler with multiple branches across the Midlands. In addition to their strong trade counter presence, they had a website that was already generating significant revenue.

After speaking with one of our other clients, Alert Electrical reached out to us with the goal of revitalising their growth. They were looking to boost performance across their 

 efforts, as recent revenue figures had started to plateau. Our main objectives included:

Using artificial intelligence to enhance decision making with Google Ads

Managing an ecommerce account with thousands of SKUs presents a major challenge: minimising wasted spend.

While the standard approach for a PPC expert is to rely on negative keywords, this becomes increasingly complex when dealing with a seed list of over 7,000 products. For context, Alert Electrical triggers ads from approximately 120,000 search terms every month. 

To scale decision-making, we developed a seamless integration between Google Sheets and the GPT API, enabling us to leverage artificial intelligence to categorise each search term into one of five categories: product, product category, transactional, informational, or irrelevant. This allowed us to efficiently filter and analyse search terms based on their relevance.

With these AI-driven insights, we could adjust bidding strategies to eliminate irrelevant and informational queries whilst optimising spend. The next step is to leverage this data for more targeted informational campaigns moving forward.

As a result, we saw a significant boost in revenue from Google Shopping, all while operating more efficiently and cost-effectively for our client.


Revenue

Keyword Ranking

Keywords in positions 1-3

Keywords in positions 1-10

20% more revenue within 3 months, within the same budget

Our splitting of the main Google Shopping campaign into smaller, category based campaigns delivered huge results, seeing return on ad spend (ROAS) go through the roof.

 to improve the positioning of key products and categories, led to an outstanding result of 20% revenue growth within 3 months without spending more on ads. We also have the scope for much more growth over the next 12 months, we can’t wait to see how far we can take it!

Alert Electrical stocks over 10,000 products, presenting a challenge when it comes to optimising them for search. We needed to create a method to highlight the biggest opportunities so that we could focus on them, with a view to bringing in big data tooling such as BigQuery, Python scripting and Machine Learning further down the line (after we’d created some initial momentum).

We have been lucky enough to have a good communication channel with Alert’s website manager, who has a deep level of product knowledge and knowledge of the profitability of different items, allowing us to make recommendations based purely on search data, and then be steered based on which items are the most profitable for them.

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