Tools I Use, Frameworks I Trust, and Gadgets I Recommend.

Linux Kali

I rely on Kali Linux for cybersecurity in web application development, eCommerce stores, and API solutions because it provides a powerful suite of tools specifically designed for penetration testing and vulnerability assessment. In the world of online retail, where cyber threats are relentless, securing customer data isn’t just a priority—it’s an absolute necessity. On average, I prevent dozens of cyber-attacks per week for my clients, ranging from brute force attempts to sophisticated SQL injection attacks. In fact, eCommerce sites face thousands of SQL injection attempts daily, as hackers try to exploit database vulnerabilities to steal sensitive customer data, including payment details and personal information. Tools like Burp Suite help uncover security flaws in web applications, Nmap enables detailed network scanning to identify weaknesses, and SQLmap automates SQL injection testing to ensure databases remain locked down. As an online business grows, it inevitably becomes a bigger target for black hat hackers, and the more sensitive data stored, the greater the responsibility to protect it. The consequences of failing to do so can be severe—in the UK, a data breach could result in fines of up to £17.5 million under GDPR, while in the EU, penalties can reach up to 4% of annual global turnover. Beyond financial losses, a security breach can permanently damage customer trust, leading to abandoned carts, reputational damage, and even legal action. Customers rely on businesses to keep their data safe, and using Kali Linux as part of a proactive security strategy ensures that trust is well-placed.

Ruby

I use Ruby primarily in combination with Ruby on Rails, especially for creating tailored and fully custom eCommerce solutions. With my recent focus on eCommerce, Ruby has become essential when transitioning from concept validation on platforms such as Shopify or other SaaS eCommerce tools to building and optimising bespoke shops in Solidus. Ruby on Rails offers the perfect balance of flexibility and structure, allowing me to craft scalable, high-performance eCommerce sites that meet unique business needs. It’s my go-to choice for businesses ready to move beyond one-size-fits-all solutions and unlock their full potential with a custom-built platform.

Python

Python is my go-to tool for data science due to its incredible versatility and the powerful libraries that make complex tasks straightforward. In one project, I used Python to analyse customer purchasing behaviour, predict future trends, and optimise pricing strategies. Using Pandas for data wrangling, Scikit-learn for building predictive models, and Matplotlib for visualising customer segments, I uncovered insights that led to a 29% increase in average order value. I love how Python enables me to iterate quickly, handle massive datasets with ease, and transform raw data into actionable strategies. Below, I’ve listed the libraries that are part of my daily toolbox—they’re the secret weapons I rely on to deliver results.

Rust

I use Rust for webstore development because of its unparalleled performance, memory safety, and ability to handle high-concurrency workloads without compromising stability. Unlike other languages that rely on garbage collection, Rust ensures memory safety at compile-time, preventing crashes and security vulnerabilities—critical in high-traffic eCommerce environments. For my clients, this has translated into ultra-fast page loads, resilient payment processing, and real-time inventory tracking without bottlenecks. One notable case was a client struggling with checkout delays due to database contention; by leveraging Rust’s asynchronous capabilities, I streamlined their order processing pipeline, reducing checkout latency significantly. When performance and customisation are top priorities, frameworks like Axum and Actix Web provide robust solutions, allowing fine-tuned control over request handling and API responses. These frameworks, combined with Rust’s efficiency, make it a top choice for scalable, secure, and high-performance eCommerce applications.

C/C++

Using C/C++ in digital marketing might not seem like the obvious choice, given the prominence of higher-level languages like Python, but in a recent project, it proved to be a game-changer for optimising real-time ad targeting. By leveraging C++ to preprocess and segment user data, implement a high-speed real-time bidding algorithm, and build a personalised ad recommendation engine, we reduced latency by 50% and increased scalability to handle over 20 million daily impressions. Through multi-threading and efficient data structures, we cut bid processing time from 100ms to 30ms, while integrating machine learning models with ONNX Runtime improved click-through rates by 20%. Wrapping these components into a RESTful API ensured seamless integration with existing systems, demonstrating that C++ is invaluable for performance-critical tasks in digital marketing, delivering speed, scalability, and precision.

Ruby on Rails

I use Ruby on Rails because it’s a powerful and efficient framework that accelerates development with its convention-over-configuration approach, built-in tools, and scalability. It’s perfect for creating tailored, completely customised Solidus eCommerce platforms—my forte—helping clients gain a true competitive edge. After testing the waters with Shopify, Magento, or whatever platform my clients initially use, we transition to Solidus, unlocking possibilities that standard eCommerce platforms simply can’t match. With our bespoke implementations, we do things our competitors can’t, ensuring they have no way to keep up with our tactics, strategies, and advanced solutions. Beyond eCommerce, Rails is my go-to for building robust APIs, developing data crawlers in conjunction with Oxylabs, and prototyping specialised web applications, enabling my clients to stay far ahead of the curve.

Django

I use Django when a project’s needs align better with Python’s extensive ecosystem, particularly for tasks like web scraping or data-driven applications. For example, Django pairs seamlessly with Scrapy, making it an excellent choice for building robust frontends to complement large-scale data scraping pipelines. This is especially useful when presenting scraped data or insights in a user-friendly interface for clients. Similarly, Django shines in Data Engineering and Science projects that require a frontend, such as creating dashboards for visualising machine learning results or building tools that interact with complex datasets. While I often turn to Ruby on Rails for tailored eCommerce solutions and APIs, Django’s flexibility in handling Python-heavy workflows makes it the superior choice for projects that merge backend data processing with compelling frontend delivery.

solidus_auth_devise

I’ve been using Devise on all my Rails projects because it’s the de-facto standard for robust, flexible, and secure authentication. Its modular design makes it incredibly easy to customise, ensuring it fits seamlessly into any application. More recently, as my work has focused on custom and tailored eCommerce solutions, I’ve relied on solidus_auth_devise, which integrates flawlessly with Solidus. This combination allows me to build platforms that not only perform but also take my clients’ businesses to a whole new level of awesomeness. Whether it’s user authentication, password recovery, or token-based logins, Devise consistently delivers the reliability and scalability that my projects demand.

haml-rails

HAML is an absolute must-have gem for every Rails project, and for good reason. It transforms messy HTML into a clean, readable, and beautifully structured format, making your views far easier to maintain and understand. By replacing closing tags and excessive indentation with a concise syntax, it not only saves time but also reduces the risk of errors. HAML encourages you to write DRY, elegant code while seamlessly integrating with Rails helpers and partials. It’s been part of every single project I’ve worked on that doesn’t involve React.js—which, to be fair, are becoming fewer by the month. Nevertheless, for traditional Rails projects, HAML remains an indispensable tool.

react-rails

The react-rails gem is an excellent choice for gradually transitioning a standard Rails web application using HTML ERB views into a React-driven frontend. Its standout feature is the ability to incrementally adopt React, allowing developers to rewrite individual pages or components step by step, rather than overhauling the entire frontend at once. This agility is particularly advantageous for teams working on existing Rails applications, as it minimises disruption while enabling modernisation. While more complex setups often involve decoupling the frontend and backend entirely, using APIs such as REST or GraphQL to handle data exchange, react-rails provides a simpler and more integrated approach. It embeds React components directly into Rails views, which is particularly useful in Solidus projects where the need for highly customised and dynamic frontends often arises. Additionally, tools like the superglue gem, designed to expose Rails helpers within React components, streamline the development of tightly integrated Rails-React applications. By making it easier to manage Rails-specific behaviour directly within React components, superglue complements react-rails perfectly, especially in cases where the backend logic is closely tied to the frontend. For anyone modernising a Rails app or handling Solidus customisations, this setup proves to be a pragmatic and effective solution.

byebug

I use the byebug gem because, let’s face it, even the best of us need a trusty sidekick when hunting down those elusive bugs. It’s like having a magnifying glass for Ruby code—helping me pause, inspect, and figure out where everything went pear-shaped. Sure, I could probably solve things the hard way, but why bother when byebug lets me dive straight into the problem with surgical precision? It’s my debugging equivalent of shouting, “Stop right there, you cheeky bug!” Honestly, I couldn’t imagine coding without it, and neither should you—it’s an absolute must-have in the toolbox of every Rails developer.

JetBrains YouTrack

I use YouTrack over Jira and other project management tools because of its simplicity, efficiency, and seamless integration with JetBrains IDEs like RubyMine and PyCharm. While I am fluent in Jira, YouTrack stands out for its intuitive interface, requiring little to no explanation for clients, which is especially valuable when collaborating with non-technical stakeholders. Its integration with JetBrains tools is a game changer, allowing code modifications and additions to be directly linked to issues, commits, and tasks, ensuring that everything is perfectly tracked. This feature becomes crucial for myPay-As-You-Go package, where accurate time allocation and tracking are essential for both transparency and efficient billing. YouTrack’s flexible workflows, custom fields, and powerful search capabilities make it easy to adapt to any project, while its lightweight design ensures quick setup and usability compared to the complexity of Jira. By combining simplicity for clients with robust features for developers, YouTrack provides the perfect balance for managing projects effectively.

Solidus

Rails Solidus is the ultimate platform for businesses that require complete control and customisation over their e-commerce experience. Unlike platforms like Shopify that depend heavily on third-party apps, Solidus provides a robust suite of out-of-the-box gems for key functionalities—product management, checkout, payments, inventory, and more—all seamlessly integrated. What sets Solidus apart, however, is its ability to be tailored precisely to the unique needs of a business. With Solidus, you aren’t shackled to cookie-cutter solutions or expensive apps that often clash with branding or fail to meet nuanced requirements. Best of all, Solidus is open-source and completely free, meaning the only ongoing cost is hosting—putting more money back into your business. Imagine the competitive edge of implementing a referral programme that stands out in a sea of off-the-shelf solutions. While your competitors rely on generic referral apps that anyone can set up, Solidus enables you to craft a truly bespoke programme that aligns with your processes and offers unparalleled value to your customers. For example, I worked on a project with a client selling homogeneous products in a highly competitive market where price wars were the norm. We developed a referral programme that rewarded customers not only with discounts but also with commissions on purchases made by their referrals for a set period. This innovative approach created a massive buzz, resulting in supernormal growth. The scalability and flexibility of Solidus were pivotal in managing the challenges of rapid expansion, from maintaining cash flow to fulfilling supplier commitments and ensuring timely deliveries. The ability to respond quickly to growth demands, implement unique ideas, and streamline operations is what makes Solidus a standout choice. Whether it’s introducing cost-saving measures, integrating advanced payment gateways, or scaling infrastructure, Solidus provides the tools to act decisively. It’s more than a platform—it’s the foundation for building a business that thrives on innovation and custom solutions.

Shopify

Shopify is an excellent platform for testing ideas and launching an initial e-commerce store, providing a streamlined environment to get a shop up and running quickly. Its user-friendly interface, extensive app marketplace, and ready-made templates make it ideal for validating concepts and collecting early data to assess market demand. By leveraging Shopify's tools, businesses can experiment with marketing, sales strategies, and customer communication, identifying areas for improvement and gathering insights on how to optimise their shop's performance. However, Shopify does come with limitations, particularly when a business grows beyond its initial stages and requires more flexibility or customisation. A common challenge is Shopify's constraints around payment providers, particularly for subscription-based models. For instance, if a business needs to improve cash flow to support rapid growth without involving external investors, Shopify's licensed payment providers may fall short. They typically impose restrictive transaction fees and do not offer next-day transfers of daily earnings, which can hinder financial flexibility. On the other hand, customised solutions like Spree Commerce or its spin-off Solidus allow integration with advanced payment gateways such as Windcave, offering better terms, faster payouts, and reduced costs. This kind of financial agility can be critical for scaling a business efficiently. Beyond payments, Shopify's limited customisation options, rigid platform structure, and dependency on third-party apps can become obstacles for businesses with unique needs or proven concepts. In these cases, transitioning to a bespoke solution built on Spree or Solidus can provide the scalability, flexibility, and control required to sustain long-term growth and operational excellence. While Shopify is fantastic for starting out, it's not the right fit for every business in the long run.

Algolia

I use Algolia for search because it’s a powerful, fast, and feature-rich solution that integrates seamlessly with Solidus (Rails) or Node.js/Next.js setups. It eliminates the need to reinvent the wheel with custom-built search engines, which are often resource-intensive and riddled with performance issues. Running searches directly on your production database with SQL, for instance, is not only slow but can bog down your entire site. This can lead to higher server costs, slower page load times, and a cascade of negative effects—poor adherence to Google’s RAIL performance model, lower quality scores, and ultimately higher advertising costs. For one client who spends over £100k daily on Google Ads, improving page performance through better search integration saved significant funds that could be reinvested into growth. Algolia offers advanced features like typo tolerance, faceted search, and personalisation, all of which provide users with a fast, intuitive search experience that keeps them engaged and drives conversions. It also includes invaluable analytics, allowing businesses to see what visitors are searching for, which queries fail, and what products are in demand. This insight is a simple yet often overlooked growth hack. By understanding what customers are searching for, businesses can address gaps in their product range, better serve their audience, and reduce over-reliance on a single brand or product. For many of my clients, this has been transformative—diversifying their offerings not only increased revenue but also future-proofed their business against market shifts. Integrating Algolia is straightforward. In a Solidus setup, you can sync your product catalogue with Algolia via its robust APIs, ensuring real-time updates for inventory and pricing. For Next.js projects, Algolia integrates effortlessly with React components, making it easy to create lightning-fast, user-friendly search experiences. Beyond its technical advantages, Algolia empowers businesses to focus on growth, customer experience, and profitability without worrying about the complexities of building and maintaining a scalable search infrastructure. It’s one of those tools that pays for itself many times over by improving performance, reducing costs, and driving smarter decisions.

Hubspot

HubSpot is a standout CRM and CMS system, offering an impressive range of features even in its free version, such as contact management, email tracking, live chat, and reporting. It’s a cost-effective solution that grows with a business, enabling centralised communication and efficient customer interaction. Unlike platforms that require hefty upfront investments, HubSpot's scalability and ease of integration with e-commerce solutions like Shopify and Solidus make it highly versatile. In one project, a client struggled to manage customer inquiries from various channels, leading to disorganisation and dissatisfied customers. By implementing HubSpot, we streamlined all communication into one dashboard, improved response times, and enhanced customer satisfaction. This helped prevent negative reviews and bad word of mouth, both of which can severely damage a brand’s reputation and sales. CRM is crucial—if you fail to keep customers happy, negative feedback on platforms like Trustpilot can significantly affect your business. HubSpot’s centralised approach ensures businesses can manage customer relationships effectively, fostering loyalty and safeguarding their brand image.

Data Manipulation and Analysis

For data manipulation and analysis in ecommerce-related tasks, I rely on Pandas and NumPy. Pandas enables efficient data manipulation, such as merging customer purchase data and filtering order histories, while NumPy is essential for array operations and mathematical transformations. For example, I might use Pandas to group total sales by product categories or calculate conversion rates per day.

Data Visualization

In data visualisation, Matplotlib and Plotly come in handy for creating insightful charts and interactive dashboards. I often use Matplotlib for quick visualisations, like line charts tracking revenue over time, and Plotly to create dynamic visualisations, such as exploring trends in abandoned cart rates.

Machine Learning

When it comes to machine learning, Scikit-learn and XGBoost are my go-to libraries. Scikit-learn is great for building predictive models, like forecasting customer lifetime value or segmenting users based on purchase patterns, while XGBoost excels in performance for large datasets, such as predicting product demand based on historical data.

Data Collection & Processing

For data processing, Dask and Polars enable me to process massive datasets efficiently, such as aggregating millions of transactions from different ecommerce platforms. BeautifulSoup and Scrapy are my preferred tools for data collection, often used for scraping competitor pricing data or product reviews.

Statistics and Mathematics

In statistics and mathematics, SciPy and Statsmodels are invaluable. I use SciPy for statistical testing, such as A/B tests on promotional offers, and Statsmodels for regression analysis, such as understanding factors that impact conversion rates.

Time Series Analysis

For time series analysis, Prophet by Facebook and Statsmodels enable me to forecast sales trends or analyse seasonality in purchase behaviours, allowing for more accurate inventory planning. Lastly, for pattern recognition and elasticity studies, TensorFlow or PyTorch can be used for advanced tasks like detecting anomalies in sales data or optimising pricing strategies to maximise revenue based on customer response.

RSpec, Capybara, and Cucumber

RSpec, Capybara, and Cucumber are essential tools in my development workflow, especially for Rails Solidus projects, where quality and reliability are non-negotiable. RSpec is a powerful testing framework that allows developers to write clear, maintainable unit tests, ensuring every piece of code behaves as expected. Capybara complements RSpec by providing robust tools for simulating user interactions, such as filling forms, clicking buttons, and navigating pages, making it invaluable for integration and end-to-end testing. Cucumber, on the other hand, focuses on Behaviour-Driven Development (BDD), using plain language scenarios to bridge the gap between technical teams and non-technical stakeholders. It ensures that the entire team, from developers to clients, has a shared understanding of how features should work. While writing tests may feel time-intensive at the outset, the long-term benefits far outweigh the initial investment. Tests act as a safety net, catching bugs early, reducing the likelihood of costly production issues, and increasing customer satisfaction by delivering a smoother, more reliable experience. In my experience, clients who embrace TDD (Test-Driven Development) and BDD benefit from reduced development costs over time, as robust tests prevent regressions and streamline feature additions. I’ve worked on projects where these tools saved us from high-impact errors, such as checkout failures or pricing miscalculations, which could have led to lost revenue and tarnished brand perception. Neglecting proper testing can have severe consequences—escalated development costs, frustrated customers, and a damaged reputation. By using RSpec, Capybara, and Cucumber, I ensure that every aspect of the e-commerce platform is rigorously validated, delivering a shop that customers can trust and appreciate. This commitment to quality not only improves customer satisfaction but also enhances the perception of the brand, turning visitors into loyal customers.

Jetbrains IDEs

I prefer JetBrains IDEs over all others, especially Visual Studio, for one simple reason: they’re worth every penny. Unlike Visual Studio, they’re not free, but the efficiency and productivity gains they bring are unmatched. For my Solidus projects, RubyMine is my go-to tool, offering seamless Ruby on Rails support and advanced debugging features. When it comes to Python, PyCharm handles all my needs, especially in data science. Whether I’m building machine learning models, performing data analysis, or automating workflows—such as a project predicting customer behaviour for an eCommerce store—PyCharm keeps things streamlined. Then there’s WebStorm, perfect for JavaScript and front-end development, and DataGrip, an indispensable tool for managing and querying databases. These tools are a must-have for any developer. Go and subscribe to JetBrains—efficiency just skyrocketed!

Warp

I use Warp as my terminal tool on my Mac because it offers significant advantages over traditional terminal tools, especially for development, deployment, and release workflows. Warp provides amodern, GPU-accelerated interface that makes the terminal feel fast and fluid, improving responsiveness during intensive tasks like running test suites or large-scale builds. Its block-based input/outputfeature allows me to easily navigate through commands and outputs, enabling me to search, copy, and edit previous commands seamlessly. This is particularly useful when I’m troubleshooting errors, reviewing logs, or revisiting previous deployment steps. Warp’s command suggestions and autocompletions save time by reducing the need to remember complex commands, which is invaluable when switching between different development environments or tools like Rails, Solidus, and Docker. Additionally, the built-incollaboration features allow me to share terminal sessions or specific command blocks with team members, making debugging and code deployment more efficient. Warp’s ability to integrate with tools like Git enhances workflows, as I can stage, commit, and push changes directly within the terminal. For releases, features like saved workflows allow me to automate repetitive tasks, such as deploying to staging or production environments, ensuring consistency and reducing errors. With its sleek, intuitive design and focus on developer productivity, Warp is a clear step forward from traditional terminal emulators like iTerm or the default macOS Terminal.

Terminus

I use Terminus to connect to servers because it provides a seamless and reliable experience tailored for managing remote connections, particularly when working with critical systems. While Warp excels as a local terminal tool, Terminus shines when it comes to SSH connections and remote server management, offering a consistent user interface across multiple devices, including mobile platforms. Its cross-platform availability, with robust desktop and mobile apps, ensures that I can connect to servers from anywhere at any time, which is essential given my frequent travel and the need to handle emergencies on the go. Unlike other terminals, Terminus’ session persistence means that even if a connection drops, I can quickly reconnect without losing context. The mobile app is a standout feature, allowing me to SSH into servers directly from my phone or tablet, which is a lifesaver when urgent deployments, monitoring tasks, or troubleshooting issues arise while I’m away from my Mac. Additionally, Terminus’ support for split panes, quick command shortcuts, and encrypted connections enhances productivity and security when managing servers. This flexibility and reliability make Terminus a superior choice over traditional terminal tools and even Warp when remote access is required, ensuring I’m always connected and ready to act, no matter where I am.

Oxylabs

I use Oxylabs for web scraping because of its reliability, scalability, and seamless integration into Rails Solidus, allowing us to turn competitive intelligence into a decisive advantage. In ecommerce, competitive pricing is everything—constantly monitoring and analysing competitors' prices, patterns, and strategies ensures that we can respond instantly and effectively. By integrating Oxylabs scrapers into Solidus, I automate the process of gathering real-time data on competitor pricing and stock levels. This data feeds directly into our pricing engine, enabling automated price adjustments within seconds, a critical edge when competitors still rely on manual price setting. Combined with machine learning models, we analyse price elasticity, product demand, and profit margins to make data-driven decisions about how far to adjust prices to remain competitive while maximising profits. This is a game changer, as it allows my clients to respond in real-time, not just to price drops but also to understand market trends and competitor behaviours. For example, clients with homogeneous products—where differentiation is minimal—have used this approach to become market leaders in certain brands. Oxylabs’ ability to deliver clean, reliable, and up-to-date data makes it the backbone of this strategy, helping businesses not only stay ahead of the competition but dominate their market with precision and speed.

Postmark

I use Postmark as my email delivery service because it is purpose-built for system-generated emails, providing unparalleled reliability, speed, and customisation. Unlike Brevo, which is better suited for bulk email marketing, Postmark focuses on transactional emails such as order confirmations, password resets, and tailored promotional emails. Its simplicity, coupled with its powerful API and Rails gem, makes it incredibly easy to integrate into any Rails or Solidus project, or even with other prebuilt or custom-built systems, regardless of the tech stack. For my Solidus clients, Postmark is a game-changer. We create highly tailored email campaigns driven by scheduled jobs that query customer behaviour, such as purchase history, frequency, and preferences. For one client, this approach increased the conversion rate of newsletters and promotional emails by an astounding 500% in the initial stages, and we’ve continued refining the strategy for even greater results. By delivering highly personalised content, Postmark helps maximise customer engagement and revenue. Additionally, Postmark’s transparency and features are second to none. Its email analytics and roll-over email budget—allowing unused credits to carry over to the next month—make it cost-effective and efficient for businesses of any size. In comparison, services like Brevo often fall short for transactional emails, where speed, deliverability, and tailored messaging are critical. With Postmark, I can confidently send high-quality, targeted emails that help my clients grow their revenue while maintaining a seamless experience for their customers.

Tailwind CSS

I use TailwindCSS because it offers an unmatched level of flexibility and efficiency compared to other frameworks, including Bootstrap, which I initially relied on. Unlike Bootstrap, which comes with pre-designed components that often require significant overriding to match a specific design vision, TailwindCSS is utility-first. This means it provides a highly granular system of CSS classes that allows me to build completely custom designs directly in the HTML without writing extra CSS. TailwindCSS eliminates the bloat of unused styles, resulting in cleaner, faster-loading sites, which is crucial for performance and user experience. Compared to other frameworks, TailwindCSS stands out with its excellent developer experience. Features like Just-In-Time (JIT) compilation ensure that only the classes used are included in the final build, keeping the CSS file small and optimised. Its extensive customisation capabilities, from theming to responsive design, make it easy to tailor the framework to any project’s needs without being boxed in by default styles. Additionally, its integration with modern tools like PostCSS and its focus on productivity means I can rapidly prototype and iterate on designs while maintaining clean and scalable codebases. For me, TailwindCSS hits the sweet spot between power and simplicity, making it the go-to choice for creating bespoke, modern web designs efficiently. It has completely revolutionised the way I approach frontend development.

Google BigQuery

Google BigQuery is an invaluable tool for e-commerce businesses, especially from a Data Engineering and Data Science perspective. Its ability to handle massive datasets with lightning-fast queries makes it essential for advanced analytics, predictive modelling, and marketing automation. I’ve used BigQuery in past projects to help clients unlock insights that their competitors—often reliant on basic tools like Google Ads reports or rigid marketing platforms like SEMrush—simply couldn’t match. By leveraging BigQuery, we’ve delivered highly creative, data-driven strategies that have driven significant business growth and created competitive advantages. One powerful use case involved integrating all customer and transaction data into BigQuery, along with ad performance metrics from platforms like Google Ads, Facebook, and even email marketing tools. By combining these data sources, we could build advanced customer segmentation models, identifying high-value customers based on lifetime value, purchase frequency, and behaviour patterns. For one client, this allowed us to automate personalised retargeting campaigns, showing specific products or offers to each customer segment. The result was a dramatic improvement in ad performance—conversion rates surged, and the cost per acquisition dropped significantly. Another standout use case was predictive inventory planning. By using machine learning models trained on historical sales data stored in BigQuery, we forecasted demand for specific products. This not only reduced overstock and stockouts but also allowed the client to align their marketing efforts with predicted demand. For instance, during seasonal peaks, we tailored campaigns to promote products we knew would perform well, ensuring maximum ROI. BigQuery also played a pivotal role in marketing automation. By exporting real-time insights from BigQuery to Google Ads using Customer Match, we dynamically adjusted bids and budgets based on the value of individual customers. This level of automation went far beyond what standard tools could offer and provided a measurable edge over competitors relying on basic data analysis. Additionally, BigQuery’s integration with Looker Studio allowed us to create custom dashboards, enabling stakeholders to track KPIs in real time and make informed decisions. The scalability and flexibility of BigQuery empower businesses to move beyond surface-level reporting and into the realm of truly actionable insights. In every project where I’ve used it, BigQuery has enabled my clients to outthink and outperform competitors, driving growth, efficiency, and profitability. It’s a cornerstone for any e-commerce business serious about leveraging data as a competitive advantage.

Hotjar

Hotjar is an indispensable tool for e-commerce businesses looking to understand their customers on a deeper level and optimise their online experience. I’ve used Hotjar in numerous client projects to uncover behavioural insights that helped shape strategies, improve user experience, and drive significant business growth. Unlike traditional analytics tools that focus on numbers, Hotjar provides qualitative data like heatmaps, session recordings, and surveys, allowing you to see why users behave the way they do. This has consistently given my clients a major edge over competitors relying solely on basic analytics tools like Google Analytics or cookie-cutter strategies from marketing agencies. One standout use case involved using Hotjar’s heatmaps to identify friction points on a Solidus e-commerce store. We discovered that users were frequently hovering over but not interacting with a product filter menu on category pages. This insight led us to redesign the filter layout, making it more intuitive and mobile-friendly, which immediately increased product discovery and resulted in a 20% lift in category page conversions. For another client, we leveraged session recordings to observe how users navigated the checkout process. It became clear that a significant number of users were abandoning the checkout at the shipping information step due to unclear instructions about delivery times. By tweaking the copy and adding a real-time shipping cost calculator, we reduced cart abandonment by over 30%, directly boosting revenue. Hotjar also shines in helping with marketing automation. By deploying on-site surveys, we captured real-time feedback from users about their preferences and pain points. This data was then used to create hyper-targeted email campaigns and personalised product recommendations, which significantly improved engagement and retention rates. For one client, this resulted in a 3x improvement in email click-through rates and a noticeable uplift in repeat purchases. Hotjar’s ability to provide actionable insights has consistently enabled my clients to outperform their competitors. By addressing customer frustrations, enhancing the user journey, and tailoring marketing efforts based on real customer feedback, we’ve delivered transformative results. Tools like Hotjar aren’t just about gathering data—they’re about understanding your customers and building a shopping experience that keeps them coming back. It’s a must-have for any e-commerce business serious about continuous improvement and growth.

Stripe

Windcave

Lloyds Cardnet

aHREFs

I prefer using Ahrefs over SEMrush for several reasons, particularly its superior data quality and extensive server infrastructure. Ahrefs boasts a vast index, crawling the web 24/7 much like search engines, which ensures comprehensive and up-to-date data. AHREFS This extensive crawling capability provides a more accurate and expansive dataset, crucial for in-depth SEO analysis. One of the standout features of Ahrefs is its robust API, which facilitates seamless integration with platforms like Google BigQuery. This integration allows for advanced data analysis and the creation of custom dashboards. For instance, in a recent client project, we integrated Ahrefs with BigQuery to combine SEO metrics with sales data. This enabled us to identify which keywords not only drove traffic but also led to conversions, allowing for more strategic content creation and targeted marketing campaigns. While I do utilize SEMrush for certain applications, especially in areas like PPC analysis and broader marketing insights, Ahrefs excels in delivering high-quality SEO data and understanding consumer behavior. Its comprehensive backlink analysis and keyword research tools provide deep insights into what content resonates with audiences and the questions they are asking. This information is invaluable for crafting content strategies that drive revenue growth. In summary, Ahrefs' commitment to data quality, powerful API capabilities, and user-friendly interface make it my preferred choice for SEO-related tasks. Its ability to provide actionable insights into consumer behavior and content performance offers a significant advantage over competitors.

Google Ads

I use Google Ads not just for its advertising capabilities but for the wealth of additional tools it offers, which are essential for running effective campaigns and making data-driven decisions. As a Google Ads Partner, managing six-figure daily budgets is part of my routine, and the sheer scale of this spend generates vast amounts of data to analyse. Google Ads isn’t just about ad placements—it’s a platform filled with resources that allow me to optimise campaigns, troubleshoot issues, and extract actionable insights to fuel growth. One of the tools I heavily rely on is the Keyword Planner, which is invaluable for uncovering high-performing search terms, understanding user intent, and spotting opportunities to enter new markets. This goes beyond ads; it influences broader marketing and content strategies, ensuring alignment with what real customers are searching for. The platform’s diagnostic tools are another vital asset. For example, the Ads Diagnostics Report identifies and resolves potential delivery issues, such as policy violations or poor ad relevance, keeping campaigns efficient and competitive. Additionally, Google Ads provides granular data on Quality Scores, impression share, and click-through rates, which allows for continuous campaign refinement and cost optimisation. Audience insights from Google Ads are unparalleled. With its reporting tools, I can analyse demographic data, device usage, and search behaviours to create highly targeted campaigns that outperform generic approaches. This data also feeds into strategic decisions, helping my clients better understand their customer base and adapt their offerings to meet demand. A major advantage of Google Ads is its seamless integration with other Google tools like Google Analytics, BigQuery, and Looker Studio. These integrations allow me to combine ad performance data with website analytics for deeper insights into conversion paths, customer journeys, and the real ROI of campaigns. For instance, I’ve used BigQuery to process Google Ads data at scale, revealing audience behaviour patterns that unlocked new revenue streams for clients. In summary, Google Ads is more than just an ad platform; it’s a comprehensive toolkit that supports smarter, data-driven marketing decisions. Managing six-figure daily budgets means optimising every detail, and Google Ads provides the insights and tools necessary to achieve exceptional results for my clients, from identifying opportunities to resolving issues and driving sustainable growth.

Google Ad Transparency

I leverage Google’s Ad Transparency tools as a crucial component of my strategy as a digital and growth marketer. From a data science and competitive intelligence perspective, this feature provides unprecedented access to granular insights into competitor activity, offering a real-time lens into their advertising strategies, messaging priorities, and product focus. By analysing the data available through Ad Transparency, I can reverse-engineer competitors’ tactics and identify not only what they’re selling but also what they’re prioritising or struggling to move in their product catalogue. For one client, we used Ad Transparency to track a competitor’s ad patterns and discovered that they were disproportionately advertising discounted bundles of slow-moving inventory. This suggested the competitor was struggling with excess stock—a critical insight that informed our pricing and promotional strategy. By focusing our campaigns on high-demand, premium products while their efforts were diluted across clearance sales, my client established a stronger market position and increased their average order value by 30% within a quarter. From a data science perspective, Ad Transparency data can be collected, processed, and analysed to uncover trends in creative iterations, keyword focuses, and budget allocation. For example, by comparing ad copy and targeting themes across a competitor’s campaigns, I’ve identified gaps in their strategy. In one case, we noticed that a competitor heavily advertised their core product line while neglecting related accessories. This insight allowed us to ramp up campaigns targeting accessories, capturing untapped demand and converting customers who weren’t fully served by the competitor. Ad Transparency also helps optimise marketing automation workflows. By feeding competitor ad data into machine learning models, I’ve predicted seasonal shifts in advertising focus and adjusted campaigns accordingly. For instance, observing competitors ramping up advertising around niche product categories signalled emerging trends, allowing us to adapt faster and secure early mover advantage in those markets. The ability to understand the behavioural psychology behind competitors’ ad choices is another critical aspect. By assessing the emotional appeal and pain points highlighted in their campaigns, I’ve tailored messaging for my clients to outmanoeuvre competitors. For one brand, I developed campaigns that addressed customer concerns competitors were failing to mitigate, resulting in a 40% higher click-through rate on average. In essence, Google Ad Transparency is not just a window into competitor activity—it’s a treasure trove of actionable data. It enables me to uncover trends, gaps, and opportunities, which I then turn into strategies that deliver measurable growth for my clients. By combining this data with predictive analytics and market insights, I ensure my clients stay ahead in an increasingly competitive landscape. My question: Why would you pay £££ for SEMrush & Co. when the data is freely available?

Google Trends

I use Google Trends as a powerful tool to identify and analyse market trends, customer interests, and seasonal patterns. By tracking keyword popularity over time, I can uncover emerging topics, predict demand shifts, and align my clients’ strategies accordingly. For example, I’ve used it to pinpoint rising interest in specific products before competitors caught on, allowing my clients to adjust inventory and marketing campaigns in advance. Google Trends is also invaluable for geographic targeting, helping me focus campaigns in regions where interest is highest. Its ability to provide real-time insights gives me a critical edge in creating data-driven, timely strategies that drive growth.