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How to Write Quality Content for E-Commerce Website 10x Faster

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How to Write Quality Content for E-Commerce Website 10x Faster


Content is one of the pillars of any e-commerce platform. Whichever products you sell, they at least need proper descriptions so that your customers can find them and understand what they are looking at. Writing hundreds of descriptions is a chore though, and takes hours, days and weeks.

A big company like Amazon with its 1.5 million employees may not even give a hoot about content production costs. For a small business where human resources are always limited, it becomes a real burden. In this article, I will tell you how to write content fast.

Facing the Problem

Let me introduce myself: my name is Andrei and I’m a senior editor at A1 SolarStore, an American online solar equipment store. There are two types of content that our website requires.

The first one is articles about solar energy and how to use it. This is high-quality content that we keep engaging and helpful for readers: we pick a topic, we do the research, and we spend a lot of time editing and polishing the text. Our efforts bear fruits but it still would be nice not to spend over 10 man-hours on a single article.

The second is all sorts of service texts. They are SEO-optimized and frankly dull and exhausting to write. In particular, our business needs descriptions for every solar panel that it sells. To make a description, a copywriter needs about 1-2 hours. There are hundreds of solar panels in stock with new ones being added constantly, so you can imagine the sheer volume of work.

We are always looking for solutions that would allow us to do more and work less. That’s why we embarked on a quest to minimize the time we spend writing the same things over and over again.

Speeding Up the Magazine

Of course, we tried to make ChatGPT write high-quality content for us. While this AI is a wonder, the results were controversial.

As you get familiar with ChatGPT, its flaws shine through. Here are the ones that we found most problematic:

  • ChatGPT 3.5 knowledge cuts off in September 2021. You can’t use it if you need the latest information.
  • You have to do fact-checking. ChatGPT makes mistakes: some come from outdated databases and some appear just because the bot was taught incorrectly. In-depth articles are what it struggles with, especially if your subject is complex and uncommon to begin with.
  • It doesn’t write well. The sentences are wordy, dull, and complex. Editing them sometimes takes more time than writing a piece from scratch.

When your blog has an established style, the quality of content is important and you need up-to-date info, ChatGPT capabilities are limited. We still use it a lot though. Rather than making it write articles for me, I ask it to explain difficult concepts for me, do the math, brainstorm ideas for headlines and many more.

Finding the right prompts is important. A query like “Explain x in simple terms”, “Explain x to me as if I’m a beginner” sometimes returns answers that you can use in your articles as is. Be specific about your task. Set up limitations: “Write two paragraphs, three sentences each”.

If you don’t like what you get, try breaking up the task into smaller pieces. Instead of asking to write an entire article, try asking ChatGPT questions that different parts of your text should answer. If you have a part that gets repeated often in your articles, I recommend trying QuillBot for paraphrasing.

Some articles just can’t be written with ChatGPT. With some, AI does most of the job and the result needs just a little polishing. Overall, AIs have proven to be immensely useful and have sped up our work by 20-60% on average.

Automating Descriptions

Unfortunately, we couldn’t make ChatGPT write product descriptions for us. However, our copywriter Max Kulik got so fed up with depicting different solar panels that he devised his own solution. This is where we’ve got our own breakthrough with how to write content fast.

Product descriptions follow or can be made to follow a similar structure. In the case of solar panels, the content is also very similar. There are a few technologies and features that may be different across individual solar panels, but there are not many overall. To give an example, solar panel descriptions often mention power output, efficiency, weather resistance, design features, etc.

When a product goes out of stock, the efforts that went into talking about it seem wasted. But what you wrote there may be valuable in and of itself. If you like how you conveyed a concept like warranties of a solar panel in a particular description, you can use it in the next one. Rather than just using Ctrl+C Ctrl+V, Max decided to automate the whole process.

Devising the Algorithm

A little bit of creativity and basic coding skills can go a long way. This is the process that Max followed in order to automate our descriptions:

  1. Max identified the common structure and content of solar panel descriptions. After writing descriptions manually for so long, it wasn’t difficult to come up with a universal structure.
  2. Using the structure, he created a template for solar panel descriptions. This template was divided into multiple logical parts, with some parts being optional depending on the specific panel.
  3. Max separated existing descriptions into building blocks. He used our stockpile of written descriptions, separating each into the building blocks for our template. This involved identifying the specific information that each description contained and fitting it into the appropriate sections of the template.
  4. Our copywriter replaced individual recurring data with variables. This would allow us to easily change the descriptions to reflect the specific characteristics of each panel.
  5. Max wrote a Python script for a program that would create a description based on 25 individual characteristics that would be filled manually for each panel in a Google sheet. Based on these traits, our script would automatically fill in the appropriate details and pick the template sections required for each particular description.
  6. Finally, we were able to Implement the automated process. We used Google Colab to create a simple interface. Whenever a new panel came, we could just fill the Google sheet with its characteristics, run all cells in the notebook and get a link to the Google doc with the description in just a few seconds.

How to Write Content Faster: The Results

The program that Max developed for this automation process wasn’t all that complex, and we didn’t even have to send a request to our IT department. The Python script uses Numpy, Gsread and Docx libraries to handle and manipulate data. Manually written and proofread texts meant we didn’t need advanced natural language processing techniques to ensure that the generated descriptions are grammatically correct and semantically meaningful.

Still, the script includes a number of validation checks to ensure that the input parameters are accurate and complete. For example, the script checks to see if the input values fall within a certain range or if they match a specific format. This helps to prevent errors and ensure that the generated descriptions are as accurate as possible.

The solution took us under 30 hours of work, including preprocessing of the manually written texts. It works: it now takes around 10 minutes to write a description for a solar panel. Aside from filling the Google sheet with the panel’s characteristics, which takes about 10 minutes, all that’s required is a couple of clicks. When you build a text like a Frankenstein monster, it isn’t always pretty. But it doesn’t have to be: these descriptions do the job, and the tool saves our copywriters countless hours each week.

All the magic is in making a universal template and preprocessing the available texts. Just 5–7 alternatives for each logical block in your description template can give decent results. Make sure the alternatives are fully interchangeable and really think about the characteristics you’ll use and how they will be affecting the composition of the resulting description. This will guarantee linguistic diversity and good structure. Shoutout to Max who taught us how to write content faster – thank you from the bottom of my heart.

Andrei Gorichenskii

I’m the senior editor of A1SolarStore.com Magazine. Climate change and its impact on people’s lives have always been among my interests and they partially explain my degree in Philosophy and Ethics

Politics

Fintech Kennek raises $12.5M seed round to digitize lending

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Google eyed for $2 billion Anthropic deal after major Amazon play


London-based fintech startup Kennek has raised $12.5 million in seed funding to expand its lending operating system.

According to an Oct. 10 tech.eu report, the round was led by HV Capital and included participation from Dutch Founders Fund, AlbionVC, FFVC, Plug & Play Ventures, and Syndicate One. Kennek offers software-as-a-service tools to help non-bank lenders streamline their operations using open banking, open finance, and payments.

The platform aims to automate time-consuming manual tasks and consolidate fragmented data to simplify lending. Xavier De Pauw, founder of Kennek said:

“Until kennek, lenders had to devote countless hours to menial operational tasks and deal with jumbled and hard-coded data – which makes every other part of lending a headache. As former lenders ourselves, we lived and breathed these frustrations, and built kennek to make them a thing of the past.”

The company said the latest funding round was oversubscribed and closed quickly despite the challenging fundraising environment. The new capital will be used to expand Kennek’s engineering team and strengthen its market position in the UK while exploring expansion into other European markets. Barbod Namini, Partner at lead investor HV Capital, commented on the investment:

“Kennek has developed an ambitious and genuinely unique proposition which we think can be the foundation of the entire alternative lending space. […] It is a complicated market and a solution that brings together all information and stakeholders onto a single platform is highly compelling for both lenders & the ecosystem as a whole.”

The fintech lending space has grown rapidly in recent years, but many lenders still rely on legacy systems and manual processes that limit efficiency and scalability. Kennek aims to leverage open banking and data integration to provide lenders with a more streamlined, automated lending experience.

The seed funding will allow the London-based startup to continue developing its platform and expanding its team to meet demand from non-bank lenders looking to digitize operations. Kennek’s focus on the UK and Europe also comes amid rising adoption of open banking and open finance in the regions.

Featured Image Credit: Photo from Kennek.io; Thank you!

Radek Zielinski

Radek Zielinski is an experienced technology and financial journalist with a passion for cybersecurity and futurology.

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Politics

Fortune 500’s race for generative AI breakthroughs

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Deanna Ritchie


As excitement around generative AI grows, Fortune 500 companies, including Goldman Sachs, are carefully examining the possible applications of this technology. A recent survey of U.S. executives indicated that 60% believe generative AI will substantially impact their businesses in the long term. However, they anticipate a one to two-year timeframe before implementing their initial solutions. This optimism stems from the potential of generative AI to revolutionize various aspects of businesses, from enhancing customer experiences to optimizing internal processes. In the short term, companies will likely focus on pilot projects and experimentation, gradually integrating generative AI into their operations as they witness its positive influence on efficiency and profitability.

Goldman Sachs’ Cautious Approach to Implementing Generative AI

In a recent interview, Goldman Sachs CIO Marco Argenti revealed that the firm has not yet implemented any generative AI use cases. Instead, the company focuses on experimentation and setting high standards before adopting the technology. Argenti recognized the desire for outcomes in areas like developer and operational efficiency but emphasized ensuring precision before putting experimental AI use cases into production.

According to Argenti, striking the right balance between driving innovation and maintaining accuracy is crucial for successfully integrating generative AI within the firm. Goldman Sachs intends to continue exploring this emerging technology’s potential benefits and applications while diligently assessing risks to ensure it meets the company’s stringent quality standards.

One possible application for Goldman Sachs is in software development, where the company has observed a 20-40% productivity increase during its trials. The goal is for 1,000 developers to utilize generative AI tools by year’s end. However, Argenti emphasized that a well-defined expectation of return on investment is necessary before fully integrating generative AI into production.

To achieve this, the company plans to implement a systematic and strategic approach to adopting generative AI, ensuring that it complements and enhances the skills of its developers. Additionally, Goldman Sachs intends to evaluate the long-term impact of generative AI on their software development processes and the overall quality of the applications being developed.

Goldman Sachs’ approach to AI implementation goes beyond merely executing models. The firm has created a platform encompassing technical, legal, and compliance assessments to filter out improper content and keep track of all interactions. This comprehensive system ensures seamless integration of artificial intelligence in operations while adhering to regulatory standards and maintaining client confidentiality. Moreover, the platform continuously improves and adapts its algorithms, allowing Goldman Sachs to stay at the forefront of technology and offer its clients the most efficient and secure services.

Featured Image Credit: Photo by Google DeepMind; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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Politics

UK seizes web3 opportunity simplifying crypto regulations

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Deanna Ritchie


As Web3 companies increasingly consider leaving the United States due to regulatory ambiguity, the United Kingdom must simplify its cryptocurrency regulations to attract these businesses. The conservative think tank Policy Exchange recently released a report detailing ten suggestions for improving Web3 regulation in the country. Among the recommendations are reducing liability for token holders in decentralized autonomous organizations (DAOs) and encouraging the Financial Conduct Authority (FCA) to adopt alternative Know Your Customer (KYC) methodologies, such as digital identities and blockchain analytics tools. These suggestions aim to position the UK as a hub for Web3 innovation and attract blockchain-based businesses looking for a more conducive regulatory environment.

Streamlining Cryptocurrency Regulations for Innovation

To make it easier for emerging Web3 companies to navigate existing legal frameworks and contribute to the UK’s digital economy growth, the government must streamline cryptocurrency regulations and adopt forward-looking approaches. By making the regulatory landscape clear and straightforward, the UK can create an environment that fosters innovation, growth, and competitiveness in the global fintech industry.

The Policy Exchange report also recommends not weakening self-hosted wallets or treating proof-of-stake (PoS) services as financial services. This approach aims to protect the fundamental principles of decentralization and user autonomy while strongly emphasizing security and regulatory compliance. By doing so, the UK can nurture an environment that encourages innovation and the continued growth of blockchain technology.

Despite recent strict measures by UK authorities, such as His Majesty’s Treasury and the FCA, toward the digital assets sector, the proposed changes in the Policy Exchange report strive to make the UK a more attractive location for Web3 enterprises. By adopting these suggestions, the UK can demonstrate its commitment to fostering innovation in the rapidly evolving blockchain and cryptocurrency industries while ensuring a robust and transparent regulatory environment.

The ongoing uncertainty surrounding cryptocurrency regulations in various countries has prompted Web3 companies to explore alternative jurisdictions with more precise legal frameworks. As the United States grapples with regulatory ambiguity, the United Kingdom can position itself as a hub for Web3 innovation by simplifying and streamlining its cryptocurrency regulations.

Featured Image Credit: Photo by Jonathan Borba; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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