Train Your AI on Your Own Data to Create Human-Like Content

Out-of-the-box AI models still lack the nuance and specificity needed for certain types of content.

We even analyzed the difference and created an in-depth case study comparing human vs. AI content for SEO ranking.

The good news is you can train your own AI model on custom data to produce more tailored, human-like writing. Whether you want an AI writing assistant that matches your personal tone and style or one optimized for your business and industry, training it on relevant data is the key.

In this post, I’ll explain how to train AI models on your own website content, documents, feedback data, and more.

With the right approach, you can have an AI writer that produces content indistinguishable from a human subject matter expert.

Why Train on Custom Data?

Generic AI models available today like GPT-4 Turbo are pre-trained on vast datasets like Wikipedia and Common Crawl. This allows them to converse naturally and write passable content on most popular topics.

However, when it comes to capturing an individual’s voice or writing optimized, industry-specific content, their output often misses the mark.

Training an AI model on data related to your use case teaches it the patterns it needs to excel at that particular task.

Here are some key benefits:

• Matches Unique Style and Tone - An AI writer trained on your past writing adopts your cadence, word choices, metaphors, and overall style. This helps it blend new pieces seamlessly with your existing body of work.
• Learns Industry Jargon – Training on documents like past blog posts, whitepapers, and website copy educates the AI on key terminology for seamlessly discussing niche concepts.
• Internalizes Brand Voice – Exposing the model to marketing collateral gives it a solid grasp of your ideal messaging and positioning when producing content.
• Incorporates Customer Feedback – Analyzing user opinions and objections around your product via support tickets or chat logs helps the AI cover pain points your audience cares about.

The more relevant data you can feed it, the better your custom AI understands the intricacies of writing effective copy for your goals.

Best Data Sources for Training Your AI Writer

Now that you know why custom ai training is so powerful, let’s explore some ideal data sources to use:

Your Own Content

This is the most obvious place to start. Uploading past blog posts, articles, emails, ads, landing pages, case studies, whitepapers, and other content you’ve written trains AI writing styles and topics specific to your needs. The more quality samples it can learn from, the better.

Website Copy and Documentation

Website copy explaining your products, services, and company mission offer the AI great insight into your brand voice and messaging pillars. Internal documentation like writer’s guides are also tremendously useful for it to adopt your desired style.

Customer Support Data

Exposing the model to user questions and feedback helps it better empathize with your audience’s needs. Analyze support tickets, chat logs, comments, forums, and reviews to uncover pain points, common objections, and current perceptions to address in content.

Industry Publications

Including relevant articles, reports, and news covering your niche educates AI on trends, emerging technologies, competitor landscape, opportunities, and challenges to write informed domain content.

Subject Matter Experts

Interview teams like sales, customer success, product experts, executives, and thought leaders at your company for unique insights and perspectives to incorporate in writing.

The best training encompasses both text-based data and conversations to impart hard facts, behind-the-scenes context, and human intuition no datasets contain.

Step-By-Step Guide to Train ChatGPT on Your Business's Information

Now that you know what data to use, let’s walk through the full training process from start to finish:

1. Compile Relevant Data

Pull together quality samples from the sources above totaling at least 100,000+ words.

More data is generally better for accurate training. Strive for a diverse mix of content types covering key subjects the AI needs to master.

2. Clean and Format the Data

Prepare the data for integration by cleaning and normalizing the format:

• Remove all embedded images, tables, ads or redundant sidebars
• Correct any formatting inconsistencies or errors
• Anonymize sensitive customer data
• Break content into logical chunks by section or document
• Standardize line spacing, indentation, etc.

Properly formatted data prevents skewed or failed training.

3. Train a Base AI Model

With prepared data, it’s time to train your custom model. Services like Performify let you upload data to enhance models from OpenAI or Anthropic.

Key training settings like number of parameters, compute costs, epochs, and frameworks vary between platforms.

Expect at least a few hours up to a couple days for complex models depending on data size and configuration.

4. Refine and Retrain As Needed

Review initial model outputs to assess strengths and weaknesses. Look for overfitting to your data (repeating odd turns of phrase verbatim or getting stuck) as well as gaps in key knowledge areas.

Use this evaluation to further diversify training data and retrain with adjustments for quality and cost/performance tradeoffs. Expect at least a few iterations of refinement.

Real-World Results and Use Cases

With the right data and tuning, customized AI writers will generate remarkably human-like copywriting matching individual styles and topics more accurately than generic models can achieve.

Our Humanized AI Copywriter creates content tailored precisely to each customer's brand voice, aligning your copywriting to audiences as an industry expert would.

A few examples include:

• A freelance blogger trains AI on years of their articles and client samples to recreate their writing to assist drafting new posts efficiently.
• An engineering consulting firm fuels AI with technical documentation to automatically generate codebooks, help articles, RFP proposals, and client deliverables.
• A CBD company uploads landing pages, ads, and product descriptions to produce on-brand marketing assets tuned for their industry.
• An eCommerce retailer shows AI visitor support chats and product reviews to make web copy addressing common buyer concerns and objections.

The applications are limitless. Any individual or company can benefit from an AI perfectly aligned to their voice and needs.

Create a Personalized AI Writer Today

Training AI models on custom datasets takes them from generic to specialized for your goals. Help your AI writer capture your style, terminology, messaging, and audience insights by teaching it with your own content and data.

With quality data preparation and training, you can automate high-quality writing unique to you at scale.  In just hours, you’ll have a customizable writing assistant suited to any use case.