CodeWords is a chat-native workflow automation platform. It's the quickest way to turn your ideas into automations, simply by chatting with our AI automation assistant, Cody. Feature highlights: One-prompt building: you're always only a single prompt away from building automations that save you hours per week. 2,700+ integrations: connect to all the tools in your stack in just a couple of clicks. Automatically test, debug, and deploy workflow automations — CodeWords handles this for you. If you can think it, you can build it. Under the hood, CodeWords uses code to create your automations so you're not confined to rigid drag-and-drop nodes.

What makes CodeWords different from other automation tools like n8n, Zapier, or Make?

CodeWords is a chat-based workflow automation tool, built for everyone, regardless of technical ability. Unlike Zapier, Make, or n8n, CodeWords is based on code. This means you can be more expressive and creative with what you build, without being confined to the limits of traditional drag-and-drop tools. With automatic testing, debugging, and deploying, you're always one prompt away from automating your workflows.

How much time will I save using CodeWords?

Most automation tools require you to have deep technical knowledge to be successful. On average, the most popular automation tools take 1-3 months to learn, with continuous learning needed after that. CodeWords requires zero technical knowledge. Our non-technical users get started in 2 minutes, and build their first automation in under 10 minutes. On average, our community save 5-10 hours a week once they've finished building their workflows.

Founders, Operators, Growth engineers, Marketers, Vibe coders — CodeWords is for anyone who wants to drive business transformation, scale fast, or who enjoys beautiful and productive systems. You'll be able to fit CodeWords into your workflow, regardless of your job role or technical ability.

Does CodeWords integrate with my existing tools?

CodeWords gives you access to over 2,700 integrations. Connect to any of your favorite tools in just a couple of clicks, without any coding or technical configuration. Quickly and easily create workflow automations that make your existing tools more productive.

How to automate social proof collection for your brand

Social proof converts. Testimonials on landing pages increase conversion rates by 34% according to BigCommerce. But collecting that proof — asking happy customers for reviews, following up, formatting responses, getting approval to publish, updating your website — is a manual slog that most teams deprioritize. Knowing how to automate social proof collection turns occasional testimonials into a steady stream of conversion-boosting content.

The direct answer: identify happy customers through NPS scores or positive support interactions, trigger automated review requests, collect and format responses with AI, and route approved content to your website and marketing channels. CodeWords handles this end-to-end as a managed workflow. Unlike generic AI automation posts, this guide shows real CodeWords workflows — not just theory.

TL;DR

Social proof collection fails when it depends on manual outreach. Automation makes it systematic.
Trigger review requests from NPS promoters, positive support interactions, and milestone events.
AI formats raw customer feedback into polished testimonials, extracts key quotes, and suggests display contexts.
CodeWords manages the pipeline from identification to publication with 500+ integrations.

Who should you ask for social proof?

Not every customer. Target those most likely to give positive, detailed feedback:

NPS promoters (9-10). These customers already told you they'd recommend you. The ask is natural: "You mentioned you'd recommend us — would you share that in a review?" If you've automated NPS surveys, promoter identification is already handled.

Positive support interactions. A customer rated their support experience 5/5 and left a nice comment. Follow up: "We're glad we could help! Would you mind sharing your experience?"

Milestone achievers. A customer hit a significant milestone (100th order, first year as a customer, completed onboarding successfully). The context makes the ask feel earned, not random.

Repeat purchasers. Customers who have bought 3+ times are demonstrating satisfaction with their wallets. A review request at this point has a 40% higher response rate than post-first-purchase requests (PowerReviews).

How to build the social proof pipeline

Step 1: Identify happy customers.

CodeWords monitors your data sources for social proof triggers: - NPS survey response with score 9-10 (via survey automation workflow) - CSAT score of 5/5 from support interaction - 3rd purchase completed in your e-commerce platform - Customer anniversary or milestone event in your CRM

State persistence via Redis prevents asking the same customer multiple times and enforces cooling periods between requests.

Step 2: Send the review request.

Personalize the ask based on the trigger. An LLM (OpenAI, Anthropic, Gemini — no API key setup) generates context-specific outreach:

For a NPS promoter: "Thanks for the kind words in your recent survey. Your perspective could help others like you. Would you be open to sharing a brief testimonial?"

For a milestone achiever: "Congrats on your first year with us! We'd love to feature your story. A 2-3 sentence review would mean a lot."

Send via email, Slack (for B2B), or WhatsApp. Include a link to a simple review form (Typeform, Google Form) with guided questions.

Step 3: Collect and process responses.

When the customer submits their review: - Record the raw response in Airtable or Google Sheets - AI extracts key quotes and highlights - AI generates a formatted, polished version (while preserving the customer's voice) - Classify the testimonial by theme (ease of use, customer support, ROI, reliability)

Step 4: Get approval.

Send the polished version back to the customer for approval: "Here's how we'd like to feature your feedback. Does this look good?"

If they approve, move to publication. If they edit, update and re-confirm. The workflow tracks approval status in your database.

Step 5: Distribute approved social proof.

Route approved testimonials to: - Website: Push to your CMS (Webflow, WordPress) via API. Update the testimonials section automatically. - Social media: Format as a branded quote graphic for LinkedIn, Twitter, or Instagram. - Sales materials: Add to case study library in Google Drive. - Review platforms: Send a follow-up requesting the customer also post on G2, Capterra, or Google Reviews.

How does AI improve the social proof process?

Response formatting. Raw testimonials are often stream-of-consciousness. The LLM restructures them into clear, impactful statements while keeping the customer's authentic voice. "I really love the product, especially how easy it is to set up, and the support team is great too" becomes: "Setup was effortless, and the support team went above and beyond. I recommend it to anyone looking for [product category]."

Theme tagging. AI categorizes each testimonial so you can display the right proof at the right moment. A testimonial about customer support goes on the support page. One about ROI goes on the pricing page.

Highlight extraction. Pull the most powerful 1-2 sentences for banner quotes and social media. The LLM identifies the most specific, results-oriented statements.

According to Nielsen, 92% of consumers trust peer recommendations over advertising. Automated social proof collection ensures you always have fresh, relevant customer evidence.

How does this compare to review management tools?

Trustpilot, G2, Capterra. Platform-specific review collection. Good for their ecosystem but don't aggregate across channels or integrate with your marketing stack.

Zapier automations. Can trigger review requests from CRM events. No AI formatting, no approval workflow, limited to simple trigger-action patterns.

Make scenarios. More flexible than Zapier for multi-step workflows. Still lacks LLM integration for response processing.

CodeWords. Full lifecycle: identify → ask → collect → format → approve → distribute. AI handles personalization and formatting. State persistence manages the multi-step approval flow. Managed deployment with error handling.

FAQs

What's a good response rate for review requests? 10-15% for cold email requests. 25-35% for post-positive-interaction requests. 40-50% for NPS promoter follow-ups. Timing and personalization are the biggest factors.

How do I handle negative feedback that comes in through the review request? Route it to your support team immediately rather than publishing. The workflow detects negative sentiment and triggers a follow-up conversation instead of a publication flow. This turns a potential public complaint into a private recovery opportunity.

Can I automate video testimonial collection? Yes, partially. Send a link to a video recording tool (Loom, VideoAsk) instead of a text form. The workflow can collect the recording URL, transcribe it using AI, and extract key quotes. Video editing still needs human involvement.

How often should I refresh testimonials on my website? Monthly rotation keeps social proof feeling current. Stale testimonials from 2021 undermine credibility in 2026. Automate the rotation: push the newest approved testimonials to the top, archive older ones.