Attract

Podcast 2 — In conversation

Speaker A: We redesigned our product landing page last month and conversions went up significantly. The new hero section really seems to attract visitors — they're staying longer and clicking through.

Speaker B: That's a great result. When you say it attracts visitors, do you mean attracts them to the page or attracts them to stay and act?

Speaker A: Both, actually. The SEO changes attract more organic traffic to the page, and then the design changes attract their attention once they're there — keeps them engaged rather than bouncing. The word is doing two jobs in that sentence.

Speaker B: Right — and that's a genuine strength of attract as a verb. It describes both the initial draw — what brings something in — and the sustained pull — what keeps it there. A good product or piece of writing attracts in both senses simultaneously.

Speaker A: I've been thinking about the difference between 'attract' and 'appeal to'. They feel similar but not identical.

Speaker B: They overlap significantly but 'appeal to' is slightly more personal and relational — it suggests the thing speaks to someone's specific preferences or values. 'This design appeals to younger audiences' has a warmer, more targeted sense. 'Attract' is more neutral and broader — it simply describes the magnetic pull without specifying why or to whom it resonates. You'd say 'the display attracted a crowd' — not 'the display appealed to a crowd', which would sound odd.

Speaker A: What about 'draw'? 'The exhibit drew large crowds' versus 'the exhibit attracted large crowds' — are those interchangeable?

Speaker B: Almost interchangeable in most contexts, yes. 'Draw' and 'attract' share that Latin 'trahere' root and are genuine synonyms for the pulling-in sense. 'Draw' is perhaps slightly more casual and physical — you draw someone in, you draw a crowd. 'Attract' is slightly more formal and works better in abstract or metaphorical contexts — 'the policy attracted criticism', 'the company attracted investment'. In practice both work for most uses; context and register decide.

Speaker A: A mistake I sometimes see — 'attract to' as in 'this will attract to new customers'. Is that right?

Speaker B: No — that's a contamination from 'appeal to'. 'Attract' takes a direct object without a preposition: 'this will attract new customers'. The 'to' creeps in incorrectly from phrases like 'appeal to' or 'draw in'. 'Attract to' is not standard — drop the preposition and you're correct.

Podcast 3 — Prompt engineering

Speaker B: 'Attract' in development prompts is the domain language of user acquisition, recommendation engines, search ranking, UI design, and marketing automation — anywhere a system is designed to draw users toward content, features, or actions. Let's work through the real scenarios.

Speaker B: First — a recommendation engine:

Speaker B: PROMPT: Build a content recommendation engine for a news platform. Use collaborative filtering to suggest articles that are likely to attract users based on their reading history and engagement patterns — time on page, scroll depth, and click-through rate. Serve the top five recommendations per user via a REST API endpoint. Log which recommended articles attracted clicks versus which were ignored, and use this feedback to retrain the model weekly. Stack: Python, FastAPI, and PostgreSQL.

Speaker A: Using 'attracted clicks' as the feedback signal for the retraining loop — that framing keeps the recommendation model focused on what actually pulls users in, not just what they were shown. The weekly retraining cycle makes it adaptive rather than static.

Speaker B: Good. Next — a marketing automation campaign:

Speaker B: PROMPT: Create a marketing automation module for an e-commerce platform. Segment customers by purchase frequency and average order value. For high-value inactive customers — no purchase in ninety days — send a personalised re-engagement email featuring product categories that historically attracted their purchases. Track email open rate, click rate, and whether the email attracted a purchase within seven days. Display campaign performance on a dashboard with attracted-revenue as a key metric. Stack: Node.js, PostgreSQL, and SendGrid.

Speaker A: 'Attracted revenue' as a named KPI on the campaign dashboard — that's a business-meaningful metric that ties the marketing action directly to the purchasing behaviour it produced. Using historical category data to personalise the re-engagement email is the feature that makes this tool genuinely useful.

Speaker B: Now a UI design prompt:

Speaker B: PROMPT: Design a product detail page for a SaaS pricing tool that is specifically built to attract sign-ups from enterprise buyers. Include a hero section with a prominent value proposition headline, a feature comparison table highlighting enterprise-tier benefits, social proof logos from recognisable brands, and a sticky call-to-action bar that follows the user on scroll. Use a deep navy and gold colour palette to attract a premium, professional visual impression. Apply entrance animations on scroll for each section. Stack: React and Tailwind CSS.

Speaker A: 'Attract sign-ups from enterprise buyers' as the design brief, with 'attract a premium visual impression' guiding the colour palette — both uses of attract are doing real work. The sticky CTA bar following on scroll is the specific feature that keeps the conversion action always visible.

Speaker B: Here's a talent acquisition system:

Speaker B: PROMPT: Build a job listing optimisation tool for an HR platform. Analyse job descriptions using the OpenAI API and score them on their ability to attract qualified candidates — checking for inclusive language, salary transparency, clear required versus preferred skills, and compelling company culture description. Return a score out of one hundred with specific improvement suggestions for each low-scoring dimension. Store scores and suggestions in a job_listings table in PostgreSQL with before and after versions when descriptions are edited.

Speaker A: Scoring job descriptions on their ability to attract qualified candidates — with before and after version history — that's a genuinely useful HR product. The dimension-level suggestions tell recruiters exactly which part of the posting is failing to attract the right applicants.

Speaker B: One more — a full application:

Speaker B: PROMPT: Build a full-stack SEO content planning platform that helps marketers attract organic traffic. Users enter a target topic and the platform uses the Google Search Console API and OpenAI to identify high-intent keywords that attract clicks in the target niche, suggest article titles and structures likely to attract featured snippets, and track published article rankings weekly. Display an attract-score per article showing estimated monthly organic visitors it is attracting. Stack: Next.js, Node.js, PostgreSQL, and Google Search Console API.

Speaker A: An attract-score per article showing estimated organic visitors attracted monthly — that metric turns a vague SEO goal into a measurable number. The featured snippet optimisation suggestions are what differentiate this from a generic keyword tool.

Speaker B: The lesson: 'attract' in prompts is the verb of pull and conversion — it tells the AI that the system's purpose is to draw users, customers, talent, or traffic toward a specific action or destination. Every feature, metric, and model in the output should be evaluated by whether it increases that pull. Use it as the governing verb in any prompt where acquisition, engagement, or conversion is the goal — and the architecture will be shaped around it.