Episodes

Maya and Tom conclude the first season of How To Get Discovered by presenting a year-long thought experiment between two identical podcasts. Show A invests in structured transcripts and dedicated web pages, while Show B relies solely on traditional distribution. The experiment tracks how these divergent technical strategies impact audience growth and long-term search visibility across a twelve-month period. By month three, Show A begins capturing long-tail search queries from AI referrers like ChatGPT and Perplexity.ai, while Show B experiences the typical cycle of initial spikes followed by total silence. At the six-month mark, Show A transforms its back catalogue into a functional asset that attracts new listeners through archived content. One host admits that over-optimizing for search engines by using literal question titles can thin out a show's unique voice, emphasizing that every loyal subscriber starts as a stranger who needs a discovery path. The analysis reveals that the silent cost of inaction for Show B is not a loss of current listeners, but the total absence of invisible growth opportunities from the open web. Maya and Tom reflect on their journey through podcast plumbing and DNS settings before taking a seasonal hiatus. The finale highlights a rare moment of vulnerability as the hosts confess to past mistakes in keyword-stuffing descriptions. This human element balances the technical deep dive into how timestamped moments and shared clips function as modern word-of-mouth marketing for independent creators.

Tom and Maya challenge the myth of overnight podcast success by analyzing the first month of growth for an ordinary gardening show. Using this case study, they demonstrate how Google and AI tools like Perplexity.ai impose a probation period on new content, often yielding zero traffic in the first three weeks of indexing. This realistic look at discovery reveals why most creators quit just before their search authority begins to compound. Google Search Console data shows that significant traffic gains occur around month four when specific episodes move from page two to page one of search results. Unlike reactionary news segments that lose value within seven days, evergreen topics like tax advice or planting garlic act as backloaded assets that earn more listeners in their second year than their first. PodHerd analytics further distinguish between high-intent problem-solving queries and the noise of daily download fluctuations that often mislead new creators. Tom and Maya emphasize that descriptive titles are the only way to prevent a back catalogue from becoming a pile of old newspapers. They preview the upcoming season finale of How To Get Discovered, which will feature a twelve-month comparative study of two identical shows to prove the long-term ROI of SEO. The hosts also commit to revealing their own personal production mistakes from the current season.

Google Search visibility for podcasts depends on technical infrastructure rather than just content quality. Maya and Tom analyze the mechanics of indexing on episode eight of How To Get Discovered, titled Under the Hood. The segment demonstrates how two visually identical transcript pages can yield vastly different results in Google Search Console based on their underlying structured data and metadata labels. PodHerd provides CNAME records to ensure creators maintain domain authority on their own subdomains rather than surrendering SEO reputation to third-party hosting platforms. Proper transcript formatting using anchor links and timestamped headings allows Google crawlers to index specific segments as standalone answers. This technical setup enables the Domain Name System to correctly attribute site history and backlinks to the creator, while tools like Google Search Console track impressions and click-through rates to verify which episodes successfully capture search traffic. Tom and Maya maintain a strict jargon count to ensure complex networking concepts remain accessible to independent creators. The pair concludes by committing to a transparent case study that avoids outlier success stories to show the realistic, slow-burn growth of a new podcast. This episode marks the transition from basic discovery to the long-term compounding value of owned digital assets.

Maya and Tom challenge the podcasting status quo in the seventh installment of How To Get Discovered by dissecting the psychological intent behind search queries. They analyze three specific freelance-related searches—ranging from rate negotiation tactics to UK business structures—to demonstrate how identical keywords mask vastly different user needs. This shift from simple SEO to intent-based discovery positions the podcast as a dynamic tool for both immediate answers and long-term authority. The framework identifies three listener archetypes: the Moment seeker, the Relationship builder, and the Authority hunter. A tax-focused episode serves as a primary case study, proving that specific legal queries can drive consistent traffic years after the original air date. By utilizing technical infrastructure like Grow the Herd and Lead the Herd, creators can transform a standard RSS feed into a citable archive for journalists and researchers. The hosts emphasize that high-quality transcripts and timestamped chapters are not just accessibility features but essential tools for becoming a referenced industry resource. Maya and Tom share a personal anecdote about being quoted by a journalist who bypassed the regular feed entirely to find a specific answer via search. The duo critiques the industry's obsession with raw click counts, arguing instead for a strategy that treats every search result as a front door for potential loyalists. Tom prepares to enforce a strict no-jargon rule for the upcoming technical deep dive into metadata and web crawling.

Tom and Maya reveal a strategic framework for podcast show notes that transforms generic descriptions into high-converting sales pitches. This sixth episode of How To Get Discovered identifies show notes as the second most critical discovery asset after the episode title, requiring a persuasive structure to convert browsing strangers into active listeners. Tom identifies three primary titling failures—cute inside jokes, lazy episode numbers, and keyword-stuffed strings—advocating instead for descriptive, human-centric summaries. The Podcasting 2.0 standard introduces technical enhancements like AI-generated chapter markers via PodHerd and searchable transcripts to improve retention. Metadata optimization extends to the Apple Podcasts author field and category selection, where Tom warns against broad headers like Business in favor of niche subcategories. A critical workflow error is addressed where hosts publish detailed notes on websites while leaving the Spotify and Apple feed descriptions blank, missing the audience at the point of consumption. Maya and Tom share a summary checklist for auditing a show's five most popular episodes to ensure titles and descriptions meet modern search standards. The conversation concludes with a preview of next week's analysis regarding the specific intent behind listener search queries.

A dry filler episode titled Sole Trader or Limited Company became a surprise growth engine for the How to Get Discovered podcast by answering a specific tax question. This accidental success highlights how durable content outperforms news-driven segments in long-term listener acquisition. By focusing on evergreen questions that people type into Google, creators can turn their back catalogue into a permanent recruitment tool for new subscribers. Podherd and other AI transcription tools now allow creators to detect chapters and extract hidden value from long-form interviews. Renaming vague titles that only feature a guest name to reflect specific searchable problems, such as moving from an agency to an in-house role, makes invisible content discoverable. While news-based rants build community and personality, durable content like pricing guides or technical fixes provides the long-tail traffic that challenges traditional 90-day podcast advertising models. Maintaining a back catalogue requires updating descriptions when tax thresholds or industry standards change to ensure accuracy for searchers years after the original recording date. One host admits that a panic-recorded segment with an accountant remains their most consistent source of traffic three years later. This episode passes the random Tuesday test by providing answers that remain relevant for half a decade. Next week, the team focuses on writing show notes as a pitch rather than a receipt to capture these easy wins.

Tom and Maya challenge the podcasting industry's obsession with SEO, revealing how aggressive growth tactics often alienate core audiences. Tom recounts a failed optimization year where prioritizing keyword-heavy metadata over episode preparation triggered a decline in show quality and a backlash from long-term listeners. This loyalty trap illustrates the danger of trading high-value super-fans for search-driven tourists who rarely convert into evangelists. Creators operating on limited schedules face a zero-sum game between search engine optimization and deep research. While Maya argues that search remains a vital front door for listeners seeking specific solutions like raising client rates, the math of growth favors word-of-mouth over generic charts. A local history podcast case study demonstrates how a ferocious small audience provides more stability than volatile search traffic. Low-maintenance discoverability tactics, such as transcribing back catalogues and refining feed descriptions, allow hosts to maintain the engine of growth without sacrificing the Thursday evening preparation time required for high-quality content. The discussion critiques the rise of staged social media clips, advocating instead for listener-generated highlights via PodHerd. This tool enables fans to create authentic clips with animated waveforms while the Ask the Archive feature provides AI-generated answers backed by specific audio citations. By excluding these shared answer pages from Google indexing, the system prioritizes private, high-trust recommendations over public search results. Tom and Maya conclude by previewing why an evergreen episode on sole traders continues to outperform newer recordings.

ChatGPT and Gemini are fundamentally altering the discovery landscape as conversational interfaces replace traditional search boxes. Maya and Tom explain how listeners like the hypothetical Sarah now bypass Google to ask AI assistants for specific podcast recommendations. This shift forces creators to move beyond audio files and focus on the readable text pools that these large language models ingest to determine which shows are worth suggesting. PodHerd provides a technical solution to this visibility crisis by transforming raw audio into structured, article-like transcripts with AI-generated chapters. Unlike the unformatted machine transcripts that often result in useless grey slabs of text, these structured documents allow AI assistants to cite specific moments within an episode. The Ask the Archive tool further enhances this by acting as a digital staff member that answers listener questions using direct audio citations. Creators can now verify their reach through PodHerd analytics, which track referral traffic specifically from platforms like Perplexity and ChatGPT alongside Google Search Console data. While AI middlemen risk summarizing content to the point of replacing the original play button, the human element remains a vital safeguard. Maya and Tom argue that a text summary cannot replicate the nervous tone of an expert beekeeper or the unique chemistry of a host conversation. The episode concludes with a preview of The Loyalty Trap, a forthcoming deep dive into why creators should prioritize their existing audience over the constant chase for new listeners.

Podcasters A and B illustrate the critical divide between digital ownership and platform dependency in the current media landscape. While Podcaster A secures long-term SEO equity through a dedicated domain, Podcaster B risks total loss of search rankings by redirecting traffic to Spotify and Apple. This scenario highlights how third-party rebrands or policy shifts can effectively erase a creator's digital footprint if they do not control their own web infrastructure. Technical configurations like CNAME records allow creators to point personal subdomains to hosting providers like PodHerd, ensuring that SEO credit remains with the brand rather than the service. Google Search Console serves as a vital diagnostic tool for these verified domains, revealing specific keyword impressions and click-through rates that are inaccessible on rented addresses. Effective metadata management requires a dual-title strategy that pairs creative hooks with descriptive, keyword-rich phrases to capture search intent. RSS feed descriptions in directories like Apple Podcasts must be optimized with plain-language summaries to convert browsing users into active listeners. Future-proofing content involves a shift toward directing all traffic to owned web pages rather than external app links. This strategy builds a portable archive that survives changes in hosting networks or distribution services. The next phase of this evolution centers on how conversational AI models like ChatGPT select and recommend shows to users as traditional search behavior transitions into AI-driven discovery.

Maya and Tom launch their ten-episode series How To Get Discovered by challenging the traditional reliance on word-of-mouth growth for independent creators. Maya argues that high-quality audio remains a long-term asset only if it survives the searchability gap, while Tom warns that over-optimization can distract from the core craft of podcasting. They use a beekeeping search experiment to demonstrate how niche content becomes invisible to new listeners within months of its initial RSS feed release. Apple Podcasts and Spotify face criticism for search algorithms that prioritize show titles over specific episode metadata, leaving evergreen topics like swarm season or rate-raising strategies buried. PodHerd is identified as a solution for transcribing back catalogues into structured, searchable chapters that capture targeted Google traffic. The transition from unformatted transcript walls to indexed data allows search engines to categorize specific segments, effectively turning a single audio file into multiple entry points for strangers seeking authoritative answers. Maya contends that while loyal subscribers drive retention, a second audience exists that requires technical discovery mechanisms to find the show. Tom reflects on a decade of podcasting to question whether a creator's primary duty lies with the existing community or the unreached seeker. The hosts compare search discovery to a shop front door, where a stranger’s specific question leads to a long-term relationship with the host. This series opener concludes with a technical preview of domain ownership and the role of C-NAME records in protecting a show's digital footprint.