How Responna Grew by Turning SaaS Into a Done-for-You AI Visibility Service

概览

This episode features Omer Khan interviewing Farzad Rashidi, co-founder of Responna, about how the company moved from a self-serve SaaS outreach tool into a done-for-you service that helps brands appear in AI-generated answers.

The central story is that Responna spent years plateauing because customers liked the tool but did not consistently use it. A pivotal customer conversation revealed that buyers resisted paying hundreds of dollars for software, but were willing to pay thousands for measurable outcomes.

Farzad explains how Responna used software, AI, publisher relationships, and productized service design to scale delivery without becoming a traditional agency. The discussion then shifts into a practical framework for AI visibility: understanding citations, finding look-alike publishers, publishing fresh third-party content, and treating AI answers as an evolution of SEO rather than a replacement.

分段落总结

[00:00] Opening Hook and Episode Premise

[事实] The episode opens with a story about a marketing agency CEO who tried to negotiate an $800-per-month software subscription down to $500.

[事实] That same customer later grew to spending about $65,000 to $70,000 per month after Responna shifted the conversation from software fees to outcomes.

[事实] Omer introduces Farzad Rashidi as the co-founder of Responna and frames the episode around a major business model shift.

[事实] The host says Farzad demoted his SaaS on the homepage and led with a done-for-you service.

[02:18] What Responna Does Now

[事实] Farzad describes Responna as helping brands show up in AI answers, including Google AI Overviews, ChatGPT, Claude, and similar systems.

[事实] He says Responna does track AI visibility, but the main offering is helping brands get mentioned on publisher pages that LLMs cite.

[事实] The company works with listicles, reviews, and comparison guides so that AI crawlers are more likely to encounter and recommend the client’s brand.

[推测] The positioning is deliberately outcome-oriented rather than tool-oriented, which sets up the later discussion about why the business model changed.

[03:42] Origins at Visme

[事实] Responna began as an internal tool at Visme, where Farzad was the first marketing hire.

[事实] Visme relied heavily on SEO because it was bootstrapped and had limited cash.

[事实] The internal tool helped Visme find relevant websites for backlinks, collaborations, and brand mentions.

[事实] Responna was released as a standalone product in 2019 and had reached a few hundred thousand dollars in ARR by the time Farzad previously appeared on the podcast.

[05:13] The SaaS Plateau

[事实] Responna’s growth stalled because churn caught up with new business.

[事实] Customers did not mainly cancel because the product lacked features; they canceled because they were not using it enough.

[事实] Customers often lacked the internal time or resources to do outreach, negotiate with publishers, write content, and follow through consistently.

[事实] Responna lost customers more often to agencies or freelancers than to competing software tools.

[推测] The team initially misread the problem as a product stickiness issue rather than an execution-capacity issue for customers.

[08:45] The Pivotal Agency Conversation

[事实] In early 2025, a large marketing agency contacted Responna about buying the self-serve tool.

[事实] The agency CEO tried to negotiate the software price down but suggested paying per result if Responna could generate outcomes.

[事实] Farzad realized the team could offer to do the work for the customer and charge per deliverable.

[事实] The customer started around $7,000 to $8,000 per month and later grew dramatically.

[推测] This call revealed that the customer’s price sensitivity was tied to uncertainty about effort and results, not necessarily lack of budget.

[12:06] Fear of Becoming a Services Business

[事实] Farzad says moving into services felt counterintuitive because SaaS founders are often warned not to become agencies.

[事实] His co-founder had previously run a marketing or web development agency and had experienced low margins and scaling problems.

[事实] Farzad believed AI and LLMs could automate much of the human work if Responna built the right operational assembly line.

[推测] The service model became more attractive because AI changed the cost structure that traditionally made agencies difficult to scale.

[14:45] First Manual Delivery

[事实] Responna delivered the first version of the service completely manually.

[事实] The team used a Google Sheet for the customer to specify what they needed.

[事实] An internal team member who had been building mentions and backlinks for Responna handled the customer work.

[事实] After the first deliverable, the customer placed a second order worth more than $10,000.

[16:08] Demand From Existing Customers

[事实] Responna began offering done-for-you work to existing software customers.

[事实] Farzad says almost every customer they approached wanted to get on a call.

[事实] Demo calls shifted away from interest in the self-serve product and toward pricing for the done-for-you service.

[事实] Demand outpaced Responna’s ability to fulfill orders because the back-end process was still manual.

[推测] This was the strongest product-market fit signal in the episode: customers were asking for more than the team could immediately deliver.

[18:50] From Spreadsheet to Product Layer

[事实] The original Google Sheet captured order details such as target URLs and anchor text.

[事实] Responna still used its software on the back end for outreach to publications.

[事实] The company later built a client portal, a publisher relationship portal, and a back-end system connecting the two.

[推测] The company did not abandon software; it redirected software toward making service delivery repeatable and scalable.

[20:42] Building Software Around Bottlenecks

[事实] Farzad says the move back toward software happened naturally as operational problems appeared.

[事实] Responna needed systems to manage a much larger publisher network, customer orders, onboarding, payments, and delivery.

[事实] The engineering team built tools because the company still saw itself as a software company at its core.

[事实] Farzad identifies publisher relationships and proprietary publisher data as an important moat.

[24:05] Economies of Scale and Network Advantage

[事实] Farzad says Responna grew revenue fivefold in the previous 12 months.

[事实] He says the company built around 2,500 brand mentions in the prior month, or roughly 100 per day.

[事实] Responna can negotiate differently with publishers because it brings repeat volume.

[事实] The company passes some of those volume advantages to clients through more reasonable pricing and higher-quality work.

[推测] The defensibility comes less from software alone and more from combining software, process, demand aggregation, and publisher relationships.

[26:04] AI-Native Services and Timing

[事实] Omer connects Responna’s model to the broader 2026 trend of AI-native services and “service as software.”

[事实] Farzad references a Sequoia article about software firms masquerading as services companies.

[事实] Farzad says the shift was not fully calculated and involved luck, timing, and sticking with the business long enough to encounter the opportunity.

[推测] Responna’s story fits a wider market shift, but the company discovered the model through customer pressure rather than top-down strategy.

[28:55] Advice for Founders in a Plateau

[事实] Farzad advises founders to ask existing customers what would happen if the company did the work for them.

[事实] He says founders should look for customers willing to pay, not just express interest.

[事实] He warns that services should be productized rather than endlessly customized.

[事实] Responna productized pricing, volume discounts, add-ons, and order options so work could still move through an assembly-line process.

[推测] The key lesson is not “become an agency,” but “turn repeatable customer outcomes into a structured delivery system.”

[32:20] Manual Path to AI Visibility

[事实] Farzad says Responna does not perform magic and that companies can do AI visibility work in-house.

[事实] He uses Notion and project management software as an example.

[事实] When users ask for the best project management tools, AI systems search the web, read high-authority content, compare brands, and generate recommendations.

[事实] A brand must understand which prompts, sources, listicles, reviews, and comparison pages influence those answers.

[36:04] Citation Research and Outreach Limits

[事实] Farzad says teams should run target prompts through models such as Claude, Google AI Overviews, Gemini, and ChatGPT.

[事实] The next step is identifying the sources and citation patterns those models use.

[事实] He says directly pitching cited websites often produces less than a 1% success rate.

[事实] Responna instead finds look-alike publishers with similar authority and semantically relevant keyword profiles.

[推测] The look-alike strategy expands the opportunity set beyond the exact pages already being cited.

[42:00] Fresh Content and Citation Pools

[事实] Once Responna secures a publisher, it creates a fresher content piece that follows the structure of already cited pages.

[事实] The client’s brand is featured near the top of the new content.

[事实] Farzad says LLMs are hungry for fresh content because retrieval helps them update beyond training data.

[事实] Over time, repeated third-party mentions help the brand enter the citation pool and influence the narrative.

[推测] The strategy resembles traditional skyscraper SEO adapted for AI answer citation behavior.

[44:18] Case Study and SEO Spillover

[事实] Farzad mentions Opus Clip as a case study and says the company reached number one in its niche for AI visibility.

[事实] He says this result was validated by visibility trackers such as Profound.

[事实] He also says Opus Clip added about 100,000 monthly organic visits.

[事实] Third-party brand mentions still create backlinks, which can support traditional SEO rankings.

[推测] AI visibility work can have a dual benefit: appearing in AI answers and strengthening conventional organic search.

[46:12] SEO Is Changing, Not Dead

[事实] Omer says organic traffic from Google may be declining, but SEO principles still matter.

[事实] Farzad agrees that authoritative content, links, and external validation remain important.

[事实] Farzad argues that off-page SEO is becoming more important because AI models cite many external sources.

[事实] He says it is no longer enough to rank only your own website; other sources need to recommend you too.

[48:00] Reddit’s Role in AI Citations

[事实] Farzad says Reddit is the number one cited source by count, but represents less than 5% of total citations.

[事实] He says most citations still come from editorial and other websites.

[事实] He recommends engaging on Reddit where relevant, but not relying on it as the whole AI visibility strategy.

[推测] Reddit can be useful as a social and visibility channel, but it is too easy to spam and too narrow to be a durable moat by itself.

[52:18] Lightning Round and Wrap-Up

[事实] Farzad says the startup advice he disagrees with is being afraid of services.

[事实] He recommends the book Sapiens.

[事实] He says building a business humbled him and taught him that good things take time.

[事实] He recommends Granola as a tool that saves him time by transcribing meetings from computer audio.

[事实] Outside work, he plays tennis, and listeners can find him on LinkedIn or visit responna.com.

播客点评/总结

This episode is valuable because it gives a concrete example of a SaaS company escaping a growth plateau by changing what it sold: not access to a tool, but the finished outcome customers wanted. The strongest part is the pricing contrast, where a buyer resisted a few hundred dollars in SaaS spend but accepted a much larger outcome-based engagement.

The discussion is also useful for founders trying to understand “service as software” without reducing it to vague AI-agent language. Farzad’s story shows that the model still requires process design, operational discipline, software infrastructure, and a defensible supply-side network.

The AI visibility section is practical and grounded in familiar SEO concepts: citations, third-party validation, publisher authority, fresh content, and outreach. Its limitation is that some of the strongest claims depend on Responna’s internal data and examples, so listeners should treat broad performance expectations as context-specific rather than guaranteed.

[推测] This episode is best suited for B2B SaaS founders, SEO and growth leaders, and operators who are considering productized services or AI visibility programs. It may be less useful for listeners looking for a purely technical tutorial or a step-by-step implementation checklist.