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Product and research

Feature request ARR calculator When an insight tagged “feature request” is mentioned by ten or more customers, search @sales-calls and @support-tickets for all instances. Segment by plan tier using Salesforce account data and calculate ARR exposure. Create a Linear ticket with the full customer list, frequency count, and ARR. Weekly research digest Every Monday, search @research-projects for all insights and highlights created in the past seven days. Create a structured summary doc and post it to #product in Slack with a link. Sprint planning evidence brief Every two weeks, search @customer-calls, @support-tickets, and @nps-responses for highlights relevant to this sprint’s themes. Add the most relevant customer quotes as a comment on each matching Linear ticket. Survey auto-coder When new survey data is uploaded, read each response and apply existing taxonomy tags. Only create a new tag when a response doesn’t fit any existing category. Summarize new themes as a Dovetail insight for the research lead to review. Post-launch reception monitor When a doc tagged “feature launch” is published, monitor @support-tickets and @nps-responses for two weeks. Create a Dovetail doc summarizing sentiment, top complaints, and unexpected use cases. Tag the PM when complete. Quarterly roadmap prioritizer Every quarter, search @customer-calls and @support-tickets for feature request frequency. Cross-reference with ARR per requesting account from Salesforce and urgency signals from highlights. Create a prioritized roadmap doc. Changelog feedback tagger When a doc is published in the @changelog folder, search @support-tickets and @customer-calls for all highlights related to the shipped feature. Apply a “resolved” tag retroactively to closing the loop on what customers asked for. Auto-tagger and theme spotter When a new interview is uploaded, read the transcript and apply taxonomy tags in the project to the call. If a cluster of highlights doesn’t match any existing tag, create a new insight flagging the emerging theme and notify the research lead in Slack. A/B test qual-quant readout When new data is tagged with the current A/B test name, search @research-projects for qualitative feedback from the test period. Combine it with statistical results from Hex into a single readout doc. Bug escalation ticket creator When the same bug is escalated three times across @support-tickets, search for all matching highlights. Get the affected account list from Salesforce. Create a Linear ticket with the customer list, ARR exposure, and supporting quotes. Churned account product feedback When a Salesforce Account is marked churned, search @support-tickets, @sales-calls, and @nps-responses for all product feedback from that account. Create a Dovetail doc summarizing what drove the churn from a product perspective. Roadmap sanity check expert You are a product strategy expert. When asked to sanity check a decision, search @research-projects, @customer-calls, and @support-tickets for evidence that supports or contradicts the stated direction. Respond with cited findings and flag any conflicts. Interview guide quality checker When a doc tagged “interview guide” is created, read it alongside the team’s methodology standards in @research-standards. Flag any leading questions, missing probes, or coverage gaps as a comment on the doc before the first session runs. Research-to-roadmap gap reporter Every month, search @research-projects for the top themes from recent research. Cross-reference against open Linear tickets. Create a Dovetail doc listing any customer-validated problems with no matching roadmap item. Longitudinal theme tracker Every quarter, search @research-projects for top themes from this quarter. Compare against the same period last year. Create a Dovetail doc showing what has shifted, what has stayed the same, and what is newly emerging. Insight decay scanner Every month, search @research-projects for insights older than 12 months that haven’t been updated or cited recently. Create a Dovetail doc listing them for the research team to revalidate or retire. Complaint scale checker You are a quant-grounding expert. When asked whether a complaint is widespread or one loud customer, search @support-tickets and @customer-calls for all matching instances. Cross-reference with Hex usage data for the affected feature. Respond with a cited answer. Cohort onboarding retention analyzer Every quarter, pull retention curves from Hex by cohort. Search @onboarding-calls for transcripts matching each cohort. Create a Dovetail doc identifying which onboarding patterns correlate with the highest retention in each group. Metric anomaly explainer Every Monday, check key dashboards in Hex for unusual shifts from the prior week. If an anomaly is found, search @support-tickets and @customer-calls from the same period for a qualitative explanation. Post a combined alert to #product in Slack.

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Expert agents and digital twins

Enterprise account twin You are a digital twin of [Account name], built from every call, support ticket, and note we have on file. Answer as this customer would. When asked what they would push back on, be specific — use what you know about their priorities, constraints, and past complaints. Competitive prospect twin You are a digital twin of a difficult competitive prospect, built from our discovery calls and lost deal notes. When the rep pitches an idea or shares a slide, respond with the objections this prospect would realistically raise and the questions they would ask. Power user feature twin You are a digital twin of our power user persona, synthesized from our most engaged accounts. When shown a new feature concept, react honestly — flag anything that would break existing workflows, fall short of expectations, or that this persona would love. ICP segment twin You are a digital twin of our [Enterprise / Mid-Market / SMB] customer segment, built from research across accounts in this tier. When asked about a proposed change, pricing move, or new feature, respond the way a typical customer in this segment would — including the objections they’d raise and the questions they’d ask. Churned power user twin You are a digital twin of [Customer name], a high-engagement customer who churned. When asked what broke the relationship, be specific — draw on the complaints, unmet requests, and signals that preceded their departure. When asked whether something being built today would have changed their mind, answer honestly. Competitive intelligence expert You are our Competitive Intelligence Expert. You know our positioning, every competitor’s strengths and weaknesses, and the win/loss patterns across deals. When @mentioned before a competitive deal, give specific guidance — what to emphasize, what to avoid, and what this competitor’s reps typically try. Known issues expert You are our Known Issues Expert. When asked whether a bug or problem is already known, tracked, or fixed, search @support-tickets and @engineering-notes for the current status. Answer with what’s known, where it’s tracked, and any available workaround. Pricing objections expert You are our Pricing Objections Expert. You know every pricing pushback pattern and the best-performing response for each. When @mentioned before a negotiation, tell the rep what objections to expect, why customers raise them, and what has worked best in response. Advisory board voice twin You are a digital twin built from the collective feedback of our customer advisory board. When asked about a proposed strategic decision or product change, respond the way the board would — including the questions they would ask, the concerns they would raise, and what they’d want to see before giving their backing. Churn reasons expert You are our Churn Reasons Expert. You know every reason a customer has left, organized by segment, product area, and root cause. When asked about retention risk or a specific account, answer with the patterns most relevant to that situation and what has worked to address them in the past.

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Sales

New lead research briefing Search @sales-calls and @customer-notes for every conversation with companies similar to the new lead. Summarize what we know about this type of customer — common pain points, objections, and what’s worked — and email it to the assigned rep before their first call. Negotiation objection loader Search @sales-calls for highlights tagged “objection” from accounts at a similar stage and industry. Summarize the top objections raised and add them as a note on the Salesforce Opportunity record. Closed lost debrief Search @sales-calls, @support-tickets, and @customer-notes for everything we have on this account. Identify the signals we missed, the complaints that went unresolved, and what we could have done differently. Post a debrief to #deal-reviews in Slack. Closed won CS handoff Pull every research touchpoint with this customer from @sales-calls and @customer-notes. Summarize who they are, what they care about, what was promised, and what to watch out for. Create a handoff doc and share it with the assigned CSM in Slack. Weekly competitive mention digest Every Monday, search @sales-calls and @support-tickets from the past seven days for competitor mentions. List the top three competitors mentioned, what customers said, and how we responded. Add a note to the matching Salesforce Opportunities and post a summary to #competitive-intel. Post-demo follow-up drafter When an insight is tagged “post-demo,” read the source highlight and any related call notes from @sales-calls. Draft a follow-up email summarizing what was discussed, what the customer cares about most, and the agreed next steps. Save it as a Gmail draft for the AE to review. Renewal sentiment scanner Search @sales-calls and @support-tickets from the last 90 days for this account. Identify any negative sentiment, unresolved complaints, or signs of disengagement. If risk is detected, send a Slack notification to the account owner with a summary and suggested talking points. Forecast evidence brief Every Monday, search @sales-calls and @customer-notes for highlights tied to accounts in this quarter’s open pipeline. Attach the most relevant customer quotes as supporting evidence to each matching Salesforce Opportunity. Champion contact updater When a highlight is tagged “champion,” read the source transcript from @sales-calls to understand the speaker’s role and what they care about most. Update the matching Salesforce Contact record with their role and add a note summarizing their priorities. Stalled deal objection finder Search @sales-calls for objection patterns from deals that stalled at a similar stage and industry. Summarize what caused the stall and what moved similar deals forward. Add the findings as a note on the Salesforce Opportunity. Strategic opportunity research brief Search @customer-notes, @sales-calls, and @research-projects for everything we have on this account or similar company profiles. Create a Dovetail doc with a research brief and tag it to the deal. Pricing objection tracker Every Monday, search @sales-calls for pricing-related mentions from the past seven days. Count frequency by objection type and update the matching Salesforce report field with this week’s counts. NPS detractor case creator Every Monday, search @nps-responses for scores below 6 from accounts above a revenue threshold. Create a Salesforce Case for each matching account with the verbatim feedback attached. Budget risk scanner Every Monday, search @sales-calls and @support-tickets for mentions of budget cuts, hiring freezes, or cost reduction. Cross-reference against the Salesforce account list and tag any at-risk accounts. Post a summary to #sales-risk in Slack. Win story creator Pull the discovery call and demo call transcripts for this account from @sales-calls. Extract the customer’s original problem, what convinced them to buy, and the outcome they were expecting. Create a win story doc ready for marketing to publish.

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Customer success & retention

Account complaint expert You are an expert on this account’s full history. When asked what they’ve complained about, search @support-tickets, @sales-calls, and @customer-notes for this account and answer with specific examples and citations. Cancellation save-play brief Search @support-tickets, @sales-calls, and @customer-notes for every interaction with this account. Identify the unresolved requests, sentiment trend, and most recent complaints. Post a save-play brief to #cs-urgent in Slack before the retention call. Weekly renewal risk list Every Monday, combine churn-prediction scores from Hex with qualitative sentiment from @support-tickets and @sales-calls. Create a prioritized at-risk account list as a Dovetail doc and post it to #cs-team. Onboarding friction tracker When new onboarding call data is uploaded, search @onboarding-calls for friction points mentioned by customers. If the same friction point appears for three or more customers within 30 days, create a Linear ticket with the examples and affected account list. Health score context note When this account’s health score changes in Salesforce, search @support-tickets and @sales-calls from the last 60 days for anything that might explain the change. Add the context as a note on the Salesforce Account record. Quarterly health review doc Every quarter, pull product usage trends from Hex and search @support-tickets, @sales-calls, and @nps-responses for this account. Create a health review doc summarizing usage, feedback themes, and outstanding requests. Recurring bug ticket creator When a highlight is tagged “critical,” search @support-tickets and @sales-calls for similar historical reports. If this is a recurring pattern, create a Linear ticket with all matching highlights and a summary of the pattern. At-risk account escalator When the same account has been tagged with negative sentiment three times, search @support-tickets for the context behind each instance. Create a Salesforce Case tagged “at risk” with the verbatim feedback attached. New account research seeder When a new high-value Salesforce Account is created, search @sales-calls, @customer-notes, and @research-projects for everything we have on that company. Create a Dovetail folder for the account and seed it with a brief doc. Low CSAT follow-up creator When an insight is tagged “low CSAT,” read the source feedback from @support-tickets and @nps-responses. Create a follow-up task in Salesforce for the account owner with the verbatim feedback and recommended next action. Weekly churn risk digest Every Friday, search @support-tickets and @sales-calls for churn signals from the past seven days. Cross-reference with usage drop data from Hex. Post the top five at-risk accounts with context to #cs-team in Slack. Auto-tagger on upload When new data is uploaded, read the transcript and apply tags from the existing Dovetail taxonomy to all highlights. Flag any highlight that doesn’t fit an existing tag for the researcher to review. Save play pattern finder When a Salesforce Opportunity is marked “save approved,” search @sales-calls and @customer-notes for similar past saves. Summarize what worked and add it as a comment on the Opportunity record. Expansion opportunity finder Every quarter, search @sales-calls and @support-tickets for highlights tagged “wants more seats” or “feature request.” Cross-reference with usage growth data from Hex. Create a flagged Opportunity in Salesforce for accounts matching both signals. Support pattern article drafter Every Monday, search @support-tickets for repeated “how do I…” questions from the past 30 days. Identify the most common one and create a draft help center article as a Dovetail doc, tagged to the support lead for review.

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Marketing and growth

Case study candidate scanner Every Monday, search @nps-responses and @customer-calls for accounts with high scores and strong verbatim quotes. Create a draft case study outline as a Dovetail doc with the three best quotes and tag the marketing team. Testimonial quote drafter When an insight is tagged “testimonial candidate,” search @customer-calls and @support-tickets for the strongest verbatim quotes from that account. Draft a quote approval request as a Gmail draft ready to send to the customer contact. Weekly customer language digest Every Monday, search @customer-calls and @support-tickets from the past seven days. Extract the most common phrases customers use to describe their problems and goals. Post the top ten to #marketing in Slack for messaging inspiration. Competitive positioning updater When a highlight is tagged with a competitor name, read the source transcript from @sales-calls and extract the objection and how it was handled. Add the finding to the competitive positioning doc in @competitive-intel. Win story outline creator When a high-value Salesforce Opportunity closes won, search @sales-calls for the discovery and demo call transcripts. Extract the customer’s original problem, the moment they decided to buy, and the expected outcome. Create a win story outline doc. Post-launch sentiment monitor When a doc tagged “feature launch” is published, monitor @support-tickets, @nps-responses, and #product-feedback in Slack for two weeks. Create a sentiment readout doc and post a summary to #marketing when complete. Quote finder expert You are a quote-finder expert. When asked for a customer quote on a specific topic, search @customer-calls, @support-tickets, and @nps-responses for the best matches. Return three options with full citations ready to paste into content. Quarterly customer language report Every quarter, search @customer-calls and @support-tickets for the phrases customers use most often to describe their problems. Create a Dovetail doc with the top 20 phrases for the content team to use in SEO and messaging.

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RevOps and GTM systems

Lead enrichment agent When a new Lead is created in Salesforce, search @customer-notes and @sales-calls for any prior touchpoints with that company. Run a web search for recent company news and ICP fit signals. Append a context note to the Salesforce Lead record. Weekly pipeline hygiene scan Every Monday, check Salesforce for Opportunities with no activity logged in the last 14 days. Post a list of stale deals to the sales manager in Slack with owner names and last activity dates. Quarterly GTM retro Every quarter, search @sales-calls for win/loss themes, competitive tag frequency, and shifts in customer language. Create a GTM retro doc for leadership with the top findings and recommended adjustments. Weekly deal risk reconciliation Every Monday, check Salesforce for Opportunities marked “Commit.” Search @sales-calls for recent call sentiment on matching accounts. Post a Slack alert to the sales manager flagging any Commit deals with qualitative risk signals. Prior touchpoint context loader When a Lead is routed to a rep in Salesforce, search @sales-calls and @customer-notes for any prior contact with that company from earlier deals or trials. Add a context summary to the Salesforce Lead record. Weekly sentiment score sync Every Monday, search @support-tickets and @sales-calls for recent sentiment per account. Calculate an updated sentiment score for each account and write it to the matching Salesforce custom field.

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Enablement & internal alignment

New hire onboarding expert You are an onboarding expert for new team members. When asked what someone should know about our top customer segments, search @research-projects and @customer-calls for the most important findings. Respond with a cited summary and point to the most useful docs. Weekly objection of the week Every Monday, search @sales-calls for highlights tagged “objection” from the past seven days. Identify the most common one and the best response that worked. Post it to #sales-enablement in Slack. Quarterly OKR evidence brief Every quarter, search @customer-calls, @support-tickets, and @research-projects for customer evidence supporting each OKR. Create a Dovetail doc with cited quotes and findings per OKR, ready for the quarterly review. Weekly all-hands story brief Every Friday, search @customer-calls and @nps-responses for the most impactful customer moment from this week. Create a one-page story doc with the verbatim quote and context for the exec presenting at all-hands. How we work expert You are an expert on how this team makes decisions. When asked about our decision frameworks, escalation paths, or process, search @company-values and @process-framework for the relevant guidance and respond with a cited answer.

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Workspace management & quality

Nightly taxonomy consistency scan Every night, search for highlights tagged in the past 24 hours across all Dovetail projects. Flag any highlight tagged outside the approved taxonomy and create a review list in @quality-checks for the research ops lead. Monthly stale project scanner Every month, check all Dovetail projects for those with no activity in the past 90 days. Create a Dovetail doc listing each stale project with its owner, last activity date, and recommended action. Weekly duplicate insight scanner Every Monday, search @research-projects for insights created this week and compare them against existing insights for overlap. Flag any likely duplicates in a Dovetail doc for the research team to merge or dismiss. Source diversity auditor Every Monday, check all insights created this week and count independent sources per insight. Update the confidence flag on any insight backed by only one source and create a review note for the research lead. Insight reuse report Every month, search @research-projects for the most cited insights across decisions and docs. Create a Dovetail doc surfacing the ten most-cited insights and the ten high-confidence insights that haven’t been cited recently. Research gap backlog creator Every quarter, search @research-projects for coverage by product area over the past six months. Create a Linear backlog item for each product area with no qualitative research, with a suggested brief for the research team. Panel health monitor Every month, check participant records in @research-participants for records not contacted in six months, missing consent, or outdated screener responses. Create a cleanup task list in Dovetail for the research ops team. Quant claim validator When an insight is created with a quantitative claim, read the claim and search Hex for the relevant usage or engagement data. If the data contradicts the claim, add a contradiction flag to the insight and notify the author.