Merciv growth playbook

Offer each qualified prospect one test: share a finished study (the data and the final report) under NDA, and within 48 hours Merciv returns its own analysis with page-level citations, side by side with their conclusions, plus anything their report missed.

A VP of Consumer Insights can judge accuracy on work they already know the answer to, which removes the biggest objection (is it right?) before IT and legal review starts.

Subject: Send us one study you have already finished

Hi {first name},

The fastest way to judge Merciv is on work you already know the answer to. Share one finished study (the data and your final report) under NDA, and in 48 hours we will send back our analysis with page-level citations, side by side with your conclusions.

Welch's did this with about ten past reports before trusting us. Your data is deleted afterwards, and we never train on it.

Worth a try?

{name}

• Prospects will not share data before a contract

  Offer a public-data version first, then the private-data test.

• The result differs from the client's report

  Show the reasoning and sources; a well-argued difference is also valuable.

• HiringProduct Marketing Manager (first dedicated PMM): the buyer is "a VP of Consumer Insights" at an enterprise consumer company; the sale is "multi-stakeholder, long-cycle, and built on trust — we're asking teams to bring their proprietary data into our platform"; own the answer to "why not just use ChatGPT?", case studies, comparison content, competitor comparisons and win/loss; accountable for conversion to pipeline.Source
• Your websiteWelch's story (October 2026): a three-person insights team runs up to seven projects at once; a question-by-question survey error log in about 15 minutes; Merciv reached the same conclusions the team had reached on about ten past reports; partner-reviewed analysis signed off in days rather than weeks.Source
• Your websiteHomepage: "The compounding consumer intelligence system", connecting internal data, syndicated research and the open web; no customers named (testimonials by role only); proof figures such as "~$12M overstock prevented", "98% faster time to answer", "87% lower research cost" and "~40x more citations per query than general AI"; integrations with Nielsen, Circana, SPINS, Numerator and NIQ; agents named Unmet Needs, Line Review Prep and Dupe Watch; SOC 2 Type II and zero training on customer data; a "Celebrity Brands" signal report banner.Source

Ask the customers behind the homepage figures for permission to be named, starting with Welch's, and replace role-only testimonials with named people, companies and one number each.

The PMM post asks for proof that convinces rigorous buyers. A named peer is the strongest proof in a trust-based sale.

• Enterprise customers refuse to be named

  Use named people without logos, or industry and size with exact numbers.

• Your websiteHomepage: "The compounding consumer intelligence system", connecting internal data, syndicated research and the open web; no customers named (testimonials by role only); proof figures such as "~$12M overstock prevented", "98% faster time to answer", "87% lower research cost" and "~40x more citations per query than general AI"; integrations with Nielsen, Circana, SPINS, Numerator and NIQ; agents named Unmet Needs, Line Review Prep and Dupe Watch; SOC 2 Type II and zero training on customer data; a "Celebrity Brands" signal report banner.Source
• Your websiteWelch's story (October 2026): a three-person insights team runs up to seven projects at once; a question-by-question survey error log in about 15 minutes; Merciv reached the same conclusions the team had reached on about ten past reports; partner-reviewed analysis signed off in days rather than weeks.Source
• HiringProduct Marketing Manager (first dedicated PMM): the buyer is "a VP of Consumer Insights" at an enterprise consumer company; the sale is "multi-stakeholder, long-cycle, and built on trust — we're asking teams to bring their proprietary data into our platform"; own the answer to "why not just use ChatGPT?", case studies, comparison content, competitor comparisons and win/loss; accountable for conversion to pipeline.Source

Publish one signal report a month on a cultural moment (celebrity brands, a viral product, a dupe trend), cut into a LinkedIn post, a 60-second video with the Marketing Manager on camera, and a gated full report for insights leaders.

Original consumer data on a topic people already talk about gets shared, and it shows the product working without a demo.

• Reads as click bait

  Lead with the data and the method, as the job post asks.

• HiringMarketing Manager: build "a content flywheel" across LinkedIn, TikTok, Instagram and X; write, shoot and edit short-form video and appear on camera; run paid tests on LinkedIn, Meta and Google; a "data-led editorial voice" on retail trends and cultural moments, "not slop or click bait"; measured on clicks, conversions and qualified leads.Source
• Your websiteHomepage: "The compounding consumer intelligence system", connecting internal data, syndicated research and the open web; no customers named (testimonials by role only); proof figures such as "~$12M overstock prevented", "98% faster time to answer", "87% lower research cost" and "~40x more citations per query than general AI"; integrations with Nielsen, Circana, SPINS, Numerator and NIQ; agents named Unmet Needs, Line Review Prep and Dupe Watch; SOC 2 Type II and zero training on customer data; a "Celebrity Brands" signal report banner.Source
• Search resultsSite scan: 23 comparison pages (ChatGPT, Claude and Copilot alternatives, Brandwatch, Sprinklr, Quid, Zappi, YouGov, GWI, synthetic audiences, build vs buy), about 175 blog posts, 5 case studies and 7 solution pages (insights teams, data teams, brand marketing); the security-header check grades the site F (Mozilla Observatory C).Source

Publish ten real insights questions, the exact prompts, answers from ChatGPT, Claude and Merciv, the number of cited sources and whether each claim is supported, with the method so anyone can rerun it.

Generic AI is the most common alternative a buyer considers. A test they can reproduce turns the claim into evidence, and the compare pages can link to it.

• General AI improves and closes the gap

  Rerun quarterly and show the trend honestly.

• HiringProduct Marketing Manager (first dedicated PMM): the buyer is "a VP of Consumer Insights" at an enterprise consumer company; the sale is "multi-stakeholder, long-cycle, and built on trust — we're asking teams to bring their proprietary data into our platform"; own the answer to "why not just use ChatGPT?", case studies, comparison content, competitor comparisons and win/loss; accountable for conversion to pipeline.Source
• Your websiteHomepage: "The compounding consumer intelligence system", connecting internal data, syndicated research and the open web; no customers named (testimonials by role only); proof figures such as "~$12M overstock prevented", "98% faster time to answer", "87% lower research cost" and "~40x more citations per query than general AI"; integrations with Nielsen, Circana, SPINS, Numerator and NIQ; agents named Unmet Needs, Line Review Prep and Dupe Watch; SOC 2 Type II and zero training on customer data; a "Celebrity Brands" signal report banner.Source
• Search resultsSite scan: 23 comparison pages (ChatGPT, Claude and Copilot alternatives, Brandwatch, Sprinklr, Quid, Zappi, YouGov, GWI, synthetic audiences, build vs buy), about 175 blog posts, 5 case studies and 7 solution pages (insights teams, data teams, brand marketing); the security-header check grades the site F (Mozilla Observatory C).Source

Fix the missing security headers, then publish a trust pack: SOC 2 Type II report on request, data flow diagram, deletion process, retention terms, subprocessors and a filled-in standard security questionnaire.

In a multi-stakeholder sale, IT and legal can stall a deal the insights team wants. A ready pack shortens that stage.

• Publishing details aids attackers

  Keep sensitive detail behind an NDA.

• HiringProduct Marketing Manager (first dedicated PMM): the buyer is "a VP of Consumer Insights" at an enterprise consumer company; the sale is "multi-stakeholder, long-cycle, and built on trust — we're asking teams to bring their proprietary data into our platform"; own the answer to "why not just use ChatGPT?", case studies, comparison content, competitor comparisons and win/loss; accountable for conversion to pipeline.Source
• Your websiteHomepage: "The compounding consumer intelligence system", connecting internal data, syndicated research and the open web; no customers named (testimonials by role only); proof figures such as "~$12M overstock prevented", "98% faster time to answer", "87% lower research cost" and "~40x more citations per query than general AI"; integrations with Nielsen, Circana, SPINS, Numerator and NIQ; agents named Unmet Needs, Line Review Prep and Dupe Watch; SOC 2 Type II and zero training on customer data; a "Celebrity Brands" signal report banner.Source
• Search resultsSite scan: 23 comparison pages (ChatGPT, Claude and Copilot alternatives, Brandwatch, Sprinklr, Quid, Zappi, YouGov, GWI, synthetic audiences, build vs buy), about 175 blog posts, 5 case studies and 7 solution pages (insights teams, data teams, brand marketing); the security-header check grades the site F (Mozilla Observatory C).Source

Build a limited public tool: enter a brand or product, get the top dupes mentioned on TikTok, Reddit and reviews in the last 30 days with sources, and a prompt to see the full analysis in a demo.

A free tool on a topic brands care about brings in the right buyers by name, and each lookup shows the product's quality before a sales call.

• Brands dislike being shown as copied

  Show results only to the person searching, never a public list.

• Your websiteHomepage: "The compounding consumer intelligence system", connecting internal data, syndicated research and the open web; no customers named (testimonials by role only); proof figures such as "~$12M overstock prevented", "98% faster time to answer", "87% lower research cost" and "~40x more citations per query than general AI"; integrations with Nielsen, Circana, SPINS, Numerator and NIQ; agents named Unmet Needs, Line Review Prep and Dupe Watch; SOC 2 Type II and zero training on customer data; a "Celebrity Brands" signal report banner.Source
• HiringMarketing Manager: build "a content flywheel" across LinkedIn, TikTok, Instagram and X; write, shoot and edit short-form video and appear on camera; run paid tests on LinkedIn, Meta and Google; a "data-led editorial voice" on retail trends and cultural moments, "not slop or click bait"; measured on clicks, conversions and qualified leads.Source

Build a list of 500 consumer and retail companies, target insights, brand and data leaders there, and promote the best-performing organic posts and signal reports as ads, measured on target-account engagement and meetings.

The audience is small and identifiable, so account-targeted ads waste little, and promoting proven posts lowers the creative risk.

• Small audiences get expensive

  Cap frequency and rotate creative.

• #3 Turn the Celebrity Brands signal report into a monthly "signal drop" with short video

• HiringMarketing Manager: build "a content flywheel" across LinkedIn, TikTok, Instagram and X; write, shoot and edit short-form video and appear on camera; run paid tests on LinkedIn, Meta and Google; a "data-led editorial voice" on retail trends and cultural moments, "not slop or click bait"; measured on clicks, conversions and qualified leads.Source
• HiringProduct Marketing Manager (first dedicated PMM): the buyer is "a VP of Consumer Insights" at an enterprise consumer company; the sale is "multi-stakeholder, long-cycle, and built on trust — we're asking teams to bring their proprietary data into our platform"; own the answer to "why not just use ChatGPT?", case studies, comparison content, competitor comparisons and win/loss; accountable for conversion to pipeline.Source

Approach the partner teams at two data providers with a joint webinar and a one-pager showing their data analyzed alongside internal research and open-web signal, plus a listing in their partner directories.

A data provider's introduction reaches insights leaders who already pay for data and trust the provider.

• Data licensing limits what can be shown

  Use sample data and confirm terms with each provider.

• Your websiteHomepage: "The compounding consumer intelligence system", connecting internal data, syndicated research and the open web; no customers named (testimonials by role only); proof figures such as "~$12M overstock prevented", "98% faster time to answer", "87% lower research cost" and "~40x more citations per query than general AI"; integrations with Nielsen, Circana, SPINS, Numerator and NIQ; agents named Unmet Needs, Line Review Prep and Dupe Watch; SOC 2 Type II and zero training on customer data; a "Celebrity Brands" signal report banner.Source
• HiringProduct Marketing Manager (first dedicated PMM): the buyer is "a VP of Consumer Insights" at an enterprise consumer company; the sale is "multi-stakeholder, long-cycle, and built on trust — we're asking teams to bring their proprietary data into our platform"; own the answer to "why not just use ChatGPT?", case studies, comparison content, competitor comparisons and win/loss; accountable for conversion to pipeline.Source

Interview every won and lost deal within two weeks, log the reasons, and turn them into one competitor comparison per competitor with the objections heard and the proof that worked.

In a long sale, small messaging fixes compound. Recorded reasons replace guesses about why deals stall.

• Lost buyers will not talk

  Offer a short call and a summary of what Merciv learned.

• HiringProduct Marketing Manager (first dedicated PMM): the buyer is "a VP of Consumer Insights" at an enterprise consumer company; the sale is "multi-stakeholder, long-cycle, and built on trust — we're asking teams to bring their proprietary data into our platform"; own the answer to "why not just use ChatGPT?", case studies, comparison content, competitor comparisons and win/loss; accountable for conversion to pipeline.Source
• Search resultsSite scan: 23 comparison pages (ChatGPT, Claude and Copilot alternatives, Brandwatch, Sprinklr, Quid, Zappi, YouGov, GWI, synthetic audiences, build vs buy), about 175 blog posts, 5 case studies and 7 solution pages (insights teams, data teams, brand marketing); the security-header check grades the site F (Mozilla Observatory C).Source

Host a dinner for 10 to 12 insights leaders each month in New York and around the main insights conferences, with one customer speaking about how their team works now, and no pitch.

Senior buyers trust peers more than ads, and a dinner produces several warm conversations at once.

• Low acceptance

  Lead with the speaker and keep it small.

• HiringProduct Marketing Manager (first dedicated PMM): the buyer is "a VP of Consumer Insights" at an enterprise consumer company; the sale is "multi-stakeholder, long-cycle, and built on trust — we're asking teams to bring their proprietary data into our platform"; own the answer to "why not just use ChatGPT?", case studies, comparison content, competitor comparisons and win/loss; accountable for conversion to pipeline.Source
• HiringCareers board: 7 open roles in New York, 5 in engineering (agentic intelligence, agentic infrastructure, AI platform, frontend, DevOps) and 2 in go-to-market (Product Marketing Manager and Marketing Manager); no sales roles open.Source
• Your websiteWelch's story (October 2026): a three-person insights team runs up to seven projects at once; a question-by-question survey error log in about 15 minutes; Merciv reached the same conclusions the team had reached on about ten past reports; partner-reviewed analysis signed off in days rather than weeks.Source

Publish a page per agent with what question it answers, a worked example on a public brand using open-web data, the time it takes, and a demo form.

Buyers search for the job, not the platform. Agent pages answer specific searches and give sales a link per use case.

• Examples on real brands draw complaints

  Use public data and neutral wording.

• Your websiteHomepage: "The compounding consumer intelligence system", connecting internal data, syndicated research and the open web; no customers named (testimonials by role only); proof figures such as "~$12M overstock prevented", "98% faster time to answer", "87% lower research cost" and "~40x more citations per query than general AI"; integrations with Nielsen, Circana, SPINS, Numerator and NIQ; agents named Unmet Needs, Line Review Prep and Dupe Watch; SOC 2 Type II and zero training on customer data; a "Celebrity Brands" signal report banner.Source
• Search resultsSite scan: 23 comparison pages (ChatGPT, Claude and Copilot alternatives, Brandwatch, Sprinklr, Quid, Zappi, YouGov, GWI, synthetic audiences, build vs buy), about 175 blog posts, 5 case studies and 7 solution pages (insights teams, data teams, brand marketing); the security-header check grades the site F (Mozilla Observatory C).Source
• HiringProduct Marketing Manager (first dedicated PMM): the buyer is "a VP of Consumer Insights" at an enterprise consumer company; the sale is "multi-stakeholder, long-cycle, and built on trust — we're asking teams to bring their proprietary data into our platform"; own the answer to "why not just use ChatGPT?", case studies, comparison content, competitor comparisons and win/loss; accountable for conversion to pipeline.Source

Before each major retailer's review window, run a campaign to brand and category teams: a checklist of what buyers ask, a sample prep pack on a public category, and an offer to prepare one pack for their next review.

Timing marketing to a deadline the buyer already has makes the offer urgent and the value concrete.

• Calendars vary by retailer and category

  Confirm windows with customers before each campaign.

• Your websiteHomepage: "The compounding consumer intelligence system", connecting internal data, syndicated research and the open web; no customers named (testimonials by role only); proof figures such as "~$12M overstock prevented", "98% faster time to answer", "87% lower research cost" and "~40x more citations per query than general AI"; integrations with Nielsen, Circana, SPINS, Numerator and NIQ; agents named Unmet Needs, Line Review Prep and Dupe Watch; SOC 2 Type II and zero training on customer data; a "Celebrity Brands" signal report banner.Source
• HiringMarketing Manager: build "a content flywheel" across LinkedIn, TikTok, Instagram and X; write, shoot and edit short-form video and appear on camera; run paid tests on LinkedIn, Meta and Google; a "data-led editorial voice" on retail trends and cultural moments, "not slop or click bait"; measured on clicks, conversions and qualified leads.Source

Build a kit the champion can forward: a one-page business case with a cost calculator (studies a year, agency spend, hours), the trust pack, a pilot plan and an executive summary slide.

The champion has to sell internally to people Merciv never meets. A ready business case turns their enthusiasm into a budget line.

• Calculators overstate savings

  Use the customer's own inputs and show the range.

• #5 A trust pack for the IT and legal reviewers, and fix the site's F security-header grade

• HiringProduct Marketing Manager (first dedicated PMM): the buyer is "a VP of Consumer Insights" at an enterprise consumer company; the sale is "multi-stakeholder, long-cycle, and built on trust — we're asking teams to bring their proprietary data into our platform"; own the answer to "why not just use ChatGPT?", case studies, comparison content, competitor comparisons and win/loss; accountable for conversion to pipeline.Source
• Your websiteHomepage: "The compounding consumer intelligence system", connecting internal data, syndicated research and the open web; no customers named (testimonials by role only); proof figures such as "~$12M overstock prevented", "98% faster time to answer", "87% lower research cost" and "~40x more citations per query than general AI"; integrations with Nielsen, Circana, SPINS, Numerator and NIQ; agents named Unmet Needs, Line Review Prep and Dupe Watch; SOC 2 Type II and zero training on customer data; a "Celebrity Brands" signal report banner.Source
• Your websiteWelch's story (October 2026): a three-person insights team runs up to seven projects at once; a question-by-question survey error log in about 15 minutes; Merciv reached the same conclusions the team had reached on about ten past reports; partner-reviewed analysis signed off in days rather than weeks.Source

For each customer, map the brand, data and innovation teams, share a short internal case study from the insights team, and offer the next team a two-week trial on their own questions.

Expansion inside an account uses trust that already exists, so the second sale skips most of the long first cycle.

• Champions do not want to share

  Make the champion the hero of the internal story.

• Search resultsSite scan: 23 comparison pages (ChatGPT, Claude and Copilot alternatives, Brandwatch, Sprinklr, Quid, Zappi, YouGov, GWI, synthetic audiences, build vs buy), about 175 blog posts, 5 case studies and 7 solution pages (insights teams, data teams, brand marketing); the security-header check grades the site F (Mozilla Observatory C).Source
• HiringProduct Marketing Manager (first dedicated PMM): the buyer is "a VP of Consumer Insights" at an enterprise consumer company; the sale is "multi-stakeholder, long-cycle, and built on trust — we're asking teams to bring their proprietary data into our platform"; own the answer to "why not just use ChatGPT?", case studies, comparison content, competitor comparisons and win/loss; accountable for conversion to pipeline.Source
• Your websiteWelch's story (October 2026): a three-person insights team runs up to seven projects at once; a question-by-question survey error log in about 15 minutes; Merciv reached the same conclusions the team had reached on about ten past reports; partner-reviewed analysis signed off in days rather than weeks.Source

Offer a partner plan to three mid-size research agencies: use Merciv on client projects, co-brand the deliverables, and introduce Merciv to clients who want the platform in-house.

Agencies bring many client relationships at once, and agency use builds familiarity before a direct sale.

• Channel conflict with direct sales

  Agree account ownership in writing.

• Your websiteWelch's story (October 2026): a three-person insights team runs up to seven projects at once; a question-by-question survey error log in about 15 minutes; Merciv reached the same conclusions the team had reached on about ten past reports; partner-reviewed analysis signed off in days rather than weeks.Source
• HiringProduct Marketing Manager (first dedicated PMM): the buyer is "a VP of Consumer Insights" at an enterprise consumer company; the sale is "multi-stakeholder, long-cycle, and built on trust — we're asking teams to bring their proprietary data into our platform"; own the answer to "why not just use ChatGPT?", case studies, comparison content, competitor comparisons and win/loss; accountable for conversion to pipeline.Source

Package a two-week consumer diligence report (brand health, unmet needs, dupes, review sentiment) with a per-deal price, and sell it to consumer-focused PE funds and their portfolio companies.

Funds run many deals a year, decide fast, and can introduce Merciv to every portfolio brand afterwards.

• Diligence timelines are tight

  Set a fixed scope and staff a dedicated analyst.

• Your websiteHomepage: "The compounding consumer intelligence system", connecting internal data, syndicated research and the open web; no customers named (testimonials by role only); proof figures such as "~$12M overstock prevented", "98% faster time to answer", "87% lower research cost" and "~40x more citations per query than general AI"; integrations with Nielsen, Circana, SPINS, Numerator and NIQ; agents named Unmet Needs, Line Review Prep and Dupe Watch; SOC 2 Type II and zero training on customer data; a "Celebrity Brands" signal report banner.Source
• Search resultsMerciv came out of stealth on January 15, 2026 with $14M in seed funding led by AI x IA (a joint venture of Off Road Capital and Commonwealth Asset Management), after about two years working with Fortune 500 clients; co-founder and CEO Shaia Erlbaum.Source

Publish a quarterly index of the top unmet needs in ten categories (snacks, beverages, beauty, apparel and so on), with the method, sample sources and a briefing for each category's leading brands.

Original, recurring data builds a brand with skeptical buyers and gives the CEO a reason to contact every target account each quarter.

• Findings are obvious

  Publish only needs the method ranks high and the press has not covered.

• #3 Turn the Celebrity Brands signal report into a monthly "signal drop" with short video

• Your websiteHomepage: "The compounding consumer intelligence system", connecting internal data, syndicated research and the open web; no customers named (testimonials by role only); proof figures such as "~$12M overstock prevented", "98% faster time to answer", "87% lower research cost" and "~40x more citations per query than general AI"; integrations with Nielsen, Circana, SPINS, Numerator and NIQ; agents named Unmet Needs, Line Review Prep and Dupe Watch; SOC 2 Type II and zero training on customer data; a "Celebrity Brands" signal report banner.Source
• HiringMarketing Manager: build "a content flywheel" across LinkedIn, TikTok, Instagram and X; write, shoot and edit short-form video and appear on camera; run paid tests on LinkedIn, Meta and Google; a "data-led editorial voice" on retail trends and cultural moments, "not slop or click bait"; measured on clicks, conversions and qualified leads.Source

Build a connector for Snowflake and Databricks so customers can bring internal data without moving it, and list Merciv on both marketplaces for purchase against committed spend.

It answers the data-security objection (the data stays in the customer's environment) and opens a buying path that skips new-vendor procurement.

• Engineering time competes with the core product

  Build only after demand is confirmed.

• Search resultsSite scan: 23 comparison pages (ChatGPT, Claude and Copilot alternatives, Brandwatch, Sprinklr, Quid, Zappi, YouGov, GWI, synthetic audiences, build vs buy), about 175 blog posts, 5 case studies and 7 solution pages (insights teams, data teams, brand marketing); the security-header check grades the site F (Mozilla Observatory C).Source
• HiringProduct Marketing Manager (first dedicated PMM): the buyer is "a VP of Consumer Insights" at an enterprise consumer company; the sale is "multi-stakeholder, long-cycle, and built on trust — we're asking teams to bring their proprietary data into our platform"; own the answer to "why not just use ChatGPT?", case studies, comparison content, competitor comparisons and win/loss; accountable for conversion to pipeline.Source
• HiringCareers board: 7 open roles in New York, 5 in engineering (agentic intelligence, agentic infrastructure, AI platform, frontend, DevOps) and 2 in go-to-market (Product Marketing Manager and Marketing Manager); no sales roles open.Source

Package Line Review Prep as a sales-team product with a per-meeting or per-seat price, and pilot it with the account team at one existing customer.

Sales teams have budget tied to revenue and clear moments of need, and they bring the insights team's platform into more meetings.

• Confusion over who owns the tool

  Agree with the insights champion first.

• #12 Campaigns timed to retailer line review seasons, built on the Line Review Prep agent

• Your websiteHomepage: "The compounding consumer intelligence system", connecting internal data, syndicated research and the open web; no customers named (testimonials by role only); proof figures such as "~$12M overstock prevented", "98% faster time to answer", "87% lower research cost" and "~40x more citations per query than general AI"; integrations with Nielsen, Circana, SPINS, Numerator and NIQ; agents named Unmet Needs, Line Review Prep and Dupe Watch; SOC 2 Type II and zero training on customer data; a "Celebrity Brands" signal report banner.Source
• HiringProduct Marketing Manager (first dedicated PMM): the buyer is "a VP of Consumer Insights" at an enterprise consumer company; the sale is "multi-stakeholder, long-cycle, and built on trust — we're asking teams to bring their proprietary data into our platform"; own the answer to "why not just use ChatGPT?", case studies, comparison content, competitor comparisons and win/loss; accountable for conversion to pipeline.Source

Create a short free course (five lessons: sourcing, citations, survey checks, synthesis, presenting) with exercises on public data in Merciv, and a certificate.

Education reaches buyers before they are in market, and each learner tries the product on real tasks.

• Low completion

  Keep lessons under ten minutes.

• HiringProduct Marketing Manager (first dedicated PMM): the buyer is "a VP of Consumer Insights" at an enterprise consumer company; the sale is "multi-stakeholder, long-cycle, and built on trust — we're asking teams to bring their proprietary data into our platform"; own the answer to "why not just use ChatGPT?", case studies, comparison content, competitor comparisons and win/loss; accountable for conversion to pipeline.Source
• Your websiteWelch's story (October 2026): a three-person insights team runs up to seven projects at once; a question-by-question survey error log in about 15 minutes; Merciv reached the same conclusions the team had reached on about ten past reports; partner-reviewed analysis signed off in days rather than weeks.Source

Sponsor two issues each of three insights-industry newsletters, offering the latest signal report, and compare cost per target-account download with LinkedIn ads.

Newsletters reach the buyer in a trusted setting at a lower cost than broad ads.

• Low response

  Test one issue before committing.

• #3 Turn the Celebrity Brands signal report into a monthly "signal drop" with short video

• HiringMarketing Manager: build "a content flywheel" across LinkedIn, TikTok, Instagram and X; write, shoot and edit short-form video and appear on camera; run paid tests on LinkedIn, Meta and Google; a "data-led editorial voice" on retail trends and cultural moments, "not slop or click bait"; measured on clicks, conversions and qualified leads.Source
• HiringProduct Marketing Manager (first dedicated PMM): the buyer is "a VP of Consumer Insights" at an enterprise consumer company; the sale is "multi-stakeholder, long-cycle, and built on trust — we're asking teams to bring their proprietary data into our platform"; own the answer to "why not just use ChatGPT?", case studies, comparison content, competitor comparisons and win/loss; accountable for conversion to pipeline.Source