Matthew Montez

Losses mount at the seams: teams buying traffic they already rank for, landing pages built for the wrong intent, and leads arriving without source data that matches the campaign. In their view, adding a fourth vendor only adds handoffs and finger-pointing; the fix is one partner accountable across SEO, paid, and CRM.

An owner forwards three dashboards: SEO reports traffic up, the ads agency reports good ROAS, and the CRM shows leads coming in — while the close rate drops.

• The gaps include the SEO team ranking for keywords the ads team is already paying for, cold traffic landing on pages optimized for different intent, and leads hitting the CRM without source tags that match the campaign.
• Montez concludes that each vendor is doing its job, but nobody is paid to manage the work between them.
• The answer, they argue, is one team holding the full picture rather than three reports that never meet.

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Their method is an ordered setup sequence with a self-test at each step. Only after verifying the chain does it make sense to look at historical data, much of which, they say, turns out to be unusable.

The post gives six steps: confirm GA4 fires by triggering an event and watching the real-time report, rather than assuming the tag is present; define which events map to revenue — form submit, call click, purchase — instead of pageviews; mark those as key events so Google Ads can optimize against them; link GA4 to Google Ads and Search Console in both directions, then check that data arrives inside Ads; test the full path by submitting the form or making the call and following it into GA, then Ads, then the CRM; and only then review the last 90 days.

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A pipeline can look healthy on leads and sales-qualified opportunities while the median response time quietly caps what the funnel can produce. The remedy is measurable: find the real median, route anything slow to a named owner, and track it weekly wherever pipeline is tracked.

The post sets a five-minute response window as the baseline: qualification is roughly 21 times less likely at thirty minutes, an hour means the seller is out of the conversation, and by a day a competitor has already closed the deal.

• A team averaging 47 minutes has a 47-minute problem, not a top-of-funnel problem.
• Three Monday actions: pull the true median response time rather than the number in the quarterly deck; route anything over five minutes to an SDR, automation, or the founder's phone; and measure it weekly.
• A later post describes cutting first-response time from days to under fifteen minutes through routing.

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The prescribed test takes a week and produces a clear verdict.

The post opens with a CRM where hundreds of leads had a last follow-up four months earlier, while the owner had spent six weeks asking for more leads.

• The test: count every lead older than thirty days with no follow-up, directly call or email the last fifty that showed real interest, and track what comes back within seven days.
• If nothing returns, the problem was never volume; if something does, the business has found revenue it already paid for.

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Montez promotes a full-service ecommerce marketing agency built around an in-house AI called Aiden working with a dedicated human marketer, priced flat-rate with a fourteen-day free trial. The pitch: the AI handles ideas, setups, and reports while people supply judgment and relationships, and the combination removes campaign-management overload.

One post introduces Aiden as the AI that never sleeps and stresses that every campaign is powered by real people who listen and adapt. Others frame the offer around burnout and the strain of managing nonstop campaigns, describing a fast-growing Denver ecommerce brand that traded chaos for faster, data-driven iteration and ran three marketing tests a week with an AI assistant.

The two strands address different audiences and sit side by side in the same account. Promotional posts target ecommerce brands with hashtag-led hashtags and trial calls to action; longer diagnostic posts on tracking, response time, and CRM follow-up speak to owners about pipeline and close rates.

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It is the clearest statement of the problem Montez writes about: marketing teams report success channel by channel while revenue quietly leaks in the handoffs between them. It answers the question newcomers are most likely to ask: what does Montez actually argue?

Montez describes owners forwarding three dashboards that all look healthy while close rate drops, then lists five specific gaps: the SEO team ranking for keywords the ads team is already paying for; cold traffic landing on pages optimized for a different intent; leads reaching the CRM with no source tagging that matches the campaign; eight months of CRM intent data the ads team has never opened; and conversion tracking that broke for eleven days before anyone noticed.

• Their conclusion: adding a fourth vendor makes the problem worse.
• The fix is one team covering SEO, paid, and CRM as a single system, a model Montez attributes to MBC Group.

For brands planning a campaign

The five failure points make a ready-made agenda for a co-marketing webinar or guest piece on attribution and cross-team handoffs. Each is concrete enough to demo live against a sample stack.

It answers "what does fixing measurement actually look like, in order?" and shows the working method behind the argument in the first post.

Montez argues that most accounts have Google Analytics installed but unconfigured, leaving every campaign optimized against nothing. The sequence: confirm GA4 is firing rather than assume the tag is present; define which events map to revenue instead of pageviews; mark those as key events so Google Ads can optimize against them; link GA4 to Google Ads and Search Console in both directions and check that data arrives inside Ads; test the full path by submitting a form or making a call and watching it land in GA, then Ads, then the CRM; only then review the last 90 days, expecting most historical data to be unusable.

For brands planning a campaign

Useful as guest content for a software audience because it names the exact steps a product would automate. It also sets up an honest demo: the post’s test-and-verify step is what a tool has to make easier.

It answers "what does this look like when it is fixed?"

Montez writes that new partners usually cannot say what their website is doing: how many leads arrive per channel or how analytics are performing.

• The audit found conversion tracking wired so clicks were counted but conversations were not, follow-up taking days rather than minutes, and reports measuring traffic instead of revenue.
• The repairs: rebuild tracking from ad click to closed deal, cut first response to under fifteen minutes through routing, and replace click reports with revenue numbers per channel, campaign, and week.
• Their framing: the system was never wired up, rather than broken.

For brands planning a campaign

The before-and-after structure suits a joint case study, especially with a CRM or RevOps partner whose product handles follow-up and reporting.

It shows how the lead-response point fits the wider revenue-leak argument.

Montez claims a five-minute response window, with qualification odds roughly 21 times worse at thirty minutes, a lead effectively gone after an hour, and a competitor already winning after a day.

• The post argues that speed of follow-up outweighs lead quality, messaging, and channel mix, and that a team averaging 47 minutes has a ceiling it will not see in its dashboard.
• The suggested Monday actions: pull the real median response time, route anything over five minutes to an SDR, automation, or the founder’s phone, and measure it weekly alongside pipeline.

For brands planning a campaign

Lead response time is the strongest hook for a webinar or guest piece aimed at RevOps and agency audiences. It turns a familiar complaint into a number readers can pull from their own CRM in an afternoon.

It answers "what does Montez tell a company that says it needs more leads?"

Montez recounts a client asking for more leads for six weeks while hundreds of leads sat with a last follow-up four months old.

• Their argument: every name in a CRM already cost money through ads, content, or salary, and the request for more volume usually masks a follow-up problem.
• The suggested test is to count every lead older than thirty days with no follow-up, contact the last fifty that showed real interest, and track what comes back within seven days.
• A response indicates recoverable revenue; silence suggests the problem was never volume.

For brands planning a campaign

A direct co-marketing angle with a CRM vendor: the recovery test is a simple, teachable exercise that ends in the product’s home territory.

This post promotes an ecommerce marketing agency offer built around "Aiden," described as an in-house AI paired with a dedicated human marketer, at a flat rate with a fourteen-day free trial.

• The pitch targets ecommerce brands dealing with campaign management overhead.
• Near-identical versions appear in three other posts in this set, with variations on burnout, testing three campaigns a week with an AI assistant, and combining automation with human attention.

For brands planning a campaign

The offer targets ecommerce brands rather than B2B software buyers, so the promotional posts and revenue-leak posts reach different audiences. A partnership fits the measurement and follow-up material better than the AI agency pitch.

The same failure points recur across two posts: the SEO team ranks for keywords the ads team is already paying for; ads send cold traffic to pages built for a different intent; leads land in the CRM without source tagging that matches the campaign; and conversion tracking breaks after a landing page change without anyone noticing for days.

• In a post about a client whose traffic was real but pipeline was fiction, the remedy was to rebuild tracking from ad click to closed deal and replace click reports with revenue reports per channel, per campaign, per week.
• Montez frames the fix as one partner covering every channel rather than adding a fourth vendor to the handoff chain.

Walks through each broken handoff as a numbered item, then names the single-owner alternative.

For brands planning a campaign

This is the strongest hook for a campaign aimed at RevOps buyers.

• A webinar or guest piece built around mapping a single lead from first click to closed-won deal matches Montez’s framing.
• They can supply the diagnostic questions—who owns the white space, and is tracking wired end to end—that a software audience would recognize as its own pain.

Examples: Source 1 · Source 2

Only then does Montez look at the last 90 days of data. The stated reason: campaigns run before this step were optimized against nothing.

Ordered setup sequence, with a self-test at each stage rather than a definition of the concept.

For brands planning a campaign

Concrete, checklist-shaped material that can go straight into a co-marketing asset: a tracking-readiness checklist or a joint webinar segment where viewers follow along in their own GA4 account. A software partner can add a technical counterpoint for depth.

Examples: Source 1

The post attributes the collapse to a response window: five minutes is the baseline, thirty minutes makes qualification far less likely, an hour puts the seller outside the conversation, and a day means the deal is already closed by someone else.

• A dashboard can look healthy while a median response time of 47 minutes remains the real ceiling on conversion.
• Montez recommends three Monday actions: pull the true median response time rather than the number in the quarterly deck, route anything over five minutes to a specific owner, and measure it weekly wherever pipeline is measured.
• A later post describes cutting first-response time from days to under fifteen minutes with routing.

Sets a response-time ladder against the funnel metrics teams normally watch, then boils the argument down to three measurable actions.

For brands planning a campaign

Speed-to-lead is a shared concern for CRM and RevOps buyers, and Montez’s numbers give the segment a spine. A co-hosted webinar could pair their response-time framing with product-side routing and alerting; the three Monday actions translate into a usable takeaway slide.

Examples: Source 1 · Source 2

Montez argues that a request for more volume usually masks unworked volume, and that every untouched name already cost money in ads, content, or salary.

• The prescribed test is deliberately small: count every lead older than thirty days with no follow-up, directly call or email the last fifty who showed real interest, and track what comes back within seven days.
• If nothing returns, the problem was not volume; if something does, the business just found revenue it already paid for.

Reverses the stated problem (needs more leads) and replaces it with a short, countable experiment.

For brands planning a campaign

A useful counterweight in a co-marketing piece that would otherwise push acquisition features, and a natural prompt for a joint content offer on CRM hygiene or reactivation workflows. The seven-day test is small enough for a reader to run after one session.

Examples: Source 1

Two lead with stress and burnout, describing a fast-growing Denver ecommerce brand that traded campaign chaos for faster iteration. Another argues that the AI handles ideas, setups, and reports while people supply the judgment and relationships.

Ask for the payment terms, trial mechanics, and identity of the Denver client; the posts state only that the offer includes a fourteen-day free trial and an AI named Aiden.

For brands planning a campaign

These posts show how Montez markets their own services and what the offer looks like when they are the seller rather than the diagnostician.

• A software partner should treat them as positioning, not as the editorial register for co-marketing: the posts carry hashtags and trial calls to action.
• Ask for named-client examples, figures, or client outcomes that readers can verify.

Examples: Source 1 · Source 2 · Source 3 · Source 4

A short, declarative opening states a problem (green dashboards and a bleeding bank account, a five-minute window, a CRM graveyard).

• The middle is a numbered list of failure modes or an ordered fix, often with a concrete number attached.
• The close reframes the problem in a repeatable sentence, then names the fix as a system rather than a tactic.
• Two clusters emerge: the promotional AI-agency posts appear earlier in the sequence, while the longer diagnostic posts on tracking, response time, and CRM follow-up appear later.

For brands planning a campaign

The diagnostic format is the one to borrow for co-marketing. It is short enough for a social amplification plan around a webinar, and the numbered middle is where a partner’s data or product screenshots can fit without breaking Montez’s voice.

Examples: Source 1 · Source 2 · Source 3 · Source 4 · Source 5

SEO, paid, and CRM as one system." The post does not specify Montez’s relationship with the firm; ask whether they own it, work for it, or partner with it.

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The posts use "our" and "we" but never name the business.

• Aiden is presented as the agency's own tool, not a separate brand relationship.
• Ask whether Montez owns the business, works there, or promotes it as a partner.

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Both treat the data layer, not the campaign, as the usual problem, and offer an audit to run rather than a tactic to buy.

Chapman writes from the UK paid-search lead-generation agency seat, keeping the remedy within Google Ads, LinkedIn, and Meta reporting discipline: test the tags, check attribution, and stop reporting vanity metrics. Montez widens the frame to the seam between SEO, paid, and CRM, arguing for one owner across all three; they differ from Chapman, who argues for a specialist partner reporting on revenue.

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Both trace the gap between the tracking layer and the business outcome in GA4, the CRM, and the ad platform, with checks readers can run.

Akash focuses on analytics and B2B demand generation, using longer worked scenarios with named tools, dollar figures, and 45-day consideration timelines. Montez is shorter and more operational, adding the argument that one team should run the whole chain instead of two teams reading the same dashboard to opposite conclusions.

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They favor a live diagnostic of a broken funnel over a polished case-study deck.

Raza is a Meta Ads funnel operator who tells the story in first person, including deliberately pushing cost per lead from $3 to $16 with qualification gates and manually typed phone numbers to save a client account. Montez offers no comparable client rescue narrative; they write numbered cross-channel checklists and treat follow-up speed and CRM hygiene, rather than form friction, as the lever.

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In her tracking-audit post, she shows how broken tags can quietly distort budget decisions.

• A second post argues that reports should connect ad activity to qualified leads, opportunities, and revenue—not stop at clicks and impressions (revenue-focused metrics).
• That makes a focused audit or reporting session a natural fit.

Her examples focus on PPC measurement and reporting. Matthew’s cover a wider range of revenue-path problems, including coordination between SEO, paid media, CRM follow-up, and lead response.

His attribution explainer distinguishes reports on where clicks came from from information on which campaigns produced customers, then offers checks for finding breaks in the path. His Google Ads tracking guide adds practical setup and audit steps.

These examples focus on attribution and conversion tracking, while Matthew’s work emphasizes cross-vendor handoffs, CRM follow-up, and response speed.

In his lead-qualification case, he describes replacing a one-click form with qualification questions and manual phone entry.

• Lead volume fell, but the goal was to give sales more useful prospects—a strong basis for a practical session on qualification rather than lead count.
• His performance-marketing lessons also connect lead quality to offer strength and funnel diagnosis.

His examples center on Meta lead generation and qualification, while Matthew’s work focuses on tracking, CRM follow-up, and multi-channel coordination.