Plan a Client Content Calendar With Funnel Mapping

Most agency content calendars are built on vibes. A holiday post here, a service spotlight there, a blog article when someone has time. The result is a content library that generates traffic from people at every stage of the funnel and converts none of them consistently, because the content was not built with a specific conversion goal at each stage.

To learn more about the full client workflow behind this, visit How to Read a Geogrid and Build a Local SEO Action Plan. Run a Keyword Content Sprint for a Local SEO Client and Build a Membership WordPress Site That Retains Members cover adjacent steps in detail.

The BoFu/MoFu/ToFu framework is a content calendar architecture. Once you know what percentage of content should serve each funnel stage for a given client, every article has a purpose, a position, and a measurable contribution to the conversion pipeline.

This article covers how to determine the right split for a local SEO client, how to map a 90-day calendar using that split, and how F! Insights generates the article titles for each stage through the Writing Campaign tab.

What the Split Actually Determines

The funnel split determines what percentage of your total content output targets readers at each stage of the buying decision. It is not a creative choice. It is a conversion strategy.

Content funnel splits and the contexts where each makes sense.

Split BoFu MoFu ToFu Best For
Traffic-first 20% 30% 50% New sites with no domain authority; building topical credibility
Balanced 33% 33% 33% Established sites with decent traffic but inconsistent conversions
Conversion-first 60% 20% 20% F! Insights Writing Campaign default; strong for established agencies
BoFu-heavy 70% 15% 15% Product or plugin sites where the buyer is already solution-aware

For a local SEO agency pushing a single plugin or tool, a BoFu-heavy split makes the most sense after the first 30 to 40 articles have established topical authority. Traffic that converts is more valuable than traffic that reads and leaves.

Finding the Right Split for Each Client

The right split depends on two variables: the client’s current content library and their primary conversion bottleneck.

  • If the client has fewer than 20 published articles, start with a 40/30/30 split. Building topical authority first makes every subsequent article more effective.
  • If the client has 20 to 50 articles but most are ToFu, shift to 60/20/20 to build conversion content on the authority foundation already in place.
  • If the client has a healthy library and consistent traffic but poor conversion rate, go 70/15/15. More BoFu content gives the traffic already arriving somewhere to land that pushes toward a decision.

Run a free GBP scan on the business to understand the competitive gap context. A client in a market with weaker competitor content can afford a higher BoFu ratio earlier. A client in a highly competitive market needs more ToFu authority content before BoFu articles will rank.

Mapping a 90-Day Calendar

  1. Choose your sprint keyword or keywords. One primary service per sprint.
  2. Apply the funnel split to the total article count. At 60/20/20 across 15 articles: 9 BoFu, 3 MoFu, 3 ToFu.
  3. Schedule ToFu articles in weeks 1 and 2. They build authority and establish context for everything that follows.
  4. Schedule MoFu articles in weeks 3 and 4. They bridge the awareness content to the decision content.
  5. Schedule BoFu articles across weeks 3 through 12, spaced 3 days apart. They should appear consistently throughout the calendar, not all at the end.
  6. Add internal links during publication. Every BoFu article links to at least one MoFu and one ToFu article. Every ToFu article links forward to at least one MoFu or BoFu article.

Internal Linking Across Funnel Stages

Internal linking across funnel stages is what turns a content library into a conversion machine. A reader who arrives on a ToFu article and finds a relevant internal link to a MoFu article, and then from there to a BoFu article, moves down the funnel in one session. A reader who arrives on a ToFu article with no internal links reads it and leaves.

The linking rule: every article should link to one article above it in the funnel (closer to conversion) and one article at the same level (building topical authority). Never link down the funnel from BoFu back to ToFu as your primary link. That sends buyers back toward awareness when they are ready to act.

How F! Insights Automates the Calendar

F! Insights generates the full title set for a content calendar in the Writing Campaign tab. You enter the focus keyword, set the funnel split ratio, and Claude generates a title for every position in the calendar, split correctly across BoFu, MoFu, and ToFu stages. The titles are generated with the differentiator context if you provide one, so BoFu titles in particular reference the client’s specific capability rather than a generic angle.

For the sprint methodology that fills the calendar quickly, see How to Run a Keyword Content Sprint for a Local SEO Client.

Related reading: The BoFu/MoFu/ToFu split maps directly to building a 4-week GBP post queue. For how to write the posts that fill each funnel stage, see writing GBP posts that move the map pack needle. ToFu content from the calendar often feeds directly into publishing a local market report as an agency.

Frequently Asked Questions

Should the funnel split change over time for the same client?
Yes. Start with a higher ToFu and MoFu ratio when the site is new. Shift toward BoFu-heavy as domain authority builds and traffic increases. Review the split every 90 days based on which articles are driving the most conversions versus the most traffic.
How do I know if a planned article is really BoFu or just feels like it?
The test: would a reader who is about to make a hiring decision specifically search for this article? If yes, it is BoFu. “How much does HVAC repair cost in Columbus” is BoFu. “Why HVAC systems are more efficient than they were 20 years ago” is ToFu regardless of how much it mentions the service. Intent is the classifier, not the content’s promotional tone.
How many pieces of content should be in each funnel stage per month?
For a local SEO client running three to four GBP posts per week, a reasonable split is two BoFu posts, one MoFu post, and one ToFu post per week. BoFu-heavy calendars perform better for businesses with a short sales cycle and high-intent search volume. ToFu-heavy calendars perform better for businesses building a local audience over time. Most local service businesses benefit from the BoFu-heavy approach.
What makes a GBP post BoFu versus MoFu?
A BoFu GBP post has a specific call to action – call now, book today, get a quote – and references a current availability or offer. A MoFu post educates: it answers a common question, explains a process, or addresses a concern without a hard sell. A ToFu post builds awareness through seasonal content, team spotlights, or behind-the-scenes photos. A calendar with only BoFu posts loses engagement velocity over time.
How does the BoFu/MoFu/ToFu calendar connect to ranking in the Map Pack?
Post frequency and consistency are engagement signals that Google uses to assess profile activity. A calendar that maintains consistent posting across all three funnel stages sends stronger activity signals than a sporadic calendar of promotional-only posts. Beyond ranking, the mixed-content approach produces a profile that looks actively managed to any potential customer who scrolls through the post history.

Turn 10 GBP Scans Into a Publishable Industry Report

Ten GBP scans is not a large dataset. But for a specific industry in a specific city, ten scans of direct competitors in the same service category is enough data to write a credible, publishable local market report that positions your agency as the authority source on that market.

To learn more about building local authority with scan data, visit Run a Local Ranking Heatmap and Find Dead Zones. How to Read a Geogrid and Build a Local SEO Action Plan and Plan a Client Content Calendar With Funnel Mapping cover adjacent steps in detail.

Most agencies treat scan data as a prospecting tool. It is also a publishing asset. A market report built from real scan data, with named findings and category-specific conclusions, is shareable, linkable, and demonstrates capabilities in a way that a services page never can.

This article explains how to structure the report, what data to extract from the scans, and how F! Insights generates the first-signal market report from as few as 10 completed scans through the Market Intel tab.

What 10 Scans Actually Give You

Data available from 10 GBP scans in the same category.

Data Category What 10 Scans Reveal
Review data Average review count, average star rating, review velocity distribution across the category
Profile completeness How many businesses have complete vs incomplete GBP profiles; which elements are most commonly missing
PageSpeed Average mobile PageSpeed score for the category; distribution of scores
Competitive position Which businesses are consistently in the Map Pack vs outside it
Photo activity Average photo count per profile; how many businesses are posting photos at all

These averages become the benchmarks in your report. “The average HVAC company in Columbus has 34 Google reviews and a mobile PageSpeed score of 41” is a specific, verifiable finding that no competitor report in this market is publishing, because no one else has done the scan.

Report Structure That Works

  1. Executive summary: 3 to 5 top findings in plain language. This is what gets shared.
  2. Market overview: Category, city, scan methodology, and date range. Establishes credibility and reproducibility.
  3. Finding 1: Review landscape. Average count, distribution, velocity. Who is winning on reviews and by how much.
  4. Finding 2: Profile completeness. What percentage of businesses in this category have complete profiles. What elements are most commonly missing.
  5. Finding 3: Website performance. Average mobile PageSpeed score. How many businesses score below 50.
  6. Finding 4: Competitive gap analysis. The gap between the Map Pack leaders and the average business in the category. What the leaders have that others do not.
  7. Implications for local businesses: Plain-language translation of what the data means for any business in this category.
  8. Methodology note: How the scans were conducted. Transparent methodology is what makes the report citable.

Extracting Findings by Category

From the F! Insights scan data export, calculate the following for the 10 businesses in your report:

  • Mean, median, and range for review count and star rating
  • Mean, median, and range for mobile PageSpeed score
  • Percentage of profiles with complete business descriptions (keyword and city in first sentence)
  • Percentage of profiles with complete service lists
  • Percentage of profiles with post activity in the last 30 days
  • Percentage of profiles with complete attribute sets

Present each finding as a comparison between the category average and the Map Pack leaders. The gap is the story. The gap is also your sales angle for every business in the category that falls below the benchmark. See Local SEO Benchmarks: What Good Actually Looks Like for context on what benchmarks look like across categories.

Where and How to Publish

  • Publish on your agency website as a PDF landing page with an email gate or a free download. The download gives you an email list of people interested in local SEO in this specific category.
  • Share in local business association groups, industry forums, and relevant LinkedIn communities for the scanned category.
  • Email the report directly to the businesses in the scan as a value-first outreach. “I scanned 10 HVAC companies in Columbus. Your profile came up. Here is how you compare to the category average.”
  • Use it as the foundation for a prospect hit list. The businesses that score below the category average on two or more metrics are your priority outreach targets. See How to Build a Prospect Hit List From Your Local Scan Data.

How F! Insights Generates the Market Report

F! Insights generates a first-signal market report automatically when your scan library hits 10 completed scans in the Market Intel tab. Claude analyzes the scan data across all eight audit categories, identifies the most significant patterns, and generates a formatted report with findings, benchmarks, and category-specific conclusions. The report is exportable as a formatted document ready for publication or client delivery.

As your scan library grows, F! Insights unlocks additional Market Intel tiers at 25, 50, 100, and 200 scans. Each tier generates more sophisticated outputs: pitch decks, competitive gap analyses, annual market reports, and media-ready research assets. Run a free GBP scan on any local business to start building the dataset.

Related reading: For the full workflow for publishing a local market report including distribution, see that guide. The compounding argument for publishing market research that builds authority is explained there. The report framework maps to what local SEO benchmarks look like across markets for the niche you scanned. For which niches produce the most consistent scan data, which tells you where a 10-scan report will be most compelling, see that breakdown.

Frequently Asked Questions

Do I need permission from the scanned businesses to publish their data?
GBP data surfaced through the Google Places API is publicly available information. Aggregated findings do not require permission from individual businesses. If you include specific named businesses in the report, their GBP data is public, but standard practice is to use aggregated data in public reports and reserve named business data for direct outreach to those businesses.
Can I run this report for multiple cities and combine them?
Yes. A multi-city report covering the same category across five cities in the same state is a stronger publishing asset than a single-city report and positions your agency as a regional authority rather than a local one. Each city’s data remains a separate dataset for the per-city findings, with a regional summary as the lead section.
What should a local market intelligence report contain?
A local market intelligence report based on GBP scan data typically contains: the average GBP health score for businesses in the niche and market, the three most common scoring gaps across all profiles scanned, the correlation between GBP score and review count in that market, and a ranking of which categories show the widest gap between top and bottom performers. Ten scans is enough data to produce all four sections with specific, citable numbers.
Who is the intended audience for a local market intelligence report?
Two audiences: the businesses in the niche who want to know how they compare to competitors, and media and industry publications that cover the niche or the local market. Restaurants, real estate agencies, and healthcare practices are categories with active trade publications that regularly publish local market data. A well-structured report from fifteen to twenty scans can generate earned media coverage that paid advertising cannot replicate.
Can the scan data in a local market report be presented as original research?
Yes, and that is exactly how it should be framed. The scan data is proprietary. It was gathered by running your own queries through the Google Places API from your own F! Insights installation. No other source has the same data. Framing the report as “scan data from [month] across [niche] in [city]” is accurate and positions it as original primary research, which carries more credibility than secondary reporting on publicly available data.

Run a Local Ranking Heatmap and Find Your Dead Zones

A local business can rank first in Google Maps for someone searching from their parking lot and not appear at all for someone searching six blocks away. That is not a theoretical edge case. It is the default behavior of local search, and most business owners have no idea it is happening.

To learn more about building local authority with scan data, visit How to Read a Geogrid and Build a Local SEO Action Plan. Turn 10 GBP Scans Into a Publishable Industry Report and Plan a Client Content Calendar With Funnel Mapping cover adjacent steps in detail.

A local ranking heatmap, also called a geogrid, makes this visible. It plots a grid of points around a business location, runs a local search query from each point, and records where the business ranks at each location. The result is a visual map of where the business is winning and where it has disappeared entirely. Those invisible zones are dead zones, and they are where ranking work needs to happen.

This article explains how to run a geogrid, what the output tells you, and how F! Insights automates the process through the Near Me Visibility tool in the Client Workspace.

How a Ranking Heatmap Works

A geogrid tool divides an area around a business into a grid of equally spaced coordinate points. For each point, it simulates a local search query from that exact location and records the business’s ranking position in the local results. The ranking at each point is color-coded and displayed on a map overlay.

Standard color coding used in geogrid ranking heatmaps.

Grid Color What It Means
Green (rank 1-3) Business appears in the Map Pack from this location
Yellow (rank 4-10) Business appears in local results but below the Map Pack
Red (rank 11+) Business does not appear in visible local results from this location
Gray (no data) No ranking data returned; usually means no GBP presence detected

Setting Up Your First Geogrid

  1. Choose a keyword that represents the client’s primary service and how their customers actually search for it. “HVAC repair Columbus” is correct. “HVAC company” is too broad.
  2. Set the grid center to the business’s GBP address. This is the point from which all other grid points are calculated.
  3. Set the grid size. A 5×5 grid (25 points) gives a broad overview. A 7×7 grid (49 points) gives finer resolution. Start with 5×5 for a first scan.
  4. Set the grid radius. 0.5 miles between points works for dense urban markets. 1 to 2 miles is better for suburban and rural markets.
  5. Run the scan. F! Insights processes each grid point and returns a color-coded map with ranking data.

Run a free GBP scan on the business first to get overall GBP health data before running the geogrid. The two outputs together give you a complete picture of where the business stands.

Reading the Output

A healthy local ranking heatmap shows a green core centered on the business address with a gradual fade to yellow at the edges. A problematic map shows red zones close to the business address, meaning the business is invisible to searchers who are geographically near but not directly outside the front door.

Pay attention to three patterns specifically:

  • Asymmetric dead zones. Red on the north side, green on the south side. This usually means a competitor is dominating from a location north of the client.
  • Close-range dead zones. Red within half a mile of the business address. This is a profile problem, not a geographic one.
  • Keyword-specific dead zones. Run the same grid for two different service keywords. If the dead zones differ, the profile is not optimized for one of the services even though it is listed.

What Dead Zones Actually Tell You

Dead zone patterns and what each one indicates about the underlying issue.

Dead Zone Pattern Most Likely Cause Priority Action
Red everywhere beyond 0.5 miles Profile completeness below 60%; few reviews Full GBP profile audit before any other action
Red on one side only Strong competitor dominating from that direction Competitor gap analysis; citation and review push
Red for one keyword, green for another Missing service category or keyword in profile Add service category; update description and services
Yellow everywhere, never green Profile complete but not authoritative Review velocity campaign; GBP post cadence

What Causes Dead Zones

Common causes of local search dead zones and how difficult each is to fix.

Cause How Common Difficulty to Fix
Incomplete GBP profile (missing categories, services, description) Very common Low: 1-3 hours
Low review count compared to competitors in the area Common Medium: 60-90 day campaign
Inconsistent business name, address, phone across directories Common Medium: 3-6 hours to audit and correct
Missing or wrong secondary service categories Common Low: 30 minutes
No GBP post activity in 30+ days Common Low: start a post cadence
Strong competitor with 3x your review count in a specific zone Common Medium-High: long-term authority build

How to Fix the Most Common Dead Zone Causes

  • Incomplete profile. Log into your Google Business Profile. Go through every section: categories, services, description, photos, hours, attributes. Fill out everything that applies. Add your primary service keyword naturally to the business description in the first sentence.
  • Low review count. Start asking every customer for a review immediately after the service. Send a direct link to your GBP review page. The gap between your review count and the competitor dominating your dead zones is the primary thing you are trying to close.
  • Inconsistent NAP. Search your business name in Google to find every directory listing that mentions you. Check each one: is the name, address, and phone number exactly the same as what is in your GBP profile? Fix every variation.
  • No GBP post activity. Start posting. Three times per week, with your service keyword and city in the first sentence, for 60 days. That alone can reduce dead zones in markets where competitors are not posting either.

How Long Fixes Take to Work

Expected timeline for ranking movement after each type of dead zone fix.

Fix Type Time to See Ranking Movement
Profile completeness update 2-4 weeks for Google to re-index
Adding missing service categories 2-4 weeks
GBP post cadence (freshness signal) 6-10 weeks of consistent posting
Review count improvement 8-12 weeks depending on velocity
NAP consistency fixes 8-16 weeks for citation re-indexing
New citation building 12-20 weeks to full effect

Turning the Results Into an Action Plan

F! Insights generates a 5-pillar action plan from geogrid results automatically. The five pillars are GBP alignment, content strategy, attribute optimization, citation building, and NAP consistency. Each pillar includes specific tasks ranked by estimated ranking impact.

For how to read the action plan output and prioritize the work, see How to Read a Geogrid Result and Build an Action Plan.

How F! Insights Runs Geogrids

F! Insights includes the Near Me Visibility tool in the Client Workspace under the Map Pack sub-tab. You set the keyword, grid size, and radius. F! Insights runs the grid using the Google Places API and returns a color-coded heatmap with ranking data at each point. Claude then generates the 5-pillar action plan from the results.

The geogrid can be run on any business in your client roster, or on a prospect before you close them. Showing a prospect their own dead zone map in a sales meeting is one of the fastest ways to create urgency without saying anything. The data speaks for itself.

Related reading: After running the heatmap, the next step is reading the geogrid output and building a prioritized action plan. For how to configure the scan parameters correctly, see how grid density and radius settings change what the scan shows. For the business-owner version of what dead zones mean, see why local businesses disappear from the Google Map Pack. For a full comparison of the best local SEO geogrid tools compared, see that roundup.

Frequently Asked Questions

How often should I run a geogrid for an active client?
Once per month is the standard cadence for tracking ranking progress. Run an additional geogrid any time you make a significant change to the GBP profile. The before-and-after comparison is your proof of progress.
Does running a geogrid affect the client’s GBP profile?
No. A geogrid is a read-only query. It retrieves ranking data from the Google Places API but does not write anything to the client’s profile.
Can I run a geogrid on a competitor’s business?
Yes. You can run a geogrid on any business that has a GBP listing by using their address as the grid center. Running a geogrid on the dominant competitor in a dead zone is a standard diagnostic step for understanding why your client is not ranking in that area.
My business ranks first right outside my door. Why am I not ranking a mile away?
Proximity is only one of Google’s three local ranking factors. Your first-place ranking close to your location means Google trusts your profile there. The drop-off further out means a competitor’s prominence score is strong enough to override your distance advantage in those zones. Review count, post cadence, and citation authority are the signals that extend your ranking envelope outward.
If I fix my GBP profile, will the dead zones disappear?
A complete profile fix reduces dead zones caused by completeness and category gaps. It will not fully eliminate dead zones where a competitor has significantly more reviews and citation authority. Dead zone elimination usually requires fixing all five pillars over 90 to 120 days, not a single profile update.
Is a geogrid the same thing as a local ranking heatmap?
Yes. A geogrid and a local ranking heatmap refer to the same tool and the same output. The tool plots a grid of coordinate points around a business, runs a local search from each point, and maps the ranking results as a color-coded overlay. The terms are used interchangeably in local SEO, though “geogrid” is more common among practitioners and “ranking heatmap” is more common in agency client reports.
How do dead zones affect a business’s actual revenue?
A dead zone means the business does not appear in Google Maps for searchers in that geographic area, even if those searchers are closer to the business than the competitor that does rank. For high-intent searches like “electrician near me” or “restaurant open now,” not ranking in the Map Pack typically means not getting considered at all. Most searchers never scroll past the top three results. Even a modest dead zone covering two or three city blocks around a busy street can represent a significant portion of the accessible customer base.
How long does it take for dead zones to shrink after implementing fixes?
Profile completeness and category fixes typically show ranking movement within two to four weeks. Review velocity improvements take six to twelve weeks to produce measurable dead zone reduction, depending on how many reviews are added and how quickly. Citation and NAP consistency fixes take the longest, eight to sixteen weeks for the citation network to re-index. Run a follow-up geogrid scan four weeks after each round of fixes to measure actual movement.

How to Read a Geogrid and Build a Local SEO Action Plan

Running a geogrid is the easy part. You enter a keyword, set a radius, and a color-coded map appears. The harder part is deciding what the map is telling you and what to do about it. Most agencies run the grid, screenshot it for the client, and move on without turning it into a work plan.

To learn more about the full client workflow behind this, visit Client Content Calendar With Funnel Mapping. Run a Keyword Content Sprint for a Local SEO Client and Build a Membership WordPress Site That Retains Members cover adjacent steps in detail.

This article covers how to interpret every major geogrid output pattern and how to convert those patterns into a prioritized action plan you can deliver, track, and use to demonstrate progress over time.

The 5 Geogrid Patterns and What They Mean

  1. Strong center, weak edges. Green near the address, yellow and red further out. Normal for a profile that is complete but lacks authority to project ranking signal beyond immediate proximity. Fix: review velocity and consistent GBP post cadence over 60 to 90 days.
  2. Weak center, no green at all. Red or yellow even directly next to the business address. This is a profile completeness problem. Run a full profile audit before anything else. See How to Run a GBP Profile Audit and Score It Across 8 Categories.
  3. Asymmetric ranking. Green on one side of the map, red on the other. A strong competitor is dominating from a location on the red side. Identify that competitor using the scan data and build a gap analysis to understand what they have that your client does not.
  4. Keyword-specific gaps. Different keywords produce different dead zone maps. If the business ranks well for “dentist Columbus” but not for “teeth whitening Columbus,” the profile is not optimized for the secondary service category. Fix: targeted profile edits, not broad authority building.
  5. Even yellow grid, no red. The business ranks consistently in positions 4 through 10 everywhere but never breaks into the Map Pack. This is a review count and freshness problem. Review velocity and GBP posts are the lever.

How to Prioritize What You Fix First

Geogrid action items ranked by effort vs ranking impact.

Issue Effort Ranking Impact Priority
Profile completeness gaps (missing categories, services, description) Low: 1-2 hours High: immediate signal improvement Fix first
NAP inconsistency across citations Medium: 2-5 hours High: trust signal for Google Fix second
Review count gap vs competitors Medium: ongoing High: dominant ranking factor Parallel campaign
GBP post cadence Low: automated with F! Insights Medium: freshness signal Start immediately
Citation building High: 5-10 hours Medium: long-term authority Fix third
Attribute optimization Low: 30 minutes Medium: relevance for specific searches Fix alongside profile gaps

Building the Action Plan Document

A good geogrid action plan has four components: the current state (the geogrid screenshot with dead zones annotated), the root cause for each dead zone pattern, a prioritized task list with owners and timelines, and a checkpoint date for a follow-up geogrid to measure progress.

  • Annotate the geogrid screenshot before sharing it with the client. Circle the dead zones. Label the dominant competitor visible in the asymmetric zones. Add a one-line explanation of what each zone means in plain language.
  • Group tasks by effort level: quick wins (under 2 hours), medium tasks (2 to 5 hours), ongoing campaigns (GBP posts, review requests). Present them in that order.
  • Set a specific checkpoint date for the follow-up geogrid. 60 days is the minimum for profile completeness fixes to show ranking movement. 90 days is the right window for review velocity and post cadence campaigns.

For the full 5-pillar framework that structures the action plan, see The 5-Pillar Method for Improving Near-Me Search Ranking.

Tracking Progress Over Time

Run the same geogrid, same keyword, same grid size and radius, at every checkpoint date. Overlay the before and after maps. The expansion of green from the center outward is your proof of progress. For how to present this in a client report, see How to Use a GBP Progress Report to Justify Your Monthly Retainer.

How F! Insights Generates the Action Plan

F! Insights generates a structured 5-pillar action plan automatically from the geogrid output. After the Near Me Visibility scan completes, Claude analyzes the ranking pattern and produces a task list organized by the five pillars: GBP alignment, content strategy, attribute optimization, citation building, and NAP consistency. Each task includes an estimated impact rating and a suggested sequence.

The action plan is exportable as a formatted document you can share with the client or use internally as a work order. Run a free GBP scan to get the GBP health data that contextualizes the geogrid results before building the action plan.

Related reading: This guide assumes you have already completed running the heatmap scan and finding dead zones. If the results look inconsistent, how grid density and radius settings affect the scan explains how the configuration changes the output. For a comparison of the best local SEO geogrid tools for agencies, see that roundup. For the owner-facing explanation of what dead zone data means, see why businesses disappear from the Google Map Pack.

Frequently Asked Questions

How long does it take to see ranking improvement after fixing geogrid dead zones?
Profile completeness fixes can produce ranking movement within 2 to 4 weeks. Review velocity and post cadence campaigns take 60 to 90 days to show consistent movement in the geogrid. Citation building and NAP correction take 90 to 120 days to fully index and affect ranking.
Should I share the raw geogrid with the client or only the action plan?
Share both, but lead with the action plan. The raw geogrid is compelling visual evidence of a problem. The action plan is what demonstrates that you know how to fix it. Clients who see only the problem without the solution become anxious. Clients who see the solution first engage with the problem constructively.
How do I know if a dead zone is caused by the profile or by a competitor?
Run the same geogrid for the dominant competitor in that dead zone. If the competitor shows strong green coverage in the same area where your client shows red, the issue is competitive authority, not profile completeness. If the competitor also shows weak coverage there, the dead zone is a market-wide signal issue, likely tied to keyword or category gaps that neither profile fully covers.
What should go first on the action plan from a geogrid result?
Start with the actions that address the most common dead zone pattern. For close-range dead zones within half a mile, start with profile completeness and category fixes. These can produce visible ranking movement in two to four weeks. For outer-zone dead zones, start with review velocity and citation building. These take longer but have more lasting impact on the ranking envelope.
How many keywords should I run geogrid scans for per client?
Start with the client’s primary service keyword plus one secondary service keyword. Two scans per client per month gives you enough comparative data to identify whether the dead zones are keyword-specific or geographic-wide. If the two scans show different dead zone patterns, the profile has a category alignment problem. If the dead zones are identical across both keywords, the issue is authority and proximity.