Analytics Connector
Connect GA4 so profile activity can be measured against actual site traffic and enquiries.
An analytics connector joins profile activity to what happened afterwards, so the question “did the work produce anything” has an answer built from your own data rather than an inference drawn after the fact.
What it does
Most local SEO reporting stops at activity. Posts published, photos uploaded, reviews replied to, tasks completed. It is all true and none of it answers the question the person paying is actually asking, which is whether any of it produced calls, visits or enquiries.
The gap exists because the two halves of the answer live in different places. Activity is in the profile and the task list. Outcomes are in profile insights, in the website analytics, in the phone system. Nobody joins them, so the connection is asserted in a sentence at the end of a report and believed to the extent the reader is inclined to believe it.
Joining them does not prove causation and should not be presented as if it does. What it produces is a timeline where activity and outcome sit on the same axis, so a change that follows a period of work is at least visible, and a claim that nothing changed can be checked rather than argued.
It also disciplines the reporting in a useful direction. Once outcomes are on the same page as activity, work that produces nothing becomes visible too. That is uncomfortable and it is the main reason the join is worth building.
Everything Analytics Connector gives you
Profile insights imported
Views, searches and actions pulled in rather than screenshotted.
Website analytics joined
Sessions and conversions from local sources alongside profile data.
Call tracking where present
Calls attributed to the profile rather than assumed from a total.
Activity on the same timeline
Posts, photos, replies and edits plotted against outcomes.
Period comparison
Like for like against the previous period and the same period last year.
Per-location breakdown
Each location separately, since estate averages conceal both problems and wins.
Consistent metric definitions
The same measures each period so a change reflects performance rather than redefinition.
Export for reporting
The joined view available where clients actually read it.
Data freshness indicators
When each source was last updated, since some lag by days.
From setup to first result
- 1
Connect the sources
Profile insights, website analytics and call tracking if it exists.
- 2
Fix the metric definitions
Decide what counts as an outcome before you start reporting on it.
- 3
Plot activity on the same axis
Posts, photos and replies against views, calls and sessions.
- 4
Establish a baseline period
A stretch of normal activity to compare later periods against.
- 5
Compare like for like
Same length, same season, same metric definitions.
- 6
Separate by location
Estate averages hide both the failures and the successes.
- 7
Report what did not move
The activity with no visible effect is the finding worth acting on.
What changes with Analytics Connector
- Reporting activity as if it were outcome
- Claiming causation from a timeline
- Changing metric definitions between periods
- Comparing across different seasons
- Reporting the estate average only
- Activity reporting answers nothing
- The halves live apart
- A shared timeline makes claims checkable
- Ineffective work stays invisible otherwise
- Definitions drift between periods
Activity reporting answers nothing
Posts published is a description of effort, not of result.
The halves live apart
Profile data and website data are separate by default, so nobody joins them and the link goes unexamined.
A shared timeline makes claims checkable
Correlation is not proof, but it is considerably better than an assertion at the end of a report.
Ineffective work stays invisible otherwise
Without outcomes on the same page, effort that produces nothing continues indefinitely.
Definitions drift between periods
If what counts as a conversion changes, every comparison is meaningless and nobody notices.
Estate averages conceal both directions
One strong location can mask several weak ones, and one weak one can hide genuine wins.
What it measures
- Profile views and searches
- Actions taken from the profile
- Sessions from local sources
- Calls attributed to the profile
- Activity items per period
- Change against the comparison period
What you get out of it
Outcomes beside activity
Not activity alone.
Checkable claims
Rather than assertions.
Ineffective work exposed
Visible instead of assumed.
Comparable periods
Stable definitions.
Per-location truth
No averaging away.
One assembled view
Not four tabs.
What Analytics Connector produces
Every output is exportable and white-label, with your branding and none of ours.
Joined timeline
Activity and outcomes on one axis.
Period comparison
Against previous and year-ago periods.
Per-location view
Each location separately.
Source breakdown
Where outcomes came from.
Effect summary
What moved and what did not.
Freshness indicators
When each source last updated.
Who uses Analytics Connector
Ship location pages, schema and locators for clients without a development queue.
Give every location a page that can rank and a route from the homepage to it.
Roll out consistent local pages across the network at once.
Turn profile visibility into enquiries on your own site.
Get more out of it
- Define your outcome metrics before reporting on them, and then leave the definitions alone.
- Establish a baseline period of normal activity before any campaign, or later comparison has no reference.
- Compare like for like — same length, same season — since local demand is strongly seasonal.
- Present correlation as correlation. Overclaiming causation is the fastest way to lose a report’s credibility.
- Break the view down by location, because estate averages hide both the problems and the wins.
- Report what did not move as well as what did. That half is where the next decision comes from.
Reporting activity as if it were outcome
Posts published tells the reader what you did, which is not what they asked.
Claiming causation from a timeline
Correlation is worth having and overstating it destroys trust in everything else in the report.
Changing metric definitions between periods
Every comparison silently becomes invalid and nothing announces it.
Comparing across different seasons
Local demand is seasonal enough that a month-on-month change is often just the calendar.
Reporting the estate average only
A strong location conceals several weak ones, and the average is true of nowhere.
Manually vs with Analytics Connector
| Doing it manually | With Analytics Connector |
|---|---|
| Activity counts | Activity beside outcomes |
| Sources read separately | One joined timeline |
| Effect asserted | Effect visible and checkable |
| Definitions drift | Fixed metric definitions |
| Month against month | Like-for-like periods |
| Estate average | Per-location breakdown |
- Connect profile, website and call sources
- Agree the outcome definitions and fix them
- Plot activity against outcomes on one timeline
- Record a baseline period
- Compare like-for-like periods only
- Break results down per location
- Report the activity that produced nothing
Analytics Connector is 1 of 42 tools you get
Every tool below is on the same plan at the same price. Nothing here is an add-on, an upgrade, or a separate subscription.
Rank & Visibility
Manage Profiles
Posts & Automation
Reviews & Reputation
Reports & White-Label
Others vs Local Rank Checker
How the usual pricing and packaging in this category compares with ours.
“Other tools” describes the common pattern across the category, not any one named product.
Analytics Connector is included on every plan
One flat price per location covers all 42 tools. There is no higher tier, no add-on, and no per-seat charge.
- All 42 tools on every plan
- No per-seat charges
- No setup fee and no contract
- Cancel or change locations any time
Analytics Connector questions
What does joining the data actually give me?
Activity and outcomes on the same timeline, so the question of whether work produced anything can be examined rather than asserted.
Does this prove my work caused the change?
No. It shows correlation on a shared axis, which is considerably more than a sentence claiming an effect, and considerably less than proof.
Why not just read profile insights?
Because they contain outcomes and not activity. The join is what makes either half interpretable.
What counts as an outcome?
Calls, direction requests, website sessions from local sources, and form completions. Decide before reporting, then do not change it.
Why do definitions matter so much?
Because a redefined metric makes every historical comparison invalid, and nothing in the report announces that it happened.
How long a baseline is useful?
Long enough to cover normal variation — usually two to three months of ordinary activity.
Why compare like for like?
Local demand is seasonal. A month-on-month change frequently reflects the calendar rather than anything you did.
Should I report work that produced nothing?
Yes. That is where the next decision comes from, and omitting it means repeating the same activity indefinitely.
How often should this be reviewed?
Monthly for reporting, quarterly for decisions. Profile data is too noisy week to week to act on.
Do I need call tracking?
It helps a great deal. Without it, calls are inferred from a total rather than attributed to a source.
Why per-location rather than the estate?
An average is true of nowhere. It hides the weak locations and it hides the wins equally.
How current is the data?
It varies by source, and some lag by several days. That is why freshness should be shown rather than assumed.
Can this connect to my existing reports?
Yes, the joined view exports so it can sit inside whatever your clients already read.
What if outcomes fall while activity rises?
That is a finding worth having. It usually means the activity is not the constraint, and something else is.
Does this replace rank tracking?
No. Rank measures visibility, this measures what happened afterwards. Both are needed and neither substitutes.
How much history is needed before it is useful?
Roughly a quarter. Less than that and seasonal variation dominates whatever you are looking at.
Should clients see the raw data?
They should see the joined view with commentary. Raw figures without interpretation generate questions rather than answers.
What is the most common reporting error?
Presenting activity as achievement. It is the default and it answers a question nobody asked.
Can I compare locations against each other?
Carefully. Different markets and different maturity make direct comparison misleading unless it is qualified.
What single change improves reporting most?
Putting outcomes on the same page as activity. Everything else follows from that being visible.
Every tool. One price. No add-ons.
$5.33 per location per month gets you Analytics Connector and the other 41 tools.