Marketing you can explain, not just report
- Capability
- 04 Analytics
- Service
- Marketing Analytics
- Typical engagement
- Twelve weeks to first measured read
- Measured on
- Verified outcomes, not impressions
Marketing analytics is the strategic measurement discipline that turns disconnected marketing signals into a clearer picture of what is working, what is not, and where to invest next. It starts with the questions the organization needs answered, establishes whether the underlying data can be trusted, and ends in decisions rather than another dashboard.
stages from definition through recommendation
levels in the measurement hierarchy we work from
data quality reviewed before analysis begins
years measuring marketing in Riverside
Selected clients
Meet some of the Raincross experts behind Marketing Analytics.
A selection of the specialists who lead and shape this work, supported by a broader multidisciplinary team.
Measurement that ends in a decision.
Marketing analytics is the discipline of understanding how marketing activity contributes to meaningful business outcomes. It sits above implementation and reporting. Its job is to decide what deserves to be measured, judge whether the available data supports a conclusion, compare performance across channels that play genuinely different roles, and interpret the result in a way that changes what the organization does next. The chain it follows is simple to state and difficult to maintain: marketing activity produces reliable data, analysis produces insight, insight produces a decision, and the decision produces an improvement worth measuring again.
Measurement is difficult for structural reasons, not because teams are careless. Customer journeys cross devices, sessions, and weeks. Some of the most valuable actions happen on a phone call or in person, where no tag is watching. Privacy controls and consent legitimately limit what can be observed. Every platform scores itself using its own rules, its own lookback window, and its own definition of a conversion, so two accurate systems routinely disagree. And the metric that looks most impressive is frequently the one furthest from anything the business recognizes as a result.
So we hold a few positions firmly. Data quality comes before analysis, because a confident recommendation built on broken tracking is worse than no recommendation. No single platform is treated as the whole truth. Context is part of the metric, since a cost per click or a conversion rate means nothing without the objective, audience, channel, and timeframe attached. Channels are judged against the role they were built to play, because an awareness campaign held to high intent search metrics will always look like a failure. And analysis has to end somewhere useful. If a review does not produce a view on what to continue, change, test, stop, or fund, it was reporting wearing an analyst's coat.
The question is not how many clicks. It is what the marketing produced.
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- stages in the Raincross measurement process
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- levels in the measurement hierarchy
The stack behind the work.
We are platform-independent. Tooling is chosen per engagement, and every account is client-owned.
Google Analytics 4
Looker Studio
- and more...
Meta
Microsoft Advertising
- Programmatic DSP reporting
- and more...
- CRM data where available
- Call tracking where available
- Ecommerce data where applicable
- Form and lead records
- and more...
- Shared conversion definitions
- Consistent campaign tagging
- A documented measurement plan
- Written interpretation, not only charts
- and more...
What this work is usually brought in to fix.
Eight failure patterns we see repeatedly, and what we change about each.
- Numbers that disagree with each other
- Every platform reports a different figure and each one is technically correct. Without a reconciled definition, the meeting becomes a debate about the data instead of a decision about the marketing.
- Performance that cannot be connected to results
- Impressions, clicks, and sessions are up, and nobody can say whether the business received anything for it. The metrics improved without the outcome moving.
- Conversion data nobody has verified
- A conversion count includes duplicates, test submissions, and spam, or misses phone calls entirely. Every analysis built on top of it inherits those flaws.
- Reporting with no hierarchy
- Forty metrics are reported monthly and none is designated as the one that matters, so attention lands on whichever number moved most.
- Channels judged by the same yardstick
- An awareness campaign and a bottom of funnel search campaign are compared on cost per conversion, which guarantees the wrong conclusion about both.
- Volume mistaken for value
- Leads are counted but never qualified, so the channel producing the most volume gets the credit while the channel producing actual customers looks expensive.
- Dashboards nobody acts on
- The dashboards are current, attractive, and unread, because looking at them has never once resulted in a change to the marketing.
- Budget decisions made without evidence
- The allocation conversation happens without evidence, so it follows last year's split, the loudest channel, or whichever platform sent the most confident report.
Where this service earns its place.
If none of these describe the situation, we will say so before a proposal is written.
- 01
Organizations running several channels at once
Spend is spread across search, social, programmatic, and organic, and each channel reports its own success. Nobody has reconciled them into a single account of what the marketing produced.
- 02
Teams with reports but no answers
The reporting arrives on schedule and the numbers are accurate, and yet the same questions come up every quarter, because the reports describe activity rather than explain results.
- 03
Marketing leaders who have to justify budget
A budget decision is coming and the supporting evidence is a set of platform screenshots that disagree. The decision gets made on instinct and defended afterward.
- 04
Businesses whose outcomes happen offline
The valuable action happens on a phone call, in a showroom, or weeks later in a CRM. Website conversions alone describe a fraction of what the marketing is doing.
- 05
Teams that no longer trust their data
Someone noticed the analytics numbers do not match the ad platform, or that a conversion count changed after a site release, and confidence in the whole setup quietly collapsed.
- 06
Brands measuring every channel the same way
Awareness work, demand capture, and local visibility are judged with one conversion metric, which makes the upper funnel look like a failure and the lower funnel look like genius.
Collect less, and measure what matters
The instinct when marketing performance is unclear is to collect more of it. Another platform, another dashboard, another weekly export. It rarely helps, because the problem is almost never a shortage of numbers. It is that nobody has decided which numbers are supposed to indicate progress, whether the underlying tracking can be trusted, or what a given figure means in the context of the objective, the audience, the channel, and the timeframe. So we work in the other direction. Start with the questions the organization needs answered, establish which signals can answer them, verify that those signals are being collected correctly, and only then analyze. A small set of trustworthy measurements that someone acts on beats a comprehensive set that nobody reads.
More data does not automatically produce better decisions. It usually produces longer meetings.
Fig. 02
Raw data is not the product.
Every platform reports the part of the journey its own tag could observe. Ad platforms credit the click or the view they served. Analytics credits the last source it could see. Search Console describes the query, the CRM describes the outcome, and the call record describes the conversation none of them captured. Reconciling those into one account, adding the context of objective, audience, and timeframe, and analyzing the result is what separates a decision from an export.
Platform exports are the input to analysis, not the conclusion of it.
A review should end in a decision: continue, change, test, stop, or fund differently.
How the work runs.
Seven stages, run in order. Measurement design is agreed before any budget is committed.
What is included.
Scoped per engagement. Most programs use four or five of the capabilities below.
- 01
Marketing measurement strategy
Establishing what the marketing is meant to accomplish, how progress will be judged, and which signals are actually capable of indicating it.
- 02
KPI development
A short, defensible set of indicators tied to objectives, with diagnostic metrics kept separate from the ones used to make decisions.
- 03
Cross channel measurement
Comparable evaluation across paid, organic, local, and offline activity, using shared conversion definitions rather than each platform's own scoring.
- 04
Campaign performance analysis
Analysis of campaign, audience, placement, and creative performance against the role that campaign was actually built to play.
- 05
Website and landing page analysis
Site behavior read as marketing evidence: where attention holds, where journeys stall, and which pages do the converting.
- 06
Lead measurement
Form, chat, and call measurement treated as one lead picture, including the calls that never appear in a website conversion count.
- 07
Ecommerce measurement
Where a store exists, product, category, and revenue analysis alongside the marketing that drove it, rather than in a separate commerce silo.
- 08
Source and channel analysis
Source and medium analysis that survives contact with reality: consistent tagging, direct and referral traffic explained, self reported channels reconciled.
- 09
Funnel and conversion analysis
Identifying where intent is lost, and whether the loss is a targeting problem, an experience problem, or a measurement problem.
- 10
Audience behavior analysis
Behavior across segments, devices, geography, and new versus returning, so performance differences can be explained rather than averaged away.
- 11
Marketing efficiency analysis
Cost per meaningful action by channel, campaign, and audience, with the quality of the resulting action weighed alongside its cost.
- 12
Budget allocation insight
Evidence for where the next dollar should go, including what is saturated, what is underfunded, and what produces volume without value.
- 13
Trend analysis
Trend and seasonality analysis over meaningful windows, so normal fluctuation is not mistaken for a result and a real shift is not missed.
- 14
Data quality assessment
Judging whether the data can be trusted before it is used: tracking coverage, conversion definitions, duplication, filtering, and known blind spots.
- 15
Attribution interpretation
A working view of how credit is assigned across touchpoints, what each platform's rules do to the numbers, and where interpretation must stay directional.
- 16
Executive marketing insight
A written account of what happened, what it means, what remains uncertain, and what we recommend doing about it.
Fig. 03
Weight the metrics that carry meaning.
Not every metric deserves equal attention. Exposure is the easiest signal to generate and the furthest from the objective. Business outcomes are the hardest to capture and the closest to what the organization actually counts. Most reporting inverts this, leading with the numbers that are easy to produce. The correct hierarchy differs by client and by campaign, and not every organization measures revenue, so the top of the ladder is defined during the Define stage rather than assumed.
Exposure and engagement explain movement. Conversion and outcome justify budget.
An awareness campaign and a high intent search campaign should not share one KPI.
Not sure whether your numbers can be trusted
Start with a measurement review
Send us access to what you already have. We will tell you what is being tracked, what is missing, where the numbers disagree and why, and which of your current metrics are worth making decisions on. No obligation afterward.
04
Analytics
Good marketing begins and ends with reliable data. Clean instrumentation, honest attribution, and reporting an executive team can defend, established before the spend and revisited after it.
HUB International
Insurance is one of the most competitive categories in paid search, and HUB International served industries whose needs had almost nothing in common. A business researching employee benefits needed a different message than one evaluating cyber liability, and the budget had to stay clear of claims, careers, and consumer traffic.
Professional services. Advertising.
Insurance is one of the most competitive categories in paid search, and HUB International served industries whose needs had almost nothing in common. A business researching employee benefits needed a different message than one evaluating cyber liability, and the budget had to stay clear of claims, careers, and consumer traffic.
Campaign themes structured by insurance need
Related thinking.
Writing from the team running this work, published as the field changes.
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Common questions.
What is marketing analytics?
Marketing analytics is the practice of measuring marketing activity and interpreting it, so an organization can tell what worked, what did not, and where to invest next.
What does a marketing analytics agency do?
It defines what to measure, checks whether the data is trustworthy, analyzes performance across channels, and turns the findings into marketing decisions.
What is the difference between marketing analytics and web analytics?
Web analytics measures behavior on the website. Marketing analytics measures the whole system around it: channels, campaigns, website behavior, and business outcomes.
What marketing metrics should we track?
Track a hierarchy from exposure to engagement to intent to conversion to business outcome, weighted toward whatever your organization actually counts as a result.
How do you measure marketing across multiple channels?
Agree on shared definitions, tag traffic consistently, reconcile conversions in one place, and evaluate each channel against the role it plays rather than one universal KPI.
What is a marketing KPI?
A KPI is a small set of measurements chosen in advance because they genuinely indicate progress toward an objective and should influence what you do next.
Can marketing analytics show which channels generate leads or revenue?
Yes, with reliable tracking you can see which sources and campaigns are associated with leads, calls, and revenue, though no platform can assign perfect credit for every interaction.
Why do Google Ads, GA4, and other platforms sometimes report different numbers?
Each platform uses different attribution rules, lookback windows, and timestamps, so accurate systems still disagree. Pick one reconciled source for decisions and use the rest diagnostically.
How often should marketing performance be reviewed?
Operational checks run frequently, performance analysis monthly, and strategic review quarterly. Reviewing slow moving channels too often turns normal variance into false conclusions.
What is the difference between analytics and reporting?
Reporting states what happened. Analytics explains why it happened and what should change as a result.
Marketing analytics
Find out what your marketing is actually producing
Tell us what you are running, what you are measuring, and the question you cannot currently answer. We will look at how performance is tracked today, where the picture breaks down, and what it would take to get a version of it you could make a budget decision on.
Call (800) 505-7570. Measuring marketing performance since 1998.