An email from Google landed in my inbox just over a week ago with a headline that immediately got my attention:

“A complete view of your marketing performance.”

The message explained that Google Analytics’ Campaign Data Import can bring campaign data from Meta, TikTok and other advertising platforms into Google Analytics at no additional cost, enabling marketers to see how their wider marketing budgets are performing in one place.

At first glance, this might sound like another useful but incremental Google Analytics update.

However, it is potentially much more significant than that.

For years, one of the most persistent challenges in digital advertising has been fragmentation. Google Ads has its own reporting environment. Meta has Ads Manager. TikTok, LinkedIn, Snap, Pinterest, Reddit and every other platform have their own dashboards, metrics, definitions and attribution logic.

The result is that a marketer running campaigns across several platforms rarely gets one clean and consistent view of what is really happening.

Instead, teams export spreadsheets, reconcile naming conventions, argue about attribution, manually build reports and try to work out which platform is actually contributing to sales, leads, registrations or other meaningful business outcomes.

Large organizations can invest in data warehouses, business intelligence platforms, specialised connectors, analytics engineers and dedicated marketing science teams to solve this problem.

Most small and medium-sized businesses cannot and this especially matters in markets like Kenya and the the rest of Africa. 

Many digital agencies also struggle with the cost and complexity of creating a reliable cross-channel measurement layer for every client.

This is why Google Analytics’ evolving combination of cross-platform campaign-data imports and Gemini-powered conversational analytics could be a genuine game-changer.

What Has Google Analytics Actually Changed?

Google’s Campaign Data Import allows marketers to bring aggregated campaign cost, click and impression data from advertising platforms outside Google into Google Analytics.

Google Analytics can then combine this imported campaign data with the revenue and key events already being measured across a business’s website or mobile application.

This makes it possible to calculate and compare metrics such as non-Google cost per click and return on non-Google advertising spend by campaign, source and medium.

The important shift is that Google Analytics is no longer looking only at what happened after someone arrived on a website or app. It can also hold more of the media-investment context that brought the person there.

Google currently supports automated daily imports from:

• Meta.
• TikTok.
• Snap.
• Pinterest.
• Reddit.

For other advertising platforms and data environments, campaign data can also be imported through sources including Google Sheets, CSV files, BigQuery, Amazon S3, Amazon Redshift, Google Cloud Storage, MySQL, PostgreSQL, Snowflake, SFTP and HTTPS.

This does not mean that Google Analytics suddenly replaces all the native advertising dashboards.

It does mean that it can become a far more useful cross-channel measurement hub.

A business could, for example, compare media cost and campaign traffic from Meta and TikTok with purchases or qualified leads measured on its website. An agency could use a more consistent view to discuss which channels are producing business outcomes rather than merely which platforms are reporting the most clicks.

That is an important distinction.

The Gemini Layer Could Be Even More Transformative

Bringing data together is only half the problem.

The other half is helping people understand it.

Google Analytics has always been powerful, but it has not always been easy to use. Even experienced digital marketers can find themselves navigating reports, dimensions, filters, events, explorations and attribution settings before they can answer what appears to be a fairly simple business question.

Google is now addressing this through Ask Advisor in Google Analytics, an agentic conversational experience powered by Gemini models.

Ask Advisor is designed to let users ask questions about their Google Analytics property in natural language. According to Google, it can surface high-level performance insights, generate visualisations for specific metrics and dimensions, investigate possible causes of performance drops or spikes, explain how to complete tasks and identify possible optimisation opportunities.

In practical terms, a user could ask questions such as:

• How is our customer acquisition performing this month?
• Which paid channels generated the strongest return on advertising spend?
• Why did online revenue fall last week?
• Which campaigns drove the most purchases from mobile users?
• What should we investigate before moving more budget into a particular channel?

This is potentially transformative because it changes the interface between people and data.

Instead of requiring every marketing manager, entrepreneur or account executive to know exactly which report to open, which dimensions to select and which filters to apply, they can begin with the business question they actually want answered.

The analytics platform can then help them find the relevant information.

Ask Advisor is currently in beta. Google says it is available only to eligible properties using English, processes information at the individual property level and may still have capability limitations. It should therefore not be presented as an infallible analyst or as a feature that every Google Analytics user can access today.

However, the logic is very clear as Google Analytics is becoming more conversational, more accessible and potentially far more useful to non-technical decision-makers.

Why This Matters For SMEs In Kenya & Africa

For me, the most exciting part of this development is not what it offers a multinational company with a sophisticated marketing analytics function.

It is what it could make possible for a growing business in Nairobi, Mombasa, Kampala, Kigali, Dar es Salaam, Lagos, Accra or Johannesburg that does not have a data engineering team.

Consider a Kenyan e-commerce business running Google Search campaigns, Meta campaigns and TikTok campaigns at the same time.

Until now, getting a genuinely useful view of performance across those platforms could involve several dashboards, exported reports and a considerable amount of spreadsheet work. Even then, each platform might claim credit for conversions using a different attribution window or methodology.

Therefore, using a properly configured Google Analytics property, consistent campaign tagging and reliable revenue or conversion tracking, the business can bring more of that campaign information into one measurement environment.

It can then ask more useful questions:

• Which platform is generating the most revenue relative to what we spend?
• Are we paying for large volumes of traffic that do not convert?
• Which campaigns are assisting customer journeys even if they do not receive the final conversion credit?
• Where should we reduce, maintain or increase our advertising budget?
• Did the decline in results come from a campaign, a landing page, a device segment or the checkout journey?

These are not merely analytics questions.

They are business questions.

That is why the combination matters.

Campaign Data Import can reduce part of the data-fragmentation problem. Ask Advisor can reduce part of the skills and accessibility problem. Together, they have the potential to give smaller organizations a level of digital marketing intelligence that previously required expensive tools, specialist integrations or considerable manual effort.

Why Digital Agencies Should Also Pay Attention

This development could be equally important for digital and performance marketing agencies.

Agency reporting has often been too platform-centric. A Meta team presents Meta results. A search team presents Google Ads results. A social media team reports reach and engagement. The client then has to determine how all of this connects to overall business performance.

That is no longer good enough.

Clients increasingly want to know what their total marketing investment produced, which channels worked together and what should happen next.

A stronger Google Analytics measurement layer could help agencies move from compiling reports to interpreting performance.

That creates several opportunities:

• Faster and more consistent cross-channel reporting.
• Better comparisons between media cost and business outcomes.
• Earlier identification of unusual changes in performance.
• More informed budget-allocation conversations.
• Clearer explanations for non-technical client stakeholders.
• More time for strategy, experimentation and optimisation instead of spreadsheet maintenance.

This does not remove the need for analysts.

If anything, it makes good analysts more valuable.

The repetitive work of locating reports and assembling basic views can increasingly be supported by automation and AI. Analysts can spend more time validating the data, challenging assumptions, understanding customer behaviour, designing experiments and translating findings into decisions.

AI can help surface an answer.

A skilled analyst must still determine whether it is the right answer, whether the underlying data is credible and what the business should do about it.

A Complete View Does Not Mean A Perfect View

The phrase “complete view” is powerful, but marketers need to use it carefully.

Google Analytics imports daily aggregated campaign metrics such as cost, clicks and impressions. It does not necessarily reproduce every creative, placement, audience, bidding or platform-specific diagnostic available inside each advertising platform.

The automated imports also run daily, and Google notes that imported data can take up to 24 hours to appear. This is therefore not the same thing as a literally real-time, tick-by-tick advertising command centre.

Attribution differences will not disappear either.

Meta, TikTok, Google Ads and Google Analytics may use different attribution windows, identity signals, consent assumptions and approaches to view-through and click-through conversions. The numbers will not always match, and a discrepancy does not automatically mean that one system is wrong.

Most importantly, no AI layer can rescue poor measurement foundations.

If campaigns are tagged inconsistently, key events are badly configured, revenue is missing, currencies do not match or internal traffic and referral issues are ignored, the resulting insight will be unreliable — however confidently it is presented.

The old analytics principle still applies:

Garbage in, garbage out.

Gemini may make the output easier to understand. It does not make weak input data accurate.

What Businesses & Digital Agencies Should Do Next

The right starting point is not to connect every platform immediately.

It is to get the measurement foundation right.

1. Define the business outcomes that matter. These may include completed purchases, qualified leads, applications, bookings, subscriptions or other events that genuinely create value.
2. Audit the Google Analytics property and confirm that the relevant events, key events, revenue values, referral exclusions and consent settings are correctly implemented.
3. Establish strict UTM and campaign-naming standards across every advertising platform. Google requires imported campaign information to match the campaign parameters recorded by Google Analytics. Even differences such as “Facebook” and “facebook” can break the match.
4. Ensure that imported campaign costs use the same currency as the Google Analytics property.
5. Connect one or two priority platforms and test the data before scaling the setup. Review import health, match rates, missing data and discrepancies against the native platform reports.
6. Develop a standard set of management questions for Ask Advisor where the feature is available. Do not ask only what happened. Ask why it may have happened, which segments were affected, what changed from the previous period and what deserves further investigation.
7. Finally, and most importantly, as in all things AI enabled or integrated, keep a human in the decision loop.

Budget reallocations, campaign pauses and strategic changes should not be made blindly because an AI-generated answer sounds plausible. The best results will come from combining reliable data, experienced judgement, commercial context and faster AI-assisted analysis.

From Digital Analytics To Accessible Decision Intelligence

I wrote about the need to get serious about digital marketing measurement in Africa as far back as 2011.

Fifteen years later, the technology has become dramatically more powerful — but the underlying challenge remains familiar.

Businesses do not need more dashboards for the sake of dashboards.

They need a clearer understanding of what is working, what is not, why performance is changing and where the next shilling of marketing budget should go.

Google Analytics’ Campaign Data Import is important because it can bring more of the fragmented cross-channel picture together. Gemini-powered Ask Advisor is important because it can make that picture easier for more people to understand and interrogate.

The combination could move Google Analytics from being seen primarily as a website and app reporting tool towards becoming a much more accessible marketing intelligence and decision-support platform.

For SMEs, this could lower the cost of getting meaningful cross-channel insights.

For digital agencies, it could reduce manual reporting and create more time for strategic analysis.

For marketing leaders, it could make performance conversations more consistent, more commercial and less dependent on whichever platform happens to be presenting its own version of success.

That is potentially a very big deal.

The technology will not remove the need for sound measurement, data governance or human judgement.

But it could make high-quality marketing intelligence available to many more businesses than ever before.

That may be the real game-changer.