Three steps to meaningful marketing analytics for the CMO

Here’s the marketing analytics problem we hear from our customers every day: “Our marketing team does a solid job. But we’re not grounded in data as much as we should be. The data that we do look at is very siloed.”

These are the thoughts of just one forward-thinking CMO we’ve been speaking to, from a global provider of smart products for the home. But in reality, we’re hearing it all the time.

And here’s why.

1. There’s not enough sharing going on between marketing and other channel-owners.

2. There’s no effective way of accessing or visualizing the data they do have.

3. Stakeholders who need to share or access the data don’t always have the technical ability to do so.

In the words of the CMO: “We want to transform our creative marketing team into a more analytics-based team.” This is because the team needs more granular visibility into channel performance in order to inform future marketing activity, but also, to share the right information with other business teams and the leadership team.

But without the right tools in place, they simply can’t access this data in any meaningful way.

“All of our channels – paid ads, social, email marketing, web – are handled independently by our channel-owners, but there’s a disconnect between these data sources.” For example, one team might be using Google Analytics to aggregate data for Google Ads, but no-one else can access this data set. Even when the data is shared, it’s likely been manipulated in such a way that is not useful to other stakeholders.

So, how can teams maximize their marketing analytics?

1. Create a culture of data sharing

Within a marketing team, even those who sit on the ‘creative’ side need to be informed by the data coming into the business; they need to be metrics-driven. However, whereas independent channel-owners can effectively optimize their own campaign performance, as soon as the data needs to reach the next level – for instance the CMO needs to present marketing spend to the CEO – they find they are only able to share one piece of the puzzle at a time, which hampers any efforts for strategic decision-making at the board level.

As the CMO describes: “Any channel-owner could speak to their own performance. But ask someone who is two tiers above them, working on overall strategy, and we’d likely struggle to explain what our performance looks like”. However, if everyone understands how the data they are using affects other teams across the organization, they will be far more likely to share it.

2. Bridge the gap with a single source of truth

What marketing teams need is a single source of truth, or as we call it, “foundational data”. This allows each channel-owner – from the analytical to the creative – to access different cuts of the organization’s data according to their specific marketing KPIs (for instance, spend vs CTR, or conversion per channel). And to visualize it in a way that is clear and useful to them.

With this, they can finally answer questions such as: “How can we improve conversions by a certain percentage?” or “which marketing channels should we scale up or cut back on?”.

3. Expedite with automation

Bridging the gap between aggregating disparate data sources and getting it to a point where everyone can run reports according to their own benchmarks requires an inordinate level of engineering, which inevitably gets pushed to the bottom of the agenda, time and time again.

With engineering teams often overstretched with other mission-critical priorities across the business, more and more CMOs are using automated no-code tools that fit neatly into the existing data stack (along with their EDW and data visualization tools) and pull data into that single source of truth. This unified data then becomes trusted and useful for the CMO to run informed investment meetings with the CFO. And, the marketing team can leverage it for fine-tuning their campaigns and channel strategy.

These tools should be integration-agnostic, so whether marketers are using Snowflake, RedShift or BigQuery to house their data – or whether they’re using Tableau, Looker or Power BI to visualize it – they can plug in and go, using pre-built connectors that can swiftly sync up with existing tools.

By using a data automation engine, CMOs can finally let their engineering team get back to other mission-critical initiatives, while building their own strategic data asset to power more meaningful marketing analytics.