“Data is the new oil” was a very popular claim a couple of years ago. In today’s world, being a data-driven marketer is a must. However, with more data than ever, putting ‘this oil’ to work is getting harder, as the recent Forbes article uncovers - “Why most marketers today are data janitors”.

Many people in the industry, especially leaders who are not as involved in day-to-day campaign optimization, often believe this is a problem for small businesses, as more mature companies have well-governed dashboards. The reality is far from it. In fact, this article focuses on the reality of large B2C scale-ups and enterprise performance marketing teams.

Wait - but aren’t dashboards enough?

All scale-ups and enterprise performance marketing teams have access to well governed BI dashboards (e.g., Tableau, PowerBI, Looker, Metabase, etc). These are created and maintained by the data team, often including internal attribution data. These dashboards are a great way to monitor key business metrics and slice and dice by core dimensions (e.g., country, channel). They meet the needs of management and C-suite executives, but are insufficient for operational use cases that require more granularity and flexibility. This is where “self-service dashboards” break, leading to the operational analytics gap.

The 2 main root causes are data granularity and flexibility:

1. Data granularity: dashboards typically go down to the campaign level (sometimes ad level). It lacks granular data for use cases like search pacing, creative performance, and ad quality score. So day-to-day business happens outside dashboards;

2. Flexibility: dashboards are static. Marketers can’t easily drill down, add/edit metrics, dimensions, etc. Changes have to go through the data team, often taking weeks or months. Waiting this long is not a viable option, thus marketers turn to spreadsheets;

As a result, for most needs of performance marketers, BI dashboards simply aren't enough. Deep dives take place on ad platforms, GA, spreadsheets, etc. Data is spread across multiple platforms and is not ready for analysis. This leads to the biggest challenge: data preparation.

The biggest challenge: Data Preparation

For granular analysis, where dashboards are not enough, marketers spend a significant amount of time in data preparation. How big is this problem? 2 key stats from the Forbes article:

• 41% of marketers spend more than half of their time wrangling data for campaigns and analysis;

• Over a third dedicate between 25% to 50% of their work hours to these tasks.;

  
  

Integrating multiple data sources it’s the main challenge. Pulling data from multiple sources, reconciling, formatting and cleaning it takes up much time. This challenge becomes more difficult as the volume and complexity of data increases (i.e. more channels, more campaigns, etc.).

Let’s look into real examples of large B2C scale-ups and enterprise performance marketing teams.

Real stories - examples

Every week, our team interviews 2-3 performance marketers at B2C scale-ups and enterprises to learn more about marketing reporting and analytics workflows.

When asked about the most frustrating and annoying part of their job, most performance marketers mention manual data preparation and reporting. Sharing below 2 representative examples from the market research study:

The business impact

The cost of this challenge can be segmented into (1) Impact on marketing efficiency (ROAS), (2) Direct cost (time).

• Direct impact on marketing efficiency - teams miss out on optimization opportunities or act too late due to these workflows. In addition, it also affects decision quality due to errors and mistakes coming from all these manual workflows (e.g., spreadsheets formulas).

There’s also a psychological effect on the data-driven culture: if preparing data takes a significant amount of work before it can be analyzed, taking action on insights becomes more of a challenge —both in the amount of time there is available to do it, and considering how much mental energy marketers may have to act on it. Thus marketers often give up on running more deep dives, leading to missed optimization opportunities.

• Wasted time in manual data preparation and reporting (3-7 hours per marketer per week based on our market study), which takes away from creative and strategic work. As the marketing landscape changes faster than ever, staying up-to-date on key trends and new tactics is a must. However, “data janitors” struggle to find time for this.

The impact is clear. Let's explore how to fill this gap. There is a lot of excitement around AI – is this the solution?

Will AI solve this problem?

Using AI for deep analytics requires having data “ready to be analyzed” (i.e., the most granular data centralized and streamlined in a single place). This is still the biggest challenge, so AI is not yet the silver bullet. Having said this, AI can help streamline the data preparation process (i.e., cleaning, integrating and formatting data), but it's unlikely to take care of this automatically anytime soon.

Solving this problem requires addressing its root causes.

Fixing the root cause: reporting and analytics workflows

Resolving this issue requires addressing the root causes and consequently changing operational reporting and analytical workflows. Pulling together granular data from all sources and making it ready for analysis is the biggest challenge.

Thus closing this gap requires giving access to the most granular data from all sources (channel, analytics and internal) in a single place. Not just cost data from channels, but also analytics data (attribution, CLV, etc) and internal data (budgets and targets). And get it ready to analyze without any effort.

Imagine this: your Tableau/Looker/Power BI dashboards would have all the most granular data and be super flexible like spreadsheets (without SQL). This would eliminate all the manual data preparation and reporting work, enabling you to focus on generating insights and taking actions, right? Problem solved!

How to close the gap: combine the scalability of BI with the flexibility of spreadsheets

AI and automation tools partially address the problem by speeding up the manual process. This alleviates the problem, but doesn't solve it. The only way to bridge this gap is to eliminate any type of data preparation work, allowing marketers to explore the most granular data flexibly, all in one place.

Streamlining this process contributes to unlocking insights and enables marketers to reclaim valuable time to focus on what truly matters.

Curious how the most sophisticated data-driven marketing teams overcome this challenge? Schedule some time with us.