Make data-driven decisions with AI reporting

I was constantly under pressure , juggling multiple projects simultaneously, tracking their performance, and creating insightful reports. All of this is overwhelming, time-consuming, and challenging.

AI for analysis 2024 .

After years of struggling to create reports for Make data-driven my marketing efforts, I discovered how AI reporting can fundamentally change the game—and fuel creativity with data-driven strategies.

Key challenges of traditional reporting in marketing

Throughout my career in marketing, one of the biggest (and recurring) problems I faced was reporting on my work and clearly showing how it relates to business revenue .

I’m sure all marketers would agree that traditional reporting methods are complex and time-consuming , making you feel like a rocket scientist with quite a few flexible elements at your disposal.

Here are some challenges I have experienced and observed in marketing reporting:

For a single report, I spent hours (and sometimes even days ) consolidating, cleaning, and organizing data from multiple tools.

I therefore recognize that a major reason why marketers struggle to build robust reporting is because the process of manual data collection is inefficient and error-prone .

No way to measure ROI

My biggest concern with traditional reporting methods is that many marketing campaigns are difficult to achieve measurable results .

It’s extremely complicated to directly link certain key metrics (like clicks, impressions, and likes) to meaningful business outcomes (like customer acquisition, retention, etc.). While you know how well a campaign performed, you lack sufficient evidence to link it to the results achieved.

my work with various companies, I’ve found that each department often operates in isolation. As a result, customer data is stored in silos and is inaccessible to other teams.

The sales team uses a CRM system, the marketing  smart caching: an accelerator for dynamic content team relies on multiple analytics tools, and the support team works with a customer success platform… and this hinders the marketing teams’ ability to get a comprehensive picture of overall performance .

Limited customization

Traditional reporting tools aren’t easily customizable to meet specific reporting needs. I tried to build my reporting system around my goals, but I could n’t fully customize my tools to get the tracking metrics I needed.

This lack of flexibility is another key reason why marketers have to spend extra time and effort on data-driven reporting.

Meaningful data analysis

After trying out several reporting tools, I can conclude that most of them simply process and visualize data. They don’t provide contextual guidance on what actions to take based on the information.

I spent most of my time interpreting  at scale and documenting key findings to help everyone involved make

Traditional reporting presents numerous challenges for marketers , increasing the pressure on them to stand out with innovative campaigns in crowded markets.

The good news is that resources like HubSpot for Marketers  text services offer a variety of tools to help streamline marketing reporting. From multi-touch revenue attribution to customer journey analytics, they help you easily measure and optimize marketing investments.

But that’s not all – now we’re also using AI .

It’s exciting to see how AI techniques can change things in reporting and significantly improve efficiency for marketing teams.

Let’s take a look at the key benefits and use cases of AI reporting.