Marketers are often asked to do this Achieve more with less. I was there too.
I struggled with the constant pressure of juggling multiple campaigns, tracking their performance and presenting insightful reports. This process is overwhelming, time-consuming, and full of challenges.
After years of struggling to create reports for my marketing campaigns, I discovered how AI reporting can truly transform the process – and boost creativity with data-driven strategies.
In this article I will discuss:
Key challenges for marketers in traditional reporting
Throughout my decades-long career in marketing, one of the biggest (and repeated) challenges has been reporting my work and attributing it to sales.
I’m sure every marketer agrees that traditional reporting methods are complex and time-consuming. Reporting feels like rocket science, with so many moving parts.
Here are some challenges I have encountered and observed in marketing reporting.
- Laborious data collection. I’ve spent hours (and even days) consolidating, cleaning, and organizing data from various tools to create a report. I realized that a major reason marketers struggle to build a robust reporting structure is this inefficient and error-prone process of manual data collection.
- Inability to measure ROI. My biggest concern with traditional reporting methods is the lack of measurable results in many marketing campaigns. It’s much harder to directly map specific top-level metrics (like clicks, impressions, and likes) to meaningful business outcomes (like customer acquisition, retention, etc.). They know how well a campaign worked, but they don’t have enough evidence to link it to the results it achieved.
- Isolated data. Having worked with several B2B organizations, I have observed that each department often works in isolation. As a result, customer Data is isolated and inaccessible to every team. The sales team uses a CRM system, the marketing team relies on multiple analytics tools, and the support team is working on a customer success platform. This makes it difficult for marketers to get an overall view of their performance.
- Limited customization options. Traditional reporting tools are not easily customizable to meet your reporting needs. I tried backwards tracking my goals to set up my reporting system, but I couldn’t fully customize my tools to track the metrics I needed. This lack of flexibility is another big reason marketers need to invest additional time and effort into data-driven reports.
- Meaningful data interpretation. After trying several reporting tools, I can conclude that most tools only process and visualize data. They do not provide contextual guidance on what actions to take based on the data. I spent most of my time interpreting data at scale and documenting key insights to help stakeholders make data-driven decisions.
The traditional reporting structure is fraught with challenges for marketers. And it only adds to the growing pressure marketers face to stand out in crowded markets with innovative campaigns.
That’s why I’m excited to discuss how AI reporting methods can change the game and maximize efficiency for marketers. Let’s look at the key benefits and use cases of AI reporting.
5 Key Benefits of AI Reporting for Marketers
Our AI Insights for Marketers report. shows that almost half (45%) of marketing leaders say AI tools make their employees more productive.
Although I’ve seen marketers leverage AI for use cases like content creation and automation, I believe that’s just the tip of the iceberg. The real game-changer is the ability to use AI tools for end-to-end data analysis and performance tracking.
Here are five key areas where I believe AI reporting will make marketers’ lives easier.
1. Optimized data collection and processing
Ask any marketer what they like least about their role and they will say: Collect data.
As I said before, collecting data manually is a slow and tedious process. Switching between your social media analytics, email marketing dashboards, CRM, and other tools can sometimes feel like the Stone Age.
With AI-powered reporting, you can easily eliminate this laborious work and automate data collection. These AI marketing tools integrate seamlessly with your target channels and collect data in real-time. Additionally, you can configure these tools to process and analyze the data.
This AI automation for reporting can significantly reduce manual workload and free you up to focus on more strategic tasks.
2. Improved ability to measure ROI
One of the biggest problems for every marketer I know is directly tying their efforts to business results.
Because traditional reporting methods focus on top-level metrics (like views, clicks, and impressions), you don’t get a clear picture of how your marketing efforts are driving revenue growth.
Instead, AI reports deliver deeper insights through advanced attribution models.
AI tools can track the entire customer journey across different channels and touchpoints. This gives you clarity on how customers make purchasing decisions and what moved them forward in the marketing funnel.
This advantage is also visible in ours AI Marketing Insights Report: 39% of marketers believe AI tools help make informed decisions based on performance.
3. Break down data silos
Data silos can arise in any organization when data is stored separately for different teams and use cases. This doesn’t give you a consistent view of customer behavior or marketing performance.
AI-powered reporting can break down these silos by integrating across multiple platforms to get real-time data and generate a detailed report.
Actually, 44% of marketers believe AI is very effective in performing data analysis, and 70% use these tools to improve their data analysis workflows.
Why? Because AI tools offer integrated dashboards to visualize cross-channel insights without manual effort. You can automatically compile and cross-reference data from different touchpoints to provide a more comprehensive picture of campaign performance.
4. Highly customizable reporting
One of the biggest benefits of AI reporting is the ability to break through the rigid reporting formats of traditional methods and build a flexible, goal-specific setup.
Instead of following irrelevant templates, Using AI-powered reporting, you can customize your reports to track metrics aligned with specific campaigns or strategies.
Jessica ApothekerHead of Marketing and CMO at Boston Consulting Group, explains why companies need to build such a customized reporting setup.
In her TED talkShe emphasizes that marketers should have the right AI tools to track customer behavior, predict results, and thoroughly analyze each campaign. This continuous feedback loop can significantly improve marketing strategies and performance.
Apotheker shows an example to illustrate the results:
“A consumer goods company I worked with used these tools to gain a ‘Left AI advantage’ and built a team of over 30 experts to develop and customize these solutions. They also trained the entire organization.
This allowed marketers to assess which audience-creative combinations were performing well in the market, determine which products resonated with which consumers, and monitor the evolving marketing funnel. This results in a highly adaptable and effective marketing approach.”
5. Improved data storytelling
I’ve seen time and time again how difficult it is to convert raw data into meaningful insights using traditional reporting tools. I strongly believe that these reports full of numbers and charts often don’t tell a compelling story. They do not explain why certain metrics are important and how they impact strategy.
That’s why I’m experimenting with AI reporting tools to interpret data, provide contextual insights, and support the decision-making process.
AI tools use Natural Language Processing (NLP) to create a narrative around your data. They can explain trends, highlight gaps and opportunities, and even answer specific questions you have.
Simply put: you can use it AI reporting tools to quickly understand data and gain actionable insights.
4 Applications of AI-Powered Reporting for Marketers
I’ve spent the last few months exploring the potential of AI reporting tools.
In addition to testing some tools for my workflows, I also spoke to my marketing colleagues to learn how they are using AI in their reporting setup and what benefits they have seen so far.
I’ve put together a list of four use cases AI in digital marketing to maximize reporting efficiency and make data-driven decisions.
Use Case #1: Predictive Analytics for Campaign Performance.
I think AI-powered predictive analytics can transform how marketing campaigns are prioritized and executed.
You can use historical data on campaign performance metrics and seasonal patterns to predict future results. You can also use this data to share further contextual details about your planned campaign. Then, these AI tools can predict whether that campaign will perform well or poorly.
Additionally, AI tools can simulate scenarios based on variable factors such as audience segments, budgets, and more.
For example, what happens if you allocate 20% more of your budget to social media ads in a specific demographic? AI can predict the possible outcome, enabling better decision making.
See AI reporting in action
Andy CrestidonaCo-founder of Orbit Media Solutions, uses ChatGPT to analyze campaign performance across the funnel and predict future performance.
He downloads the latest reports from his email marketing platform and Google Analytics. It then adds this data to ChatGPT to combine the data sets and derive insights.
Here’s an example of how he instructs the tool to merge and organize the dataset.
He also uses ChatGPT to derive insights from this data set and visualize it in different ways. For example, he asked the tool to create a chart showing the performance of various topics in the email marketing channel.
Use Case #2: Real-time insights for content optimization.
As a content marketer, I have focused heavily on using AI to create more efficient workflows.
However, it was only recently that I discovered the power of AI tools to measure performance and optimize content for better results.
I use AI tools to track metrics like engagement, bounce rate, and conversion rate.
This real-time data for content posted on different channels makes it clear whether a topic is a hit or a miss. This allows me to improve underperforming content or redirect resources from one campaign to another.
I also rely on HubSpot SEO marketing software Optimize content. The tool analyzes the content of each website to provide suggestions for improvements in real time.
Each advisory identifies the number of pages affected by an error and provides a clear reason why that error is important. It also shows you the impact of each recommendation, so you can prioritize high-impact tasks.
Use case #3: Audience segmentation and personalization.
AI can analyze huge data sets to find patterns that you would naturally miss.
Marketers can use this feature to improve audience segmentation and deliver more targeted messages. For this reason 34% of marketing managers say that AI leads to more personal customer experiences.
For example, AI tools can analyze all available customer data and create segments based on their behavior and preferences. You can also use these tools to understand how each segment interacts with your brand.
Based on this audience segmentation, you can then personalize the customer experience and offer tailored solutions and offers depending on each customer’s interaction history and journey.
Sarah Cornettan AI consultant, shares how she implemented an AI solution for marketing in the banking sector to provide personalized customer experience and targeted communications. In a conversation about the State of AI-powered marketingshe shares a case study of her work.
“The solution used identity resolution to collect historical data about a customer, such as: B. the products you have with us, your digital touchpoints and real-time activities such as navigation on our website. By leveraging this real-time data, we were able to identify the most relevant communications at any given time.
With thousands of potential discussion topics, the AI system would analyze triggers to deliver personalized messages, be it a next-best action, an upsell or a cross-sell offer, all tailored to grab attention and contextually to provide the most relevant experience.”
Use Case #4: Attribution Modeling and ROI Tracking.
A common challenge for me is identifying the most effective marketing channels. With AI-powered attribution modeling, this becomes much easier. With AI reporting, you can pinpoint and analyze every touchpoint in the customer journey instead of using traditional attribution models.
With a multi-touch attribution approach, you can honor each touchpoint and provide a more realistic picture of the impact of each channel. This level of granularity allows marketers to focus on the most profitable touchpoints.
Additionally, you can leverage multi-touch attribution data to predict ROI for future campaigns. It improves predictive analysis and streamlines your marketing investments.
My top tips for getting started with AI reporting
Okay, are you ready to give AI reporting a try? Here are my top tips to get you started.
- Automate data collection. One of the easiest ways to integrate AI into your reporting setup is to automate data collection and processing. Integrate AI tools into your existing tech stack to combine information from multiple platforms and process data into a single dashboard.
- Audience segmentation. Use AI to analyze customer data and divide your audience into micro-segments. It will help you truly understand your customers based on behaviors, preferences, pain points, and other parameters.
- Predictive analytics. Let AI tools analyze the probability of success of each new campaign idea and prioritize ideas based on these predictions. You can also use these predictive insights to set campaign budgets and realistic results to maximize ROI.
- Data storytelling. Let AI interpret and decipher complex data to derive meaningful insights. Create a narrative with your data that aligns with business goals and makes it more accessible to stakeholders.
- Attribution model. When you’re ready, replace your existing attribution model with an AI-powered multi-touch model. Get an overview of your customers at every touchpoint and track interactions across different channels with a unified reporting setup.
Remember that integrating AI into your reporting workflow should be a gradual process. I encourage you to experiment and explore the possibilities to find where AI tools perform well for your business.
Use AI reports to improve your marketing strategy.
I get it: reporting is a chore. You’re tired of exporting data from half a dozen platforms and consolidating it in one place, then spending hours extracting insights from it. Feeling the same frustration, I started using AI tools for reporting to reduce the workload and make this process more efficient.
My biggest takeaway from researching this article is that AI reporting is changing the way marketers engage with data. It makes data more accessible for decision-making and strategy development, allowing you to plan campaigns based on facts rather than just trusting your gut.