How Can Marketing Technologists Overcome Challenges in Analyzing Marketing Data?
Martech Interviews
How Can Marketing Technologists Overcome Challenges in Analyzing Marketing Data?
In the intricate world of marketing analytics, professionals from CEOs to Digital Marketing Managers face unique challenges. From navigating the GA4 transition to embracing data-driven storytelling for impact, we've compiled six expert insights on overcoming hurdles in marketing data analysis.
- Navigate GA4 Transition with Expert Help
- Integrate Data for Actionable Insights
- Combine Fast and Slow Data for Branding Impact
- Measure Top-of-Funnel Efforts Creatively
- Implement Data-Cleaning for Accurate Insights
- Embrace Data-Driven Storytelling for Impact
Navigate GA4 Transition with Expert Help
One challenge I've had while analyzing data this year has been the transition from Universal Analytics to GA4. This transition has been tricky because I felt like UA was intuitive and had everything right where I liked it for SEO data. The way I've overcome this has been to ask lots of questions, watch videos, and rely on SEO experts in my network who have more experience with GA4 than I do. Certain metrics have been renamed or moved around, so relearning where to find things takes time.
Integrate Data for Actionable Insights
One particular challenge we faced while analyzing marketing data for an insurance client was managing and making sense of the vast amounts of data from multiple sources. The data was fragmented, coming from social media, email campaigns, website analytics, and CRM systems, making it difficult to derive actionable insights.
To overcome this challenge, we implemented a centralized data management platform that integrated all these sources into a single system. By using advanced data analytics tools, we improved data organization and analysis efficiency by 50%. This approach allowed us to identify key patterns and trends, resulting in a 35% increase in campaign performance.
The key takeaway from this experience was the importance of a robust data integration and management strategy, enhancing our ability to deliver precise, data-driven insurance agency marketing strategies and achieving higher ROI for our insurance clients.
Combine Fast and Slow Data for Branding Impact
A huge challenge for marketers is how to measure and analyze the indirect effect, or branding effect, that marketing has—besides the direct campaign performance effect. As it can take weeks or even months sometimes from exposure of an ad to conversion.
When we looked at this problem, we realized that you need to evaluate and measure what you do using both "fast" (digital) and "slow" (offline) data. By combining the two, we could both understand who we reached with our branding, the direct metrics on campaign performance level, and the long-tail effect on organic and non-measurable visits to the digital domain.
This made it possible for us to interpret the website traffic based on a unified audience metric and compare previous weeks and months of campaign audience reach with the effect on the website traffic audiences.
We created a way to measure and enrich the campaign data with offline data sources which could tell us reach in the targeted audiences, compared to the market, as well as the direct campaign performance. Over time, we could also see audience effect on the website traffic, indicating the branding effect.
Disclaimer: As the measured audience effect on site is not directly attributable to a specific campaign, it is an inferred effect that we measure by understanding the reach of the marketing and comparing it to the visitor audiences, and not an absolute metric like a click.
Measure Top-of-Funnel Efforts Creatively
We have long wrestled with how to analyze the performance of our top-of-funnel efforts. Specifically, out-of-home, CTV, and YouTube.
The first challenge we had to overcome was our own expectations. We had gotten comfortable with the performance of our Meta and Google Ads campaigns. It took a lot of work to build understanding with key stakeholders. We all had to get comfortable with the fact that our goals of breaking into new markets necessitated new strategies and that those new strategies would be harder to measure performance and would necessarily have higher CACs.
The next challenge we had to overcome was finding ways to measure the performance of the campaigns. We believe that as a marketing team, we have a duty to use our budget wisely and have been very transparent in reporting our performance, both good and bad. We felt it was imperative to have the ability to show what effect our top-of-funnel advertising efforts were having, despite the lack of direct click attribution. We had to get clever, think outside the box, learn SQL and Python, and get into the weeds of our subscription data.
Implement Data-Cleaning for Accurate Insights
One common challenge is data quality. Early on, I realized inconsistent formatting or missing entries were creating misleading insights. To overcome this, I implemented a data-cleaning process that ensured all information was accurate and standardized. This allowed me to generate reliable reports and identify true trends within the marketing data.
Embrace Data-Driven Storytelling for Impact
As a Project Manager, I've embraced a data-driven storytelling approach. By crafting compelling narratives around my findings, I transform raw data into actionable insights that resonate deeply with the organizations I collaborate with. This method simplifies complex information and catalyzes informed decision-making, driving effective strategies and optimizing campaign outcomes.
