How can you share marketing analytics data with other analysts and marketers?

"Let the data tell the story" Quite often, in the zeal to be data-driven, clients can say the above-mentioned phrase. However, nothing can be further from practicality, as I found from my very first engagement on a marketing analytics project. The Client (a Fortune 100 company) wanted to do customer segmentation and shared the data. In my naivete, I started working on the data not knowing why we were doing it (and not bothering to ask!). Multiple iterations and exasperated client interactions later, we both realized the need to fix what the outcome of the segmentation was supposed to be. While we ended up with an insightful solution, we could have definitely avoided the initial hard phase. Sometimes we learn from hindsight!

The success of your business hinges on setting clear goals and understanding your audience. Goals provide direction, purpose, and measurable outcomes, while audience insights empower businesses to cater to their customers' needs effectively. When these two elements intertwine, they form a powerful synergy that propels businesses toward sustainable growth, customer loyalty, and enduring success. In essence, knowing where you're headed and who you're serving is the winning formula for businesses that aim to thrive in the long run.

Selecting the right data format and platform should align with your data's characteristics, accessibility needs, scalability, security, integration, analytical tools, cost, compliance, backup, and user-friendliness. A well-informed decision in these areas can greatly impact the efficiency and effectiveness of your data management and analysis efforts. First, analyze the type of data you have. Is it structured (e.g., in tables), semi-structured (e.g., JSON, XML), or unstructured (e.g., text, images)? Choose a format that suits your data's nature.

Select a chart or graph type that best represents the data's patterns and relationships, whether it's a bar chart for comparisons, a line chart for trends, or a pie chart for proportions. Avoid clutter by presenting only essential information. Use labels, legends, and colour sparingly to highlight key points and reduce visual noise. Include clear titles, axis labels, and annotations to help viewers understand the data's significance and context. Contextual information enhances interpretation. Maintain a uniform style and colour scheme throughout your visualizations to make them more visually appealing and easier to comprehend.

- When we discuss our data it shouldn't be a lecture. It should be like telling a story where numbers intersect with real world impact. The unexpected twists in the plot? They represent the trends we identify leading to points where we take actions. - Captions and summaries are not just additions. They serve as guiding lights in our data narrative helping audience understand the idea without getting lost in a sea of numbers.

Set expectations correctly: data isn't as precise as it may appear at first glance. With the availability of easy-to-use marketing data dashboards, a lot of non-technical & non-marketing leaders from the C-Level have gotten the impression that every user, every ad view and every click on a Site or App can be precisely tracked. The truth is: it's not the case. Even if a report gives an exact number, this number is just an estimation. Wether its Website tracking (limited by privacy settings), or social content view numbers (often inflated by social networks) - don't be surprised if numbers are not fully accurate. It's important to set this expectation within the company: numbers are powerful, but not 100% precise!