How can you present marketing analytics projects in your portfolio using data visualization tools?

In my experience, I have used both Tableu and Power BI. The biggest advantage of these tools is that once the setup is done, it literally takes seconds for the visualisations to load as opposed to massive excel files. For any Marketing department, decisions need to be made fast in todays ever changing customer dynamics and this is why it is important to implement such tools.

If you have an online business that most of your data is in Google platforms like Google Analytics, Google Search Console, Google Sheets and etc, it is recommended to use Google Looker Studio to visualize the data. The reason is that using Looker Studio you can integrate all the data and create more consistent reports and dashboards

While advanced software has its merits, prioritize tools that align with your team's skill levels and your project's timeline. Sometimes, the simplest visualization tools can convey insights effectively without a steep learning curve.

Here are a few considerations: - how clean, accurate and structured is the source data you are going to work with - is it usable? - should the data be enhanced before visualisation? - do you need to maintain the integrations yourself? - does the tool connect to all systems required for your analysis including ones that provide context to your data? - how customizable are dashboards once they are built? Different analytical objectives require different visualizations. - do you need specific technical knowledge or an IT team/consultants to build and use the tool? There’s a solution for everyone to connect the dots on the range from vertical-specific fixed dashboards to build-everything-yourself platforms such as PBI and Tableau.

Hey all, If you're immersed in Google platforms, Google Looker Studio is a gem—it beautifully ties everything together. Remember, choosing the right tool isn't just about features. Think comfort, data types, and cost. In my portfolio, highlights like customer segmentation, campaign ROI, and trend analysis shine brightest. Keep visuals neat and colors consistent. Always respect data privacy and welcome feedback; it's our growth catalyst! As we navigate this digital world, our knack for making data 'sing' truly differentiates us. Cheers!

I'm a big fan of Looker, ever since they got acquired by Google. Thus, free and easy to extend from your data sources into simple interactive charts. Tableau used to be my favorite until they got bought by Salesforce. The Tableau in Salesforce is a neutered version of the old tool. But more important than visual display or the tool are the meaningful insights that we uncover. Amen?

How can you structure your data and insights into a compelling story that engages your audience and leads them to your conclusions?

It is also very important to know the background/level of knowledge of the audience to know if you need to simplify the visual or if you can go into more details in the findings.

Project Goals: Define objectives, e.g., improving ROI. Audience: Identify viewers (employers, clients). Data Selection: Choose relevant datasets. Tool: Pick appropriate visualization tools. Design: Create visuals aligned with goals. Narrative: Craft a compelling story. Usability: Ensure user-friendly visuals. Interactivity: Add engaging elements. Feedback: Seek input for refinement.

Before you can consider how to create within a data visualization tool, you must ensure your team is aligned on what data is tracked: 1?? Do you have clear KPIs (top 2) from your chief officer and the C-suite on how the marketing goals are to drive your company's goals? 2?? Does leadership clearly understand what metrics matter for the marketing initiatives in relation to your company's goals? 3?? Is your team aligned in the top 2 metrics that will be tracked to clearly outline your marketing team's contribution to the annual company goals and C-suite's expectations?

Beyond static charts and graphs, consider leveraging interactive visualizations for your data. Interactive visuals, such as clickable dashboards or animated charts, allow your audience to engage with the data!

Choose chart types based on data: Line: Trends over time. Bar: Comparing categories. Pie: Composition. Scatter: Relationships. Heatmap: Data density. Funnel: Conversion stages. Area: Components' contribution. Gantt: Timelines. Choropleth: Regional variations.

Remember that you're presenting data so if you use blue for one data point you should use it everywhere for the same data point. Don't confuse your audience by randomly assigning colors throughout the presentation or dashboard. If you're working with creative to design prettier dashboards or presentations, make sure to specify that colors should be consistently applied.

When presenting marketing analytics, I've found that choosing the right chart types is crucial. Bar charts work well for comparing metrics over time, while pie charts simplify market share visuals. Line charts convey trends effectively. Using interactive formats in data visualization tools like Tableau adds engagement, ensuring that your audience truly grasps the insights.

When it comes to sharing data with executive stakeholders - beyond the simple bar & line charts - I've found these two visualizations really do the trick: Histograms: These are your go-to when you need to understand how data is distributed. They paint a clear picture of how often things happen and how wide the range is, making it easy to spot any trends or unusual data points. Waterfall Charts: These are your secret weapon for showing a sequence of data, like budget breakdowns or profit sources. They break it down step by step, so it's easy to see how everything adds up to the final result. Always remember, in executive-level reporting, simplicity is key. Choosing the right visualization can turn complex data into actionable insights.

Prioritize Key Insights: Place the most critical visuals upfront to grab attention. Logical Flow: Organize visuals in a logical sequence, following the story you want to tell. Consistency: Use consistent colors, fonts, and styles for a cohesive look. Grouping: Group related visuals together, e.g., campaign performance metrics. Annotations: Add clear labels and annotations to explain data points. Whitespace: Use whitespace to separate visuals and improve readability. Emphasis: Use size, color, or highlights to emphasize important data points. Interactivity: Incorporate interactive elements for deeper exploration. Test and Iterate: Get feedback and refine the arrangement for clarity and impact.

KPIs first, details later. Usually human eyes are accustomed to look from left to right and top to bottom. So, arrange your visuals such that the information logically flows in these directions, e.g. start with #Impressions on the left, then towards right place #Leads, #MQLs, #SQLs, #Conversions, $Revenue and so on. Secondly, the real estate on the dashboard that fits the screen is utmost important and should be able to give a big picture of the Marketing which then should be drill-able to details on the other visuals/pages of the dashboard. Last, each dashboard should have some basic filters which the audience can use to slice and dice the data.

Data and visuals are just there to aid the story you want to tell, that's why it's important to have a sequence in mind which can help readers make sense of what is being presented. In addition to highlighting key-points along the way, your analysis should end with key actionable items which were derived from it.

In every project, Arrange your visualizations in a logical and coherent order. Start with an attention-grabbing summary or executive summary, followed by the most critical insights. Use a narrative structure to guide your audience through the data. Provide context and gradually build up to more complex visualizations. Ensure a smooth flow to help your audience understand the story you're telling.

customers are quick to judge to judge our hard worked presentartions in few seconds they see presentations. explaining logical flows start in the beginning help to paint the picture & drive data analyst points

Set Clear Objectives: Define specific, measurable goals for your marketing analytics project, like increasing conversions or reducing customer acquisition costs. Choose Key Metrics: Identify the essential performance metrics (KPIs) that align with your objectives, such as click-through rates or ROI. Design Hypotheses: Formulate educated guesses about strategies or changes that can help achieve your goals, such as testing different ad creatives. Run A/B Tests: Execute structured A/B tests to validate your hypotheses, comparing control (A) and test (B) groups while collecting data. Analyze, Refine, and Iterate: Analyze test results, refine strategies based on insights, and iterate for continuous improvement in your marketing efforts.

Testing your visuals is crucial. Ensure that they accurately represent your data and are free from errors. Seek feedback from peers or mentors to refine your presentation. Be mindful of data accuracy, consistency, and the overall design. A/B testing different visualizations can also help identify the most effective way to convey your message. Continuously refine your visuals to maximize their impact.

get 1 or 2 potential audience to review our presentations before presenting to bigger groups can really help the success of data analyst final delivery

When presenting marketing analytics projects in your portfolio using data visualization tools, several crucial considerations come into play: Be selective about the projects you feature in your portfolio. Opt for those that exhibit a diverse range of skills and demonstrate your ability to handle marketing challenges, from optimizing ad campaigns to analyzing customer behavior and measuring ROI. Describe the visualization techniques you used, such as bar charts, line graphs, heatmaps, or interactive dashboards. Explain your rationale for selecting these techniques to effectively communicate findings and insights to stakeholders. If your visualizations are interactive elements, stress their role in user engagement and understanding.

Always remember, less is [often times] more. Visuals are most helpful when they answer a simple question. Instead of trying to cram as much information as possible into your dashboard, find out what questions your stakeholders are trying to answer and make sure your dashboard answers that.

its always essential to think thru, throughout the presentation creation process, how each visuals can help to drive the main objectives. paralysis by analysis can be the loopholes Creating each items with the end of minds will help us to create SMART & succint final deliveries

Incorporating these elements into your marketing analytics project portfolio will not only make it more compelling but also demonstrate your ability to communicate complex data effectively, a valuable skill in the world of marketing analytics

To present marketing analytics projects in your portfolio using data visualization tools, you can follow these steps: 1. Highlight Key Projects: Choose projects that demonstrate your skills in interpreting and visualizing data. 2. Use Tools: Use tools like Jupyter Notebook or R Notebook for presenting data analytics findings. 3. Showcase Your Work: Include screenshots, tips, and examples of how you've visualized data. 4. Include Variety: Use different types of visualizations like charts, maps, graphs, etc. 5. Make It Interactive: If possible, include interactive elements. Remember, the goal is to demonstrate your ability to interpret complex data and present it in a visually appealing and understandable manner.