How can you use data visualization to increase e-commerce revenue?

- That which is not measured, cannot be improved. - That which is not understood, cannot be measured. - That which is not visualised, cannot be easily understood! So, by inference one can appreciate the importance of visualisation to influence any kind of improvement! The way the human brain is wired, visually appealing factors like color differential, relative size, following a path (trend), etc. help relate to the data much more deeply with great retention! This causes better dwelling into thoughts that can improve or change the scenario at hand!

It's like giving a visual voice to all those numbers and metrics, making it way easier to spot trends, patterns, and insights that might be missed in raw data. The beauty of data visualization is in its ability to tell a story. When you look at a heatmap of your app, it's not just about which areas are getting clicks; it's about understanding how users are interacting with your app, what's drawing their attention, and what's not. However, there's a flip side too. It's crucial to remember that while data visualization shows 'what' is happening, it doesn't always explain 'why'. That's where your intuition, customer feedback, and deeper analysis come into play. Plus, there's a risk of misinterpretation.

Data visualization can boost e-commerce revenue by providing actionable insights. By visualizing sales trends, user behavior, and product performance, businesses can make data-driven decisions to optimize their strategies. This includes identifying top-selling products, understanding customer preferences, and spotting conversion bottlenecks. With this information, e-commerce sites can tailor marketing efforts, enhance the user experience, and fine-tune inventory management. Improved decision-making leads to increased sales, higher customer satisfaction, and ultimately, higher revenue.

How cant you? Collect all the metrics you possibly can, and just explore correlations. Play with it to see new patterns, or work out some ML/AI to do that for you, but collect as many metrics as possible.

Data visualization facilitates insightful picture of data at a glance. This can be effectively used to identify customer interest on given set of products. Heat map with shades of same color could be utilized to visualize fast moving items to slow moving items in a sorted order.

This article and collaborations provide valuable and detailed information. I would like to share the top three most popular data visualization tools: Tableau: is a powerful and widely-used data visualization tool that allows users to create interactive and shareable dashboards. Power BI: a business analytics tool by Microsoft that enables users to visualize and share insights across an organization. It integrates seamlessly with Microsoft Excel and other Microsoft Office products. Google Data Studio: is a free tool from Google that allows users to create interactive and customizable reports and dashboards. ?? Thanks for your Insightful reaction.

Here are some of the ways data viz can help in marketing. Gain Insights Quickly: Visualizations make it easier to understand trends, patterns, and key insights about marketing data at a glance. Make Informed Decisions: Visualizations facilitate data-driven decision-making, allowing marketers to identify successful strategies and areas for improvement. Communicate Effectively: Visuals simplify the communication of marketing performance and strategies, making it easier to convey information to stakeholders.

Yes, this is important. You can also establish diversity policies. Social media can help improve diversity and inclusion in the workplace, and attract more diverse candidates.

From the zeroth moment to becoming an evangelist for your product, tracking user behaviour through their journey with your product helps the team empathise with users and get a better sense of how well execution on the customer journey is performing. Having dashboards made using something like a Google analytics or your own custom data to visualisation pipeline will enable visualisation that can also help attend to disruptions or changes unexpected.

From a software engineer's perspective, leveraging data visualization for customer service is advantageous. Integrating data visualization tools allows for real-time monitoring and optimization of key support metrics like response time, resolution time, and satisfaction scores. By implementing visual representations such as line charts, engineers can identify trends and fluctuations swiftly, enabling prompt issue resolution and overall enhancement of the customer experience. This data-driven approach not only streamlines customer support processes but also contributes to building lasting customer loyalty and advocacy.

Customer service is imperative!!! I believe that you should talk to the customers...Collect feedback. Actively seek feedback from customers through surveys, social media polls, website feedback widgets, and direct conversations.

We can understand how competitors cannibalize over a window and design pricing strategies. It helps in bringing out a mental model and better playbook for the future.

This is a great way to see if you are moving the needle. Also, whenever you get a chance, participate in industry wide surveys. When you get the results you can benchmark yourself against others who have taken the survey.

"You can't improve what you don't measure". Hence, data is key everywhere in all decision making, which can impact many areas of a business including its revenue. But lack of data may not be an issue nowadays, it is the problem of plenty. And to solve it, we need tools to summarize data for easy and quick consumption for decision makers and data visualization fits perfectly there. And we also need to be aware of evaluating such data to make sure that we are collecting and using the right kind of data for our decision making.

Data visualization permits real-time analysis of market trends and customer needs, and it helps us to understand the key metrics. By displaying sales data visually, businesses can pinpoint popular products/trending products, identify market gaps, and foresee emerging trends, thereby optimizing their product offerings.

If a picture is worth a thousand words, how many rows of data is a visualization worth? In this day and age, companies collect a TON of data. It's estimated that Google, Amazon, Microsoft and Meta store a combined 1.4 petabytes of data. Companies collect data to, among other things, help them make decisions. But first, they have to understand the data. It's much easier to reason about large amounts of complex data if you can aggregate it, simplify it, and visualize it in order to recognize patterns, see trends, detect anomalies and outliers, etc.