Product Update

The 2 Axis of Piktochart and Competitors

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Infographics app are not plenty in the world. In fact, the one tool that is able to create infographics (more visual presentations than data visualizations) would be who has not publicly launched yet, who is currently going through an accelerator at HackFwd and Piktochart, we have publicly launched!

Apart from that, the other tools out there are very heavily focused on data visualizations/ presentations. In other to differentiate ourselves, we used a very simple x vs y axis and plotted ourselves on 2 axis: one on data visualization and “presentation” which includes mainly slide-based presentations like Powerpoint.

Data visualization vs presentation

We realized from our findings previously that Piktochart’s users were not looking for heavy data visualizations that use charts. What we realized was that creating data visualizations more than a bar chart, pie chart, line charts, annotated maps,  the users are pretty apprehensive about trying to create a visualization. All they want is an app that easily can create about 4 basic types of visualizations, make it look awesome and really Wow their web audience.

So since then, we have considered a new vertical. If you have seen infographics flooding the web like a plague, you have not yet seen interactive infographics flooding the web. Why do we want to consider interaction as the next thing for Piktochart? To look back at the user who is sitting there trying to figure out how to make his data/statistics really impressive, it was not about coming up with the fanciest looking bar chart, it was about the graphics/ animation/ how unique the experience of reading the information would be! They want their information to be memorable and sadly, graphs that look like the below fail to leave an understanding of what it really means to a lot of non-technical audience, and therefore this is where Piktochart wants to be.

How to create interactive presentations

An example of a graph that looks amazing but would fail to make you understand it. Credits: Image is taken from this link

visual complexities in data visualization

What do you think? We’d love to hear your thoughts.

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