Presentation Management

Making Presentations Intelligent

Presentation Management 14

Original content by AlexAnndra Ontra and James Ontra
Enhanced by Geetesh Bajaj

In the last part of this Presentation Management series of posts, we looked at how better storytelling can make your content stand apart. In this part, we look at making your presentation content intelligent.

At first, presentation management might seem like taking PowerPoint and other files and putting them on a cloud with a few frills. But there’s another aspect of presentations that comes alive once they are managed in a cloud environment where they can be tracked.

Presentations throw off data. Every word and pixel is data. Every time a slide gets used, the data can tell us who used it, and where and how it was used. The data can tie sales presentations, for instance, to deals closed, which means the data could show which slides helped sell the most.

All of that data can be captured and analyzed in ways that help make every presentation better.

Where do you get the data?

Reports in Shufflrr

Yes, data can be helpful, but where do you get this data from? The answer is Reporting.

Any Presentation Management solution contains a Reporting module. For example, Shufflrr’s Reporting module has many reports, including the DashboardFileSlideUserActivityLikesComments, and Shares.

Presentation management tracks the usage of files and slides in different scenarios. This provides a concrete understanding of what files, what messages and what products are being used and by whom.

Data can be captured and analyzed

Additionally, Presentation management includes social tools for users in the field to give feedback in real-time, associated with actual content and activity. Users can comment and collaborate on files and slides through conversation threads, comments, likes, etc. in real-time, spontaneously. It’s like Facebook, except for marketing material instead of someone’s vacation.

As Alex says:

I know I’d rather look at sunsets on a sandy beach than last quarter’s sales figures, too. But we need those sales to afford the beach vacation.

The combination of data and anecdotes from the field provides a full picture of how the content is performing, and where and how to make adjustments to your message and content as your business evolves.

Machine Learning and Modeling

Artificial Intelligence is about organizing enormous amounts of data, drawing conclusions and acting on them. Again, where does this data come from? The ubiquity of mobile technology has made it possible to collect data from millions of users’ activity, then analyze and apply it to some purpose.

  • For Amazon, this means suggesting products for you to buy based on what you purchased last month, and what you’re browsing through today.
  • For Google, it means finishing phrases, suggesting search terms based on what you just started to type into the search window, or based on what ads or articles you clicked on.

These actions are tracked, and the data collected.

The more actions are tracked, the more data gathered, the better AI can make “suggestions” or predict actions and behaviors. Then those actions are further tracked, analyzed and as a result, AI can fine-tune and improve. AI builds on itself, over generations of data.

Acronyms: ML and AI

The technology industry loves acronyms, and AI has almost become part of our vocabulary. ML is less popular, but related.

Let’s list their full forms:

AI: Artificial Intelligence
ML: Machine Learning

It is through ML that AI gets more intelligent and richer. And like we say in the real world, “Learning never stops;” that’s true for ML or machine learning too!

Shufflrr, as a presentation management platform, uses both ML and AI, but did you know that PowerPoint also uses both to help you create slides? One example is the PowerPoint Designer feature.

Not surprisingly, this AI applies to presentations. That’s because presentations are no longer one-and-done lone files; they are enterprise assets. The same files are used and reused throughout many different scenarios, and results are collected, tracked, and analyzed. It’s the foundation for intelligent presentations — what we call Predictive SlidesTM.

Predictive Slides will suggest which files and slides you should include in your new presentation based on who you are, to whom you are presenting and what you have presented in the past. During meetings, Predictive Slides will suggest slides based on how that conversation is progressing. This is the future of presentations, and we’ll get into much more on that in subsequent posts of this series.

Machine Learning and Modeling

In the next post of this series, we will look at the culture of presentations management.