How to Present Data Analysis to The Audience?

Data analysis and Data research firms need to present their findings to their clients and prospective customers. Here we will discuss a few things that they should keep in mind when presenting their findings or selling a solution to the audience.

Common Mistakes When Presenting Data

Often, what happens is that data presenters focus too much on the hows and whys of their analysis. This may feel reasonable to a researcher but an audience of business people is not so keen on hearing the ins and outs of how the data was collected. The vast majority of the audience just wants to know how this effects their business.

The Data Research Firm’s Perspective

A desire of many research firms is to show the customer how important this analysis and data is to their business. However, it is hard to do this. Many firms try to focus on the data and how it was carefully collected and analyzed. A lot of this information only makes sense to the researchers and not the audience.

The Audience’s Perspective

The perspective of the audience depends on who is in the audience. However, if people in the audience are customers who don’t know much about data analysis, then it is most likely that they don’t care about research aspects of the data. What they really care about is what the data means to their business. They care about what the data implies for their future.

See What The Audience Sees

To be successful in any business, you need to understand the needs of your audience; their attitudes about the services you’re providing, and how they view your services right now. Put yourself in their shoes.

Wouldn’t you want for the conclusion to be announced in the beginning so you know what you’re being presented? If you didn’t know most of the jargon, wouldn’t you want only the most important information to be presented?

Conclusion

Focus on the points the audience really cares about. This will make it easier for you to make and deliver your presentations since you’ll be focusing on a few important things rather than all the details that matter. Once you realize this, data analysis reports become a lot more effective.