Whether you’re reporting on sales and revenue or more qualitative data like retention and customer lifecycles, combing through data and visualizing it in a meaningful way is important so you can more easily identify changes and trends and make better decisions.
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When you think about raw metrics or data analysis, numbers, figures, equations, and horrific flashbacks to Calculus 101 come to mind. But in reality, visualizing data simply means translating it into a more digestible format. Ordering tables, highlighting colors and calling out trends make your raw data more appealing to a reader and will improve understanding and recall.
Most of the data coming out of Salesforce and other CRMs are qualitative, meaning not just metrics and figures but names, contact information, and lifecycle information. This type of information can also be displayed visually but requires a little bit more creative thinking.
No matter what kind of information you’re compiling or what the data might be showing, the most important consideration when building a visual (or any kind, for that matter) report, is who your target audience is. If you’re reporting on yearly sales growth to your C-level executives, showing high-level growth trends is going to be more important than drilling down on minute data points.
The reverse is true as well. If you’re building an internal report on the changes you made to your marketing strategy in the last quarter, then the devil is definitely in the details.
Just like identifying your target audience, it’s key to dial in what information and data points matter the most. It’s helpful to start with a question and figure out what data will answer that question. Some examples include:
These questions can most likely be answered using one or two qualitative or quantitative data points so focus on those numbers.
Most often, reports happen on a regular basis (quarterly, monthly, weekly) and usually, it’s the same data every time. But the key when visualizing data is to highlight changes. Whether things are moving in a positive or negative direction, highlighting trends is going to be the most effective way for users to understand what’s happening with the information. Comparing Month over Month or the same week in the previous calendar year will help users understand why that metric is important.
Simply using colors (green for positive changes and red for negative) or arrows (up for increases, down for decreases) will help quickly, and definitively, identify those changes.
The human eye likes charts. They are organized, orderly, and sorted so we can see trends and draw conclusions.
Spacing and headings are key for making charts readable. In general, left-justified text is the most natural for the reader. Center-justified text should be used sparingly, perhaps for elements you want to stand out from the rest, such as column headers and subheads.
Add borders, highlight, or bold certain areas that you’d like to call out, and sort your data by the trend you want to show.
Windward’s whitepaper on Designing Beautiful Reports goes into greater detail about using color, spacing, and even layout to create an impactful report.
If you’re a left-brained, data analytics nerd then tables and charts might be exciting enough. But for the other half of the world, breaking up numbers with true visual elements will make your reporting more impactful, and well prettier.
Just like sorting tables and charts and drawing conclusions with colors, using visual elements will help the user understand and comprehend raw data points.
As instinctive animals, we understand that red (and other associated warmer tones) signal danger or in the case of reporting, numbers going in the wrong direction. Conversely, green has a positive connotation. If someone is going to spend only 30 seconds reading your report, signals like colors and arrows help them digest the data as quickly as possible.
Infographics are also a very helpful way to help display quantitative information. They keep readers more engaged and boost memory recall. Examples of some common images to use for reporting include:
Using images in place of words is a common practice for adding visual interest to any type of report or data set.
It might seem impossible to put words to numbers but shifting your thinking and seeing your qualitative data from a visual perspective will help. This is especially useful for Salesforce and other CRM data because so much of the information is human-centered. Most of the data stored in Salesforce CRMs is accounts, opportunities, contacts, activities, and leads.
There is more data than the number of qualitative data points. Consider other aspects of the data like lifecycles, time spent, efficiency ratings, and forecastings like potential future revenue or referral accounts.
The most important component of any data analysis and reporting is to be impartial and unbiased. If it’s your sales team that’s performing poorly it would be downright unethical to skew your data to make metrics look otherwise. The same goes for favorable data, if your graphs are moving in a positive direction, it’s important to attribute that growth where it truly belongs.
But when it comes to visualizing that data, draw conclusions. Make statements about the story your data is telling. Answer the questions (like the ones listed in bullet #2). Create your report so that if someone only has 30 seconds to review it, they can clearly understand the most important trends, changes or conclusions from the report.
So maybe reporting is getting a little more daunting with things like focusing on conclusions and adding visual interest. Automating your reports will save valuable time so you can analyze, rather than just export spreadsheets and spend countless hours copy and pasting raw data points.
With Windward Team’s Salesforce Integration, you can automatically generate powerful reports. Build your template once (without the help of your designers and developers) in the tools you already know how to use, and sync your native Salesforce data. Run the queries as often as you need for a regular reporting cadence or run ad-hoc reports on the fly.
No matter how much data or how you present it, automating your reports will ensure you save time building and utilize more accurate data.