Dashboards are a great way to make sense of complex data. How effective a dashboard is, however, ultimately depends on the specific composition. In modern dashboard systems like Datalion, the compilation of charts is easy – but how to choose the right chart types?
First, ask yourself what messages and information you want to communicate with your dashboard and what kind of data is available for that purpose. Depending on whether you want to display distributions and shares or want to visualize trends and processes, different chart types are possible. Also, the target audience of your dashboard is important: A data analyst often expects a different level of detail than, for example, a marketing employee. You find more information about the basic approach here.
On the one hand, you should be brave and, in addition to common bar charts and line charts, use unusual chart types to inspire the target audience of your dashboard. On the other hand, you must always pay close attention to the clarity and meaningfulness, this should always be your priority. Offering added value through interactivity in the form of selection filters makes great sense, but also has an impact on the selection of appropriate forms of presentation and must be taken into account accordingly. In addition to deciding on the right charts, the definition of colors, fonts and dimensions is ultimately part of the optimal composition of a dashboard. The best diagram does not help if, for example, colors are hardly meaningful or do not match the corporate identity.
The easiest way to play and test different visualizations in the dashboard software is to step by step and select the best charts and graphs. Datalion offers more than 50 different chart visualizations that can be inserted and exchanged with just a few clicks. Here are some particularly important chart types.
Pie- and Donut Chart
The good old pie chart is a classic one and well understood for less data-savvy people. This graph type is suitable for representing relative frequencies within a category of data – all shares together are 100 percent. Classic example: age groups or genders and their proportions within a sample.
The so-called radial chart b> is also in great demand for design-oriented chart professionals. It looks like a speedometer and is very meaningful thanks to its simplicity. However, the range of applications is limited, since it is only suitable for the visualization of variables with only one expression. By the way, the donut chart b> is closely related to the pie chart: The hole in the middle loosens up the image, thus providing (at least) an optical treat.
Column and bar chart
Column and bar charts are also part of the basic equipment of every dashboard artist. This is called a bar chart when the columns are vertical.If the columns, pardon bars, run horizontally, it is a bar chart. For charting relative and absolute frequencies and their comparisons, these chart types are great, making them one of the most popular chart types, whether vertical or horizontal.
Stacked bar chart
An important special form of the bar chart is the stacked bar chart. It is suitable for displaying scaled data and, thanks to the compressed representation, provides a quick overview – even over extensive result tables. Stacked bar charts are often used when you want to put results into so-called item batteries in the dashboard. However, it is important to have a good color choice that intuitively reveals, for example, approval (green) or rejection (red).
Another well-known classic is the line chart. For comparisons of features or trends, there is hardly a better choice. For example, the results of various image measurements can be displayed and important differences made easily visible. For the visualization of time series, Datalion offers a separate time series b>, which has already been optimized accordingly.
If you want to compare two or more features and highlight differences, the Polarity Chart b> is great. This type of chart is often used in the case of usage trends or awareness measurements, since the presentation is equally clear and easy to understand. In addition, it is ideally suited for the additional integration of filters.
Somewhat fancier is the radar chart. Visually appealing and meaningful, even larger amounts of data can be displayed. Typically, this type of chart is used to represent several evaluations, such as brand awareness. The prerequisite is that the variables to be compared have the same scaling. Each value is entered on an axis and evenly distributed to 360 ° around the zero point, for each category there is an axis. Not only in marketing radar charts regularly meet with a positive response and have many fans.
The wordcloud is truly a special case in this article, but can not be used to represent quantitative results. For qualitative data, however, the Wordcloud is worth gold: terms that are particularly common are displayed in a larger or more prominent manner. Words that are rare, smaller. This gives open ended questions an easy form to display and looks good. Well, it’s not quite that easy: depending on the question and the response, the results have to be adjusted and the words such as “and” or “me” have to be removed. If you still use the matching colors for the presentation, the Wordcloud could definitely be an eye-catcher.
Especially sales professionals have their joy on this chart type, as they allow the different stages of a sales funnel simple and impressive. But also characteristics of other gradients or phases can be elegantly communicated herewith. An important added value of the chart is that potential problems between stages of a process or process can be identified quickly.
Also very effective is the presentation of multidimensional scaling (MDS). This is used, for example, to identify certain buyer groups and to clarify their respective differences. The combination of two features is reflected in the coordinate system, whereby the corresponding scaling can be read on the x or y axis. This form of presentation is not for beginners, but a must-have for data professionals.
Incidentally, this also applies to the scatterplot chart b>: Similar to the MDS chart, values of two dimensions are displayed in a coordinate system. However, this type of diagram deals with the depiction of relationships between two variables or characteristics. It is easy to see from the pattern of points whether variables correlate and to what extent they do so.
Rather, something for design lovers are bubble charts. The circles used can be used to compare the expressions of a variable, for example, when comparing different age groups within the variable “age”. On the one hand, the radius of the circles represents the size of the portion, on the other hand colors can also be used to illustrate the differences. However, if you are not a fan of “bubbles”, you better use the tree map b>: It works like the bubble chart, but uses squares instead of circles. This looks a bit tidier and the differences can often be better interpreted.
A true piece of art can be the chord chart – if you use the right data. From a design point of view, this chart type is out of competition, but experience has shown that interpretation is difficult for many people. It shows relationships and overlaps between data in a matrix. For example, different groups of buyers can be identified. Once you have understood the basic principle as a dashboard user, the added value is huge. However, as a dashboard designer you should provide an explanation for this to happen.
We are on the IIEX Europe from 18.-19. February as an exhibitor in Amsterdam. The IIEX – Insight Innovation EXchange – is the premier fair for innovation in market research. Of course, we should not miss that, since the possibilities that DataLion offers at the press of a button for creating tables and reports – paired with KI algorithms – are certainly among the most exciting innovations in the industry right now.
The full program can be found here . We have our own exhibitor kiosk on site. As usually, there are the latest features in our software, our new DataLion brochure, postcards, adhesive tattoos < / a> and Lion . In addition, a nice raffle for anyone who is willing to stick our adhesive tattoo.
DataLion at the BigDataParis in Paris
From 11-12. March meet us as an exhibitor in Paris. We are part of the Startup Villages . With more than 17,000 visitors, BigDataParis is the central European trade fair for big data. You can still sign up for free here . We would be happy to meet you there!
Wir sind auf der IIEX Europe vom 18.-19. Februar als Aussteller in Amsterdam. Die IIEX – Insight Innovation EXchange – ist die wichtigste Messe für Innovationen in der Marktforschung. Da dürfen wir natürlich nicht fehlen, da die Möglichkeiten, die DataLion auf Knopfdruck zur Erstellung von Tabellen und Reports bietet – gepaart mit KI-Algorithmen – sicherlich zu den spannendsten Innovationen der Branche aktuell gehört.
Das komplette Programm kann hier nachgelesen werden. Wir sind mit einem eigenen Aussteller-Kiosk vor Ort vertreten. Es gibt am Stand wie immer die neuesten Features in unserer Software, unsere neue DataLion-Broschüre, Postkarten, Klebetattoos und Lion. Außerdem noch ein nettes Gewinnspiel für jeden, der sich unser Klebetattoo stechen lässt.
DataLion auf der BigDataParis in Paris
Vom 11-12. März treffen Sie uns als Aussteller in Paris. Wir sind Teil des Startup-Villages. Die BigDataParis ist mit mehr als 17.000 Besuchern die zentrale europäische Messe rund um das Thema Big Data. Noch können Sie sich als Besucher für die Messe kostenlos hier registrieren. Wir würden uns freuen Sie dort zu treffen!
Key performance indicators or KPIs are not just a big issue in most companies since the growing importance of business intelligence software. However, it is very controversial which KPIs actually lead to success. Which are superfluous? Which indicators are more misleading than help? Even dashboard solutions are an indispensable part of KPIs, as they are the only ones that develop their full potential here. Imagine you are still late in the office finishing your presentation for the next morning’s board meeting. That’s where it helps if you can easily pull up the real-time KPI dashboard in BI system.
On the one hand, the up-to-dateness and availability of the data can be continuously ensured by means of dashboards. On the other hand, the development of indicators over the course of time can also be presented in an attractive and supportive manner. Many KPIs perform their purpose much better, especially in marketing and market research, but also in management and sales. The sole use of static reports increasingly loses its right to exist in times of “real-time data”.
Targets are the foundation for every performance indicator
But which KPI should you choose for managing your business? This question is difficult to answer as the choice depends on several factors. It is worthwhile, however, to answer this question in principle for the company, as it simplifies internal discussions immensely. Otherwise, you waste a lot of time discussing different key figures, which may show different trends. Rather than better thinking about what the company needs now.
The right set of KPIs is essential
A key point in choosing adequate KPIs is the objective you pursue with your dashboard and the KPIs shown. A KPI should basically map what its business or a specific department wants to achieve, e.g. contacts with new customers (leads), reach or customer satisfaction. For example, sales operations should be supported in generating new customers as efficiently as possible. By contrast, marketing should achieve the highest possible return on investment (ROI) with regard to the use of the advertising budget. And in customer service, the number of complaints should settle to a low level.
Use of indicators is not an end in itself
Even this small discussion shows how different the goals of KPIs dashboards are. A key success factor is therefore that the use of indicators does not become an end in itself. The chosen KPIs must fit exactly to the objective and be able to represent the appropriate level of target achievement. Another mistake sometimes made is that the KPI chosen is the measure that is easily available or easiest to measure. An example would be e.g. use the number of demo account registries as KPI for leads, without checking if and how much the demo was actually used. In addition, it must be clear to all persons involved what the key figures and their characteristics mean and what blurriness is associated with the corresponding indicator. Even if one speaks frequently of hard numbers, you will be usually amazed, how much blur is also in seemingly “hard” controlling numbers.
Customized KPIs can make more sense
No matter which KPIs you choose: Make sure that the key figures are actually relevant for you and all stakeholders are involved. Sometimes a meaningful indicator only results from the combination of two key figures. And in most cases, individual KPIs make more sense than popular indicators such as the Net Promoter Score (NPS). Everyone benefits, but their informative value can still be low for your concrete goal achievement. In any case, it pays to invest time in planning and to coordinate this with all stakeholders. Another important success factor is the appropriate presentation of the key figures. By mapping past values in the form of progressions, KPI developments can be presented very effectively. Good dashboard solutions offer extensive design options and make positive and critical developments visible at a glance. For time series the database must be updated regularly. The best is a real-time connection to the database via an interface, if one exists. Such a link has the additional advantage that the cost of maintaining the dashboard in the future is very low. In general, the more up-to-date the KPI is, the greater the informative value.
KPI dashboards become even more effective if the possibility of filtering exists within the figures and gradients. Thus, the knowledge gain is often greater, if users can spend depending on the topic personalized KPI developments over certain periods, target groups, cost types, etc. Also the possibility to compare the filter selections usually brings a considerable added value. Last but not least, the motto “less is more” undoubtedly also applies to key performance indicators. A good dashboard, only features KPIs that are actually relevant to users. Even though there is no general rule on numbers, more than ten indicators and time series are more likely to confuse rather than achieve goals. Here are some examples of KPIs from business practice:
The net profit is the difference between revenues and total costs. It can be calculated for the entire company or even for individual products and is not only an important key figure in sales, but also a must in the management dashboard. It symbolizes the success or failure of the entire enterprise.
Being able to see graphically how much the company is growing (or even shrinking) in terms of its sales and revenues is an important support for decision-makers. Do processes have to be changed or optimized? This metric is also a must-have for businesses, but only if it’s always up-to-date. The revenue growth rates should be configured in the dashboard so that you can individually change the period for calculating the rate.
Customer acquisition costs (CAC)
Customer acquisition is a painful and expensive topic in many companies. Keeping an eye on the specific costs is also essential and says a lot about the long-term success of the company. Properly presented in a dashboard, acquisition costs regularly provide for wholesome surprises, as they are often underestimated.
Market research oriented KPIs
Customer Loyalty & CX
In customer-centric organizations, an up-to-date customer satisfaction KPI should be prominently placed on each employee’s dashboard. One challenge, however, is the meaningful measurement of customer satisfaction and its dimensions. Not only in large service departments representations in dashboards help to detect and eliminate grievances.
Net Promoter Score (NPS)
The Net Promotor Score (NPS) is a common measure of the likelihood of a customer recommending a company or brand. In some industries, this metric correlates with business success and is therefore standard on many market research dashboards.
Customer Lifetime Value (CLV)
Often used is the so-called Customer Lifetime Value (CLV). The CLV describes the value of a customer for a company, throughout the life of the customer relationship. What revenue is expected of the customer, what is his potential? By means of the CLV one can e.g. justify why you give different customers different care.
Just as important and challenging in measurement as customer satisfaction is the brand image. How well or badly is your brand perceived among your potential customers? The perception within the individual target groups plays a decisive role in purchasing decisions. With the help of a dashboard solution, you can identify important developments easily and early.
Experience more lion power – Embrace our new features!
There’s exciting news from DataLion: we released version 1.9 which includes numerous new features we’ve developed in close cooperation with clients & users. We have incorporated your feedback and suggestions gathered in the past months. Among new features like visualizations and export functions, we have also implemented several optimizations (e.g. loading time) and bug fixes.
In short, DataLion is faster, more flexible and more productive than ever. We hope you will love it!
Let’s have a closer look at some highlights:
Yes, more chart types!
Stacked column chart with option to display the mean or the sample size (Example):
Extended donut chart e. g. for the comparison of Key Performance Indicators (Example):
New exports, New interfaces! Let’s check out the new export functions
Export of a dashboard or a report with more than one dashboard and charts as PowerPoint or Excel document
Export of an excel report with multiple tabs in an individually defined format:
Overview of our new features
New chart type: stacked column chart with means and case numbers
New chart type: extended donut chart with means e.g. to compare KPI Values
Sort charts by mean value
Reverse order of stacked column chart segments
Top5, Top10 etc. for time series charts
Hide empty values and categories in time series charts
Separate filter dropdowns for each tab of a report
Export of wordclouds as image
Reports and Dashboards
Placeholder element in report/dashboard title
Read-only mode for read-only access profiles
Selected global filter remains across tabs
Automatic selection of comparison operators depending on the selected report filter
Individual dropdown-menus per dashboard
Adjustable precision of average values
Back-end definition of missing values
Set alignment and spacing in chart settings
Back-end configuration of pptx-exports and masters
Export of an entire report with multiple dashboards and charts as PPTX
Export of an entire report with multiple dashboards and charts as Excel
Export of an excel report in a pre-defined format
Metadata and import
Add of text fields via codebook
Automated incremental data update (e.g. backfill of last month, week)
Export of the codebook including special fields and text elements
Back-end function to delete and replace entire codebook
Various bug fixes and optimizations (load time, exports, imports)
The best things in life aren’t things – but free books. At least if you want to spend the next few weeks to take your machine learning to another level.
We’ve selected five great books that help you to understand one important aspect in machine learning in a very profound way. Thanks to the Open Access initiative, all of these works are available for free:
The Elements of Statistical Learning by Trevor Hastie, Robert Tibshirani and Jerome Friedman
If you need a refresher on your machine learning methods, ESL is the book to go to. From Lasso to boosted trees and ensemble learning – this beautiful typeset work covers all the bases for your professional life as a data scientist.
Convex Optimization by Stephen Boyd and Lieven Vandenberghe
If you have spend some years in machine learning, the probability is very high, that you’ve stumbled upon convex optimization problems. The theory and methods around convex optimization has been around a long time. But until a few decades, they were thought to be mostly of theoretical value. Today, convex optimization is e.g. an important part of Deep Learning and many smart things around are powered by these algorithms.
Group Representations in Probability and Statistics by Persi Diaconis
This book goes back to Diaconis’ lecture notes for his course on this topic at Harvard in the 1980s. There are a lot of situations where data scientists have to deal with rankings, e.g. consumers having to rank products in a survey. These mathematical problems can be solved by applying group theory.
But wait, there’s more: As Diaconis is also a magician, the shuffling of cards also plays quite a role in this work.
Mining of Massive Datasets by Jure Leskovec, Anand Rajaraman and Jeff Ullman
And finally, for something more accessible: This book is already a classic on big data techniques for processing large data sets. If you haven’t already, you really take a look at the 2nd edition of the book that also includes mining large graphs and map-reduce programming. You can also take a look at the first chapters of the upcoming 3rd edition.
This time, we will explore some of the most fascinating Bavarian craft beers. Together with beer sommelier Stefan Hermansdorfer, we will taste six very different craft beer varieties from Munich and region.
Of course, all our tasting results – from appearance and mouth-feel to aroma and taste – will be visualized in real-time on a DataLion live dashboard:
Monday evening was a special evening at the DataLion office in Munich:
We hosted a beer tasting event as an official side-event of the Bits & Pretzels Founders Conference and Startup Night.
Together with beer sommelier Stefan Hermansdorfer, we tasted six different beers from Munich and surroundings that were all in the Märzen or Festbier style (Hacker-Pschorr, Augustiner, Hofbräu, Tilmans Das Helle, Eittinger and Giesinger). One of them even had a lion on the label. And because we all love data, we also created a short survey for describing and scoring the beers in terms of appearance, aroma and, of course, taste.
All results were displayed in a DataLion real-time dashboard in our conferencing room: We chose radar charts for our live visualization because they allow to compare the different taste profiles of the beers very intuitively at one glance. Every time one of our guests rated a beer, the results were updating and showing the new rankings.
You can see the live dashboard at this link. If you’re interested in live dashboards that are connected to a quick survey for your business, just leave a message at our contact page.