For businesses, it has never been easier to get hold of real-life data about their business to analyse. Thanks to locational analysis, they can now, for example, easily analyse the real needs of their customers and optimize sales channel settings accordingly. Modern tools are providing easy access to complex business data analysis, now also for business managers who understand their business the best. The CleverAnalytics platform allows them to see hidden contexts in data by displaying and analysing it on a smart map. We talked to the product manager Lukáš Puchrik about the possibilities and advantages offered by location analysis and about how the CleverAnalytics platform works. Since the very outset he has been involved in developing this tool—one which allows anyone to see their data in the context of location.
What mission and objectives did you have when setting up the company? Can you briefly tell us about your journey since the company started?
We knew that the market needed a specific tool for data analysis that was not being covered by the traditional business intelligence approach, a tool which would be available not only to data analysts, but also to managers and business users. We were responding to actual market demand.
We created a tool which allows users to analyse their data in spatial contexts and to reveal contexts that would otherwise remain hidden in the charts and spreadsheets of standard reporting systems. We placed a hitherto highly complex analysis into the hands of those who wanted to understand their business better and to quickly address the business issues as they appeared in the results of these analyses.
Our vision is still to give businesses the ability to perform analyses that were once too complex for them. Data map analysis had previously been the sole preserve of professionals working with geographic information systems. Thanks to the CleverAnalytics solution, it can now be done by anyone seeking to find connections and new contexts for making the right business decisions. Businesses will find it easier to identify the problems they face and analyse the phenomena which have an impact on their business, all that thanks to the tool for quick and easy analysis on a smart map.
Tell us about the solutions you provide your customers and how they benefit
The CleverAnalytics platform transfers user data onto a smart map, combining the benefits of GIS (geographic information systems) with the traditional approach of business intelligence. As with BI tools, the user defines the metrics in the CleverAnalytics platform, which are then monitored on a smart map. The tool immediately calculates the figures of these metrics for any territory and time. The user can also display these figures through different types of visualizations such as a heatmap, dotmap or grid and choropleth.
Over the course of two years, we have developed a mapping tool that benefits companies in every industry. Locational analysis is not only suitable for medium and large companies that do business with end customers, such as insurance companies, banks, convenience stores and food delivery firms, but for other industries, too. It finds its use in companies that provide data to other entities, or companies in the energy sector.
However, it is important to say that the CAN platform is a universal, analytical, cloud-based tool that displays data in the form of a map or indoor map, so people can use it in any area of human activity where data can be tied to a location. Thanks to the cloud, the CAN platform is accessible from anywhere, anytime.
Companies often labour under the under impression that they must have data from special external resources such as mobile operators, Google, complex tracking services, or detailed information about competitors. But excellent sources might be found in their own data, for example, details from different loyalty programs, e-shop orders or contracts with clients. In most countries there are a lot of data available freely without the need for additional spending, and even though it is quite anonymized, it can be used for business. The location analysis differs from the classic business intelligence approach mainly by its ability to connect data, both internal and external.
What the tool brings to companies is the ability to easily analyse their data and unearth new connections buried within it, so they can understand the phenomena that really affect their business. They can understand the problems they are dealing with much better and make their business decisions based on the results of analysing real-world data.
What’s your biggest USP?
Competing projects only visualize map data. These companies have the data already processed and prepared, the tool only displays it. The CleverAnalytics platform, on the other hand, counts the metrics in the logical model in real time. Its users have many filtering and analytics options. The process runs in the background; behind the final visualization are complex calculations and algorithms that make it possible to see the real functioning of each company on the map. You simply define what you want to see on the map, and according to the specific settings of time, granularity—i.e., the geographic detail for the type of visualization—and individual filters, the application will return the result.
Compared to classic reporting tools, we’re giving businesses the ability to easily access a brand-new way of looking at their data. When you only see figures in spreadsheets, a lot of information can be missed. Without having the right context, you won’t recognize a phenomenon and its causes. Locational analyses put data in the required context and enables companies to see, for example, the potential of individual branches; it helps to understand customer needs; it analyses strengths and weaknesses in terms of internal and external data; and it provides new arguments for smart sales. The important thing is that these complex analytics can be used directly by business users.
How does adopting your company’s technological innovations help customers deliver important business outcomes?
Those with the power to make decisions in companies need immediate access to real-time data. The smart map delivers the goods in an easy-to-read form.
Let me tell you a specific example from a smart sales area. Data analysis in the context of location-enabled B2B sales staff of the multinational Edenred, dealing with employee benefits and meal vouchers, to build a highly specialized and effective database of the companies they contacted. Their success rate in addressing those companies then increased by 25%.
Companies with a network of branches can determine how clients visit individual branches or where they overlap. Cannibalization between branches is a relatively common problem for larger companies. Analysis can reveal the so-called “white areas”, those that are suitable for a business but are still not being served by the company. Thanks to locational analysis, a company can see the real-life catchment area of its branches on a map. This shows where customers are actually coming from.
The analysis also works with the so-called “exposure index”. This indicates the occurrence of a target group. When evaluating individual locations, locational analysis can work with all sorts of data, such as data from cell phone providers, economic transactions data from banks, and data from IoT sensors.
What’s your view on the current situation with Big Data Analytics and its future?
Tools such as CleverAnalytics enable companies to process even big data. Thanks to the cloud, not only will such solutions be available anywhere and anytime, but availability will naturally also extend to smaller companies that previously couldn’t afford similar tools.
The most important trend involves lowering the information stress of users to the bare minimum, regardless of how much data is needed for an analysis. The goal is for data analysis tools to show new connections and highlight—unprompted—important phenomena, while also providing users with comprehensible information. Tools will then make it easier for users to make business decisions more easily, and allow them to react readily to a specific situation. In the future, these tools may, for example, guide their users to take the most effective decisions. In particular, the trend will be to develop tools that really do show what needs to be done, based on the analysed data.
How is all this related to machine learning and artificial intelligence?
To use machine learning requires a sufficient quantity of data. Personally, I find that, unlike humans, artificial intelligence is able to evaluate dramatically greater quantities of interacting phenomena and determine their relationships, so I can see its role everywhere where there are many variables in play. In locational analysis, this happens very often. Artificial intelligence and machine learning can help a lot with interpretation, prediction and “what if” analyses.
Where do you see growth in the sector?
The field of localization analysis, as well as numerous other fields, will draw on the ability to collect data from the IoT network. The number of sensors is constantly growing, and their range of uses is similarly expanding. They can do lots of things nowadays and are collecting very interesting information which can be useful not only for the specific purposes for which they were produced. In the future, it will also be possible to use such data for many other applications and to process information about the “world”.
A typical example is the amount of data coming from so-called connected cars. This will not only increase the comfort and safety of the owner, or aid the manufacturer’s development objectives, but will also, through its analysis, improve overall safety and bring a number of economic and environmental improvements. We could find many more such examples.