CRM Data Analytics & BI
Do you still make business decisions without data analytics?
Even without CRM Data Analytics & Business Intelligence: With the increasing digitization of business processes, more and more data is accumulating in many companies. These make up a real treasure that should be used profitably.
According to the iwd (Institute of German Economy), of the 1,100 companies surveyed in the IW panel, 84 are still entry-level in the data economy. This means that they have hardly yet used data as a value-added resource.
Why use data at all?
The fact that we need to collect data and evaluate data analytics with CRM in order to remain competitive is no longer seriously questioned. But it is not always clear why all this is.
In fact, business data can be analyzed profitably on many levels and serve as a meaningful basis for important decisions. In this way, senior positions can gain multi-layered insights from the right data and evaluations, from the performance of departments to individual employees to concrete measures. Strategies and methods can then be derived from this in a targeted manner. CRM data analytics also serves as support for employees at the lower levels.
For example, let’s look at a sales department: it analyzes the data received in the CRM software, from website tracking and phone notes, to the visit report and the offer to the completion of the purchase and further correspondence. Numerous patterns and trends can be identified or previously unknown relationships between individual factors can be identified and contextualized.
This can serve as a basis for the sales manager to define the appropriate methods for a strategy to achieve the set goals.
The sales representative can help with reminders and suggestions based on CRM data analytics in everyday life – for example, who should be contacted urgently or which customer might have a possible need. The following video introduces you to the exemplary function “Customer Journey Monitoring” (German language only).
If these data pools and CRM data analytics are systemically linked to those of other departments such as marketing and service, the holistic view of company data also at the managing director level leads to a valuable basis for overarching strategic decisions and orientations.
At the same time, CRM data analytics can also provide insights into a possible new business model. For example, can you derive an additional service from the data already collected? Consider automated maintenance based on the data collected by a Wi-Fi-enabled washing machine or the like.
Make data-based decisions – But how?
Quality before quantity
If you plan to consider your data as a value-added resource, and now you wonder how exactly you should address it, it is best to follow the credo “Quality before Quantity”.
Collecting and evaluating all sorts of data, which holds the stuff, can give you valuable and possibly completely surprising information, but it also involves a lot of time and costs. First, clarify the above question specifically for your company:
- Why do you want to analyze data?
- What are the points of action in your business model that could be better served due to meaningful data analysis?
Derive the analytical questions that arise from the business questions that arise from it. You then ask the how question.
- What data do you need to analyze to answer the questions?
- Are you already collecting them?
- What external data might you need to contextualize your data?
Finally, develop an evaluation framework for the analyses, for example in the form of KPIs (key performance indicators), i.e. performance figures, from which you can read (miss) successes in a targeted manner. Especially here it can be extremely helpful to work with experts. They bring a lot of experience, where it is worthwhile to measure and analyze and which framework makes sense for this.
Looking ahead and back
One of the great advantages of data-based decisions is the ability to adopt trends based on the available data or to simulate the impact of different decisions in the future – predictive analytics. Of course, this still does not make a decision infallible, but the likelihood of a proper one is still increasing.
At the same time, it is also important to establish mechanisms that track the actual impact of your decisions and actions. This allows you to make timely adjustments and improvements if necessary. After the analysis is, so to speak, before the analysis.
Now use state financial support for your digitalization:
If you want to introduce a CRM data analytics, we are your competent partner: We take over the CRM introduction and submit the application for you to the BMWi funding program “Digital Now”. (Support programm for Germany only)
The right tools
If you already know why, how and what data you want to use, you will of course also need the appropriate tools.
With the increasing popularity of data evaluations, the high-performance BI tools (BI: Business Intelligence) are also gaining in popularity. This certainly makes sense for complex evaluations of large amounts of data. Nevertheless, they are not a must.
Depending on which data you want to evaluate and to what extent, it will also be much less expensive tools.
CRM Data Analytics & Reports
For example, your company needs certain tools, such as a CRM system,to collect the necessary data anyway. Most CRM software, on the other hand, already comes with some analysis and report functions that allow you to perform a wide range of evaluations.
For example, prefabricated reports, such as sales funnel, pipeline, forecast or conversions, are often found in the CRM system itself. These usually come with clear graphics and can be flexibly arranged on dashboards as required. This ensures a quick detection of important KPIs.
In addition, it is usually easy to create individual reports, which are then tailored precisely to the key figures that are relevant to your company. On the basis of such information, fundamental, forward-looking decisions can already be taken.
When does a BI tool make sense?
If the amount of data increases or requires even more complex analyses, the BI tool may have to be produced. This is the case, for example, if you rely on big data and want to come across previously unanticipated insights with the extensive analysis of all available data.
The BI tools are of course much more specialized and powerful. They are optimally equipped with appropriate standard interfaces (APIs), which make it quite easy to dock to the existing software landscape.
However, keep in mind that a pattern that occurs can only be interpreted in the context of further data and information, should it become the basis of your decision.
Conclusion: First the right questions, then the right analysis
Whether with CRM data analytics or BI tool – you should definitely first ask yourself the right questions and always think them systemically:
- Which business questions should be answered by data analysis?
- What data do I need to analyze for this?
- How can I analyze them?
Also, don’t forget to weigh up cost-benefit factors well before making expensive purchases.