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Writer's pictureNikolaus Bremerich

HOW OR USE BIG DATA IN SALES MANAGEMENT

Thanks to current technologies, sales management has access to a multitude of data from internal and external sources (aka Big Data). Today, these large, unstructured and continuously flowing volumes of data can be analysed more easily than ever before to make fact-based decisions and to take a 360-degree view of customers and sales.


Data analysis is increasingly becoming a main task of sales management. It offers the possibility to optimise the entire sales process and to significantly improve the quality of decisions in sales. Thus, the evaluation of big data should be used in sales management to achieve not only improvements in effectiveness but also in efficiency and to secure competitive advantages over one's rivals.


But how can Big Data Analytics be used effectively in sales?


1. Create the right environment for the use of big data in sales


In order to use big data successfully in sales management, a modern IT infrastructure and data analysis technologies are needed to summarise, consolidate, analyse and process the mass of data from different sources.

In addition, competent analysts are needed who understand sales-related questions, are able to form meaningful hypotheses and are also proficient in all common statistical methods with which these questions can be answered and hypotheses can be confirmed or falsified.

This adds up to a sizable investment. Therefore, it makes sense to start with pilot projects and external advice and then expand the scope over time. In this way, not only can experience be gained in data analysis, but also indications of data still to be collected to answer new questions in sales. This procedure increases investment security and it can be concretely checked which competitive advantages can be achieved through big data analytics in sales.

Today, only very few companies use big data analytics in sales, but most are planning to do so. This is mainly due to a lack of technical and professional know-how in the field of analytics.


2. Focus on the right KPI


Through data analysis, sales managers can comprehensively monitor performance on a daily basis. In this way, deviation analyses can be used to counteract undesirable developments at an early stage. It is important to focus on the right key figures.

With the increasing scope of performance of CRM and ERP systems, more and more key figures are available.


Before you listen to your gut feeling because of the sheer quantity of data, you should rely on facts. Suitable statistical methods can be used to determine which KPIs have the greatest correlation with the sales result or the achievement of sales goals. For example, the number of customer contacts is not the decisive factor for every product and every sales form.


It is important to focus on the top 5 defined Key Performance Indicators (KPIs) and review them every 2-3 years.

This also applies per sales channel. For example, in stationary trade, different KPIs are relevant than in eCommerce. To control digital forms of distribution, new KPIs, such as retweet rate or online reputations - important data sources for measuring online performance - must be included.


3. Increase the reliability of your sales planning with data analytics


With the help of data analytics, you can not only improve sales management but also carry out more precise, detailed planning or forecasts and align sales activities accordingly.

For example, big data provides information about customer behaviour in the event of price increases or increasing competition. Or it helps you to better evaluate your team's pipeline.

If you digitally record all sales improvement measures (e.g. training, trade marketing, new sales staff) and then correlate them with data from CRM, ERP, POS management systems up to e.g. weather databases, you can see in detail what works how well with which customers or sales partners. This creates a new basis for the planning and use of corresponding budgets in sales.


In summary, it can be assumed that sales management will no longer manage without data analytics. The world has become too complex, so that gut feeling and experience are no longer sufficient.

This will not turn sales managers into controllers, as many fear. Rather, they will plan better and make better decisions to ensure growth in the future.

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