How Big Data Helps Make Good Business Decisions

How Big Data Helps Make Good Business Decisions

Around 2.5 trillion bytes of data are generated around the world every day. This amount of data is called big data and corresponds to a storage capacity of 36 million iPads. Your business and your customers and prospects also produce a large amount of data every day. But which of these amounts of data are profitable for your company? With a well-thought-out big data strategy, your data stocks can be transformed into future business successes – if you do it right.

What is big data?

Big data refers to the large amount of structured and unstructured data generated and stored, for example, in companies or on the Internet. These databases are so large, fast and complex that they are often difficult or impossible to process using conventional, manual methods. As a result, these quantities of data often remain unused in companies and are not valued.

What are the dimensions of Big Data?

The size of datasets alone is not decisive for big data. To be considered big data, data must meet various characteristics. Using the 3V model, analyst Doug Laney described the term in the early 2000s:

  • Volume: mass of data sets and possibility of saving them
  • Velocity: Speed ​​of data generation, processing and analysis
  • Variety: Variety of data in different structures

Today, three other dimensions are attributed to big data:

  • Validity: Data Quality
  • Veracity: credibility of the data
  • Value: measurable value or benefit of the data

Why is big data so important?

Big data can be relevant information for your business to win. Thanks to precise analyzes of customer behavior, you can create more targeted offers for your customers that can be adjusted individually. Your data is the key to developing new business potential and building unique customer relationships.

The benefits of big data for your business:

  • cost reduction
  • time saving
  • Optimization of products & offers
  • Use business potential

This makes Big Data an important success factor for your business.

A current study by Bitkom Research shows that companies have already recognized the potential of big data and are increasingly using it: 74% of managers surveyed see big data as a key technology that will determine the competition. 57% of companies are already using this technology or are planning or discussing its use. Their goal: to better understand their customers through data analysis.

How does big data work?

In order to be able to derive business-relevant insights from your data, you must first structure it well. There are three requirements for structured data that will drive your business forward:

  • Valuable data sources like your CRM system
  • A well-thought-out Big Data strategy
  • Appropriate tools and skills for intelligent data analysis

The results you can achieve with it are enormous: By specifically combining structured and unstructured data from internal and possibly also external sources and evaluating it using Big Data technology, you filter relevant information to the company.

Big data is generated from countless sources. The most common are:

  • data flow of the Internet of Things (IoT), e.g. intelligent machines and systems
  • social media data
  • Publicly accessible databases such as the EU Open Data Portal
  • Other big data from pools of data, for example from partners, suppliers or customers

This gives you a true 360 ​​degree view of your customers. On this basis, you can make much more informed decisions than before – especially with a view to the future. The buzzword here is: “Predictive analytics”.

What is Predictive Analytics?

predictive analytics uses historical data to predict future events. It uses historical data to create a mathematical model that reveals important developments. This model is then applied to current data in order to make a prediction of future developments.

Big data in customer management

In the area of ​​customer management in particular, marketing and sales benefit from big data analytics.

A good example is this retail business: Large online stores can, for example, use appropriate analytics to determine in real time which products customers prefer and what they are likely to buy next. This brings great advantages, especially for the marketing strategy. In the B2C domain, large amounts of data form the basis for successful marketing campaigns and personalized customer service.

But also in B2B environment the possible uses are promising. Many companies have so far been content with retrospective evaluations of their CRM data and otherwise relied on their intuition. But what medium-sized company does not dream of better knowing the real value of its customers, better planning the use of its sales force or better establishing its pricing policy?

The conceivable key questions for a corresponding analysis no longer differ too much from those in B2C business:

  • What products has the customer purchased so far?
  • What are similar buyers interested in?
  • What are potential customers looking for on our website right now?

CRM as a basis for analyzes

As the hub of customer communication, your CRM system contains all the important data and the answers to your key questions. In order to be able to make effective predictions from this, you must first find “positive cases”. These are, for example, customers who have accepted certain offers and purchased products. All known customer information such as demographics, preferences, location data and transactions can then be merged, aggregated and evaluated.

A mathematical model is created from existing customer data using predictive analytics. From this, patterns of buying decisions can be derived. This model can then be applied to current data to make a prediction and suggest further actions. In this way, new cross-selling potential can be exploited and sales forecasts can also be significantly improved.

The more customer data and information available and included in the analysis, the more accurate the forecasts can be.

How to successfully implement a Big Data strategy?

The starting point of your Big Data strategy is of course your database. The benefit is that your business already has large amounts of data to work with, whether structured CRM data Where unstructured data such as emails or service logs. If necessary, external data such as information from social media, market analysis or, in the B2B environment, data from the customers provided can also be added.

It is above all a question of acquiring the adequate resources and skills to be able to evaluate the existing volumes of data with the right algorithms. Mixed teams of data professionals, salespeople and management have proven to ask the right questions.

Rely on mixed teams: When implementing big data strategies, many companies primarily encounter cultural barriers. Because where different data sources need to be brought together, the silo mentality of departments often gets in the way. It is therefore one of the most important tasks in data projects to overcome these obstacles.

Conclusion: take advantage of your data volumes

Businesses deal with massive amounts of unstructured data on a daily basis. In order for business decisions to be derived, volumes of data must be aggregated into meaningful information. Take the time to collect, store and process your data. With a powerful and flexible CRM system, you can more easily unleash the potential of Big Data.
In other words, until you get your big data fortunes structured, you’ll probably have to overcome a few hurdles. On the other hand, the gain for the future is all the greater.

Leave a Comment

Your email address will not be published.