Leveraging your CRM data in a Big Data strategy

Big Data is one of the biggest challenges for companies and one of the top priorities among company managers. This powerful field is no stranger to marketing managers, who understand its importance in getting to know the consumer by identifying patterns of behavior which help create better experiences for the customers. While 62 percent of companies believe Big Data can give them a competitive advantage, it is important to keep in mind that the success of your Big Data strategy must be associated to an appropriate implementation of your CRM data, the data quality, and the ability to visualize and use the data. A recent study shows that only <4% of companies are applying the best Big Data practices; If Big Data strategies are successfully implemented, the results are highly profitable.

Now, a Big Data strategy is not complete without complementing it with analytical processes. Companies that know how to use business data and implement Business Intelligence (BI) solutions successfully are 23 times more likely to outperform their competitors in acquiring customers and 9 times more likely to gain customer loyalty. Most of the data you need to start with are assets that you already have in your databases or in public data sources such as Social Networks, transaction log data or customer histories.

How can I then leverage my CRM data with a Big Data strategy?

Data Quality

Implementing data governance processes and creating some recurring processes can not only help you capture the most important data for your business but also prevail spending up-to-date and non-duplicates throughout the time.

Business Processes

Having a clear understanding of your company's processes will make it easier to adopt Big Data strategies. CRMs already automate and standardize business processes, so what your company needs to know is where the main sources of information are, what are the main challenges in the maturation and retention of customers, and if and where there exists a lack of information and data visualization. By understanding these processes, strengths and weaknesses, you can define the use-cases that will allow you to work on your first data scenarios. For example, if your company has low customer retention, you could perform a historical exploration of data and with some algorithms identify which patterns are replicated in the behavior of customers. This will give your company a better understanding of what process need adjustment.

Marketing Campaigns

Through your CRM Marketing software you can collect historical data from your campaigns, response from your customers, more profitable and less profitable campaigns, among other information. This information could be used in a Big Data project to design smarter campaigns that use user behavior data from any source of information, such as email, web, mobile, SMS, social networks, group messages, and others.

Information Analysis

Viewing business data will help you contextualize it and bring business cases that are defined in your Big Data project to life. Many of the first marketing reports already exist in your CRM and these should be the first sources for your CRM projects. The goal at this point is for you to see not only data of what has happened but automate these reports in processes that allow you to predict and prescribe actions based on business processes. Advanced visualization capabilities through Big Data allow organizations to obtain information that would otherwise be impossible.

All organizations are somehow destined to perform processes taking advantage of Big Data. The first use-cases should begin with a process of knowledge, patience and trial and error, so don't expect to achieve big changes in your first use-cases. Start with hypotheses (that might initially be wrong), but that will be an important part of the learning process that will lead you to improve the case section, data quality, and the visualization and projection of this information for the benefit of your company.

Know all data management terms that you need to know including easy exporting, cleaning, and importing processes best practices. Read the guide of Smartsheet: