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The Synergy of Big Data and SuiteCRM in the future

By July 1, 2021July 13th, 2021CRM Trends

In this article, we will discuss the synergy of Big Data and SuiteCRM in the future. SuiteCRM is a major tool for enhancing the business ecosystem around the customer. With the help of Big Data, SuiteCRM can enhance new personalized services for customers and sales. It is evident that Big Data handles huge data with accuracy and CRM can be integrated and can yield better analytical insights about the business. SuiteCRM Integration with Big Data helps in decision making and managing customer aspects in terms of veracity, value, variety, speed of customer acquisition and the data volume.

CRM and Big Data

Big Data opens up a pool of opportunities in any nature of business being small, medium or big and it is important for any organization to introduce right systems for integration of huge volumes of data to derive comprehensive insights out of it. This reiterates the importance of synergy of Big Data and Free CRM as it helps in storing and recording customer insights.

With Advent of the internet and increasing momentum of social media, collating the amount of data flowing through the formal and informal channels is a big task. When the concept of Big Data comes into the picture, it tends to give a sort of semblance and order to this mammoth scale of data. It encompasses all the rapidly moving data via the digital mediums which cannot be contained with traditional storage or collation techniques. Transnational data, video, text, audio, visual images, all make interesting stories if analysed properly. Automatically this carves out a path for use of Big Data along with the CRM solution for a company for better decision making.

Sources of Big Data

Big data can be represented as structured and unstructured. The popular relevant sources for a company are listed, but not limited to, the following:

1. Social media: This is the most talked about and obviously has far-reaching tentacles. This can be harnessed to get an idea about the actual customer sentiments from live feedback and also devise marketing strategies in real time mode.

2. Geo-location aspects: This data can be very helpful to understand the global foot-stamps of the customers, their movement patterns, and accordingly optimize inventory and logistics.

3. Web visits and clicks: This can reveal customer profiles, customer segmentation etc and possible hotspots.

4. Sensor and Machine generated: Like IoT, data here can help in predictive/ preventive models.

5. Logging during various processes in the organization’s (and other authorized) servers: This can be used to understand the operational flow for handling customer service for instance. The response times could be improved, efficiency in processes and operations achieved, thereby giving a thrust to responsive IT.

6. Customer service contact points: This includes information from email, chats, omni-channel medias, or call-center records.

SuiteCRM systems, now and in the future, are leveraging the analysis of data for bettering the consumer and customer experience. This is easier said than done. Data Collation is critical and it should be meaningful. The algorithms and data analysis tools play a critical role in tapping all the customer centric data with high degree of relevance to the business

The End goals of Big Data and CRM.

The end-goals of Big Data analytics for CRM include:

  • 360-degree view of the customer with internal and external scope of business.
  • Identifying new ways to manage and sustain  customer relationships
  • Identify new sales opportunities, with better buy-in possibilities from end-users
  • Get innovative and scalable idea for new products and services
  • In-depth analysis of customers
  • Data Mining for shaping efforts towards higher levels of customer engagement
  • Metric based customer services can be targeted to measure and improve the customer-facing operations
  • Call-center productivity can be improved with detailed insights, so can internal processes be streamlined for higher efficiency and reduced costs.

In fact, data analysis within CRM can act as strong indicators of the performance of a business. Companies can use these to benchmark their own values as pitched against the competition. This could include cost vs. revenue measurements, customer retention and other parameters which can be used to improve self in order to capture sizable market share and improve customer perception.

How to go full throttle?

Technically, companies that intend to use data-driven ways to improve their CRM need to ensure the following:

  • Quality of data: especially from a variety of sources needs to be monitored for its effectiveness. A phased approach to incorporate data from various sources is best to gain maximum control.
  • Quality of the tools: The analysis is as good as the tools and techniques used. A tailor-made solution is the best, but may not be financially viable. The selection of the tools and off-the-shelf products needs to be reviewed and evaluated thoroughly and revisited periodically to assess the effectiveness.
  • Models: Predictive models and preventive models are the natural by-products of data analysis, yet parallel models like causal analysis algorithms will need to be put in place for a holistic view that looks at past, present, and future.
  • Profiling: This is not simply customer profiling as seems obvious. Data itself needs to be classified into meaningful groups, with those with similar attributes being grouped together for better data management.

Analysis over multiple facets:

Regression analysis can be used to detect anomalies or the behavior of a specific section or group from amidst a larger population. This can be used for target campaigns’ planning and execution as well.

Market basket analysis tries to group items that tend to be bought together and put them in ‘baskets’. This can be used for innovative cross-selling and up-selling efforts.

Customer sentiments try to set scores for customer sentiments and customer satisfaction levels. These can be further used to set target goals and measure results of actions taken.

Customer classification analysis tries to segregate the customers in different categories extrapolated with the views of the business needs.

The synergy of Big Data and CRM is a definitive advantage to all types of industries. The power of deep analysis is thereby affordable with many tools being available today, ensuring that the CRM investments are optimized and profits are increased.

The success of any CRM implementation largely depends on the ability of the users to efficiently work with the system. This is the best way to know more about the SuiteCRM Implementation & SuiteCRM Training.

Are you planning to integrate your big data with CRM? Your expert guide will be available at Fynsis Softlabs. Call us and step forward to boost your business.

Get to know about the Popular trends of Big Data Integration with SuiteCRM