What is the key objective of any organization? Of course, the key objective is to increase the business revenue. But, doing so is not a cakewalk when you have heaps of data lying around you. Only when you analyze the data effectively can you predict consumer behavior accurately and thus make actionable business decisions. You can choose to take the help of companies offering data consulting services to make your job easier. It is crucial to gain valuable insights into the buying behavior of your consumers to offer the right products and services, thus increasing their demand for your offerings and ultimately generating more revenues for your business. Even forward-thinking employees use quick advanced analytics solutions for effective workforce management, thus becoming highly productive and profitable.
This blog explores how you can leverage the right combination of people, data, and tools to generate higher revenues for your brand and thus alleviate your journey towards digital transformation.
Influence Price Differentiation
Operating profits are expected to increase by about 9 times if there is a price increase. To increase margins in a significant way, it is critical to have the right pricing strategy in place. As a catalyst, big data helps to achieve that. Businesses of today use customer product-level pricing strategies driven by big data analytics. Enterprise data analytics services enable organizations of all sizes to recognize how factors that are overlooked frequently – show what acts as a driver(s) for varied customer segments, and products. These factors include the economic situation in general, sales-representative negotiations, and product preferences.
Besides, automated systems help to detect narrow customer segments, ascertain what propels value for each one, and align that with historical transactional data. Based on data, businesses can thus set prices for clusters of customer segments and products. Automation even makes it easier to replicate and tweak analyses, leaving it unnecessary to begin from zero every time.
Revolutionize Marketing and Sales
As we hit the analytics umbrella, it makes sense to invest in fraud and compliance monitoring, operational analytics, enterprise data warehousing, and customer analytics. These are believed to be different aspects of sales and marketing. When you develop these facets of sales and marketing through big data analytics, there is a significant increase in revenue per customer.
In the field of marketing, big data analytics solutions help to offer insights into the content that is the most effective at all stages of a sales cycle and also how investments in customer relationship management (CRM) systems can be improved, besides developing strategies for increasing the rate of conversion, better prospect engagement, enhancing customer lifetime value, and generating a seamless flow of revenue. In the case of cloud-based enterprise software companies, big data enables them to mitigate the customer acquisition cost (CAC), customer lifetime value (CLTV), and manage several other customer-driven metrics critical to running a cloud-based business.
Areas, where data analytics solutions make for a noteworthy contribution to sales, include:
- increase sales lead quality,
- improve the accuracy of the list of prospects,
- enhance the quality of sales lead data,
- win rates and engagement strategies for decision-makers, and
- territory planning.
Improve Customer Responsiveness
The B2C and B2B marketers of today leverage big data analytics and data mining techniques to secure highly effective consumer behavior insights. Efficient and effective use of techniques in data analytics helps to develop better marketing strategies that are relationship-driven. This ultimately leads to improved customer responsiveness, sales, and higher revenues.
Also Read: Legacy Application Modernization Services
Driving Effective Customer Service with Big Data Analytics Services
Your business can easily make use of big data to make its customers happy, as big data analytics services lend you access to many valuable customer insights. You can thus drive effective customer service. With big data, your customer support teams can respond to customers faster and scale personalized support at the same time. Besides, they can support real-time customization. You can identify profitable and new product offerings faster through the use of big data with your business providing seamless omnichannel support.
Harnessing big data drives effective customer service, enabling you to improve customer retention and loyalty. This ultimately leads to increased sales and greater business opportunities.
Make Targeting More Precise with Geo-Analytical Data
Geo analytics integrates traditional analytics with location-based information to offer greater context and perspective on the data being studied. Data can thus be layered on and compared between locations, measured by regions, countries, and cities, and modified to provide unanticipated patterns and trends. Geo-analytics help add a spatial dimension to insights, accounting for distance between points, affiliation, contiguity, etc.
In today’s times, organizations focus on their go-to-market strategies through geo-analytical data. Businesses can easily execute territory segmentation based on a higher sales potential while mitigating their go-to-market costs.
In digital fields, like application development and web services, as you understand how different people in varied locations across the globe react to and interact with these products, doing so becomes crucial to provide more appealing and reliable services. Besides, geo-analytics finds its application in data visualization. Comprehending a geographic distribution can, of course, be easier when observing a density chart or heat map than rows and columns on a table.
Infuse Artificial Intelligence into Big Data
As artificial intelligence (AI) uses data from multiple sources, it can build a repository of knowledge that will eventually enable accurate predictions about customers. These predictions are based not only on what your customers buy but also on the amount of time they spend on a specific part of your website, what they look at when they browse your online business, what they buy compared to what they don’t, as well as a host of other tits-bits of data that AI can combine and add to, finally getting to know about your customers and what they want in rather an effective manner.
The capability of AI to work seamlessly with data analytics solutions is the key reason why AI and big data seem to be inseparable. AI machine learning and deep learning refer to learning from every data input and employing those inputs to generate new rules for business analytics in the future.
The Bottom Line
Remember big data analytics services have evolved, emerging into mainstream success factors for businesses. Best data analytics companies provide businesses with data consulting services helping them to increase revenues and book higher profits. Besides, big data is known to be the most suitable for AI technologies, like smart personal virtual assistants and machine learning. So, if your organization fails to move on to big data analytics services, you will become redundant and extinct in some time.
