The business ecosystem has become extremely complex. To sustain themselves in a competitive landscape, it becomes extremely important for retailers to keep growing, innovating and diversifying. This would require them to understand and fulfill customer demands while provide them with a superior customer experience. Unfortunately, the retail marketplace is riddled with slow economic growth and high costs. The problem is further compounded by new age customers who seek personalization, and promotion based pricing, which has made it extremely difficult for retailers to sustain let alone expand and attract new customers.

However, disruptive trends associated with retailers, as well as customers have resulted in massive explosion of data, which when processed and analyzed can provide retailers with a sizeable opportunity to understand customer behavior and other valuable insights that can be leveraged for informed decision making. However, processing such humongous and voluminous sets of data has become a tremendous challenge for companies, and will continue to grow in the years to come.

According to report shared by Gartner, data volume is set to grow by 800% in the years to come, 80% of which will reside as unstructured data.

To make sense of this wealth of big data, retailers require a robust data management solution that can help them retrieve and process data from multiple places. This will help them draw real-time insights for quick decision making while generate true business value. Predictive analytics has emerged as a sure shot solution to all the data woes faced by businesses. By anticipating customer needs based on post-interaction, historical and real-time analysis of big data, customer requirement can be fulfilled in a quick and efficient way.

According to statistics shared by Forbes, there has been a whopping increase in number of companies adopting predictive analytics i.e. from a mere 17% in 2015 to a massive 53% in 2017.

A combination of machine learning (ML) and artificial intelligence (AI), predictive analytics is growing all the more accurate and insightful. However, several businesses continue to assess this technology with certain degree of skepticism considering it to be too complex, disruptive and expensive to incorporate.  Listed below are few ways how businesses could achieve sales goals and increased customer satisfaction

by leveraging this smart technology:

Uncover Qualified Leads: Though, the entire practice of lead scoring has been in place since quite some time, they were largely based on guesswork and were extremely time-consuming. With a predictive analytics solution in place, businesses can make their sales and marketing teams more efficient by allowing them to access information such as whether your offering matches a potential customer’s needs, how convinced is your potential client to make a purchase, and similar other details that too in a precise way. This would allow your marketing and sales teams to better determine whether or not a customer is likely to convert and if yes what would be their potential lifetime value. This helps your sales team focus their efforts on the most rewarding areas.

Measure Call Outcomes: Till date, many companies rely on manual assessment of data in order to determine the success of a new product campaign or sales strategy. Since, data is manually recorded, it is subjective and prone to inaccuracy. This doesn’t leave much scope for precisely evaluating campaign success. With an automated system in place, calls and activity are appropriately tracked. This allows the sales team of a business to accurately measure their sales performance.

Reduce Customer Churn: Predictive analytics is extremely useful in identifying issues and trends that has a large impact on your business operation. This would help you predict when and why customers might consider abandoning you. Such important details will allow businesses to take proactive action to enhance customer experience and serve their needs in a better way.

The altering demands of technological forces have influenced the retail sector in the biggest possible way. Predictive analytics has the potential to transform businesses and industries in a way that will make them more productive, competitive and efficient. Used effectively, this technology can turn out to be the key to your outbound sales success and customer satisfaction. In a nutshell, it will act as a magic bullet that may lead to improved profits and better business outcome.

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About Author
Jaya Ghosh
Jaya Ghosh
Jaya is a content marketing professional with more than 10 years of experience into technical writing, creative content writing and digital content development. Her decade long experience lends her the ability to create content for multiple channels and across different technology verticals.
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